This document summarizes a proposed system that uses an Android smartphone to control a phased array antenna. The smartphone is wirelessly tethered to a network of microcontrollers that control phase shifters connected to a 4x4 microstrip patch antenna array. The smartphone runs algorithms that use its sensors and location data to track a point in space and send control signals to electronically steer the main antenna beam toward that point. This allows the smartphone user's motion and location to cognitively control the antenna beam. The system is designed to operate in either a "Tethered Mode" where the beam tracks the smartphone orientation, or a "Tracking Mode" to follow a designated target.
A NOVEL APPROACH TO DETECT THE MOVEMENT OF TARGET IN WIRELESS SENSOR NETWORKSEditor IJMTER
The document summarizes a novel approach to detect target movement in wireless sensor networks. It proposes a prediction-based target tracking and sleep scheduling protocol (PPSS) to improve energy efficiency. The protocol reduces actively awakened nodes and controls their active time. It uses a related neighborhood graph to divide the area into non-overlapping faces for target tracking. An edge detection algorithm identifies polygon locations and wakes nodes before a target crosses to continuously monitor mobile targets. The approach achieves high tracking accuracy while reducing energy costs in wireless sensor networks.
A personalized Wireless Sensor Network Communication Model for computerizatio...IOSR Journals
This document proposes a personalized wireless sensor network communication model for automating electric power distribution. It involves using sensor networks to monitor parameters like voltage, current, temperature across the distribution system. Sensors would be grouped into clusters and use a virtual MIMO scheme within clusters to reduce errors from transients. Between clusters, a location-aware GEAR routing protocol would be used to route data to monitoring stations efficiently. This decentralized approach could automate operations faster than current centralized SCADA systems while reducing power consumption. It could also help detect electricity theft by strategically placing sensor nodes along transmission lines.
This document discusses wireless micro-sensor network models and classifies them according to communication functions, data delivery models, and network dynamics. It describes four data delivery models for sensor networks: continuous, event-driven, observer-initiated, and hybrid. The continuous model involves sensors communicating data continuously at a pre-specified rate. This taxonomy framework can help network designers choose appropriate communication protocols for different sensor network applications. The classifications are meant to aid in defining communication infrastructure and selecting protocol architectures matched to specific application requirements.
This document discusses constrained passive tracking using wireless sensor networks. It begins with an introduction to wireless sensor networks and target tracking. It then describes the proposed system for passive tracking using a wireless sensor network. The system includes initializing the network, forming clusters using K-medoids clustering, creating an object to track, determining the sensor node nearest to the object, gathering information from sensors to the base station, and analyzing the results. It discusses the K-medoids clustering and Kalman filtering algorithms used for clustering and tracking, respectively. The document provides an example of applying the K-medoids algorithm to cluster a sample dataset.
This document summarizes a study on analyzing sensor network mobility using the OMNeT++ simulation framework and MiXiM modeling toolkit. The study models sensor node mobility and examines how various parameters affect mobility and energy consumption. The simulation involves 5 mobile sensor nodes moving randomly within a 700m x 700m area. Results show that average packet delay and energy consumption increase with higher node mobility. MiXiM provides mobility and connectivity handling in OMNeT++ and allows modeling mobile wireless networks like sensor networks.
Abstract: Wireless location finding is one of the key technologies for wireless sensor networks. GPS is the technology used but it can be used for the outdoor location. When we deal with the indoor locations GPS does not work. Indoor locations include buildings like supermarkets, big malls, parking, universities, and locations under the same roof. In these areas the accuracy of the GPS location is greatly reduced. Location showed on the map in not correct when the GPS is used under the indoor environments. But for the indoor localization it requires the higher accuracy sp GPS is not feasible for the current view. And also when the GPS is used in the mobile device it consumes a lot of the mobile battery to run the application which causes the drainage of the mobile battery within some hours. So to find out the accurate location for indoor environment we use the RSSI based trilateral localization algorithm. The algorithm has the low cost and the algorithm does not require any additional hardware support and moreover the algorithm is easy to understand. The algorithm consumes very less battery as compared to the battery consumption of the GPS. Because of these this algorithm has become the mainstream localization algorithm in the wireless sensor networks. With the development of the wireless sensor networks and the smart devices the WIFI access points are also increasing. The mobile smart devices detect three or more known WIFI hotspots positions. And using the values from the WIFI routers it calculates the current location of the mobile device. In this paper we have proposed a system so that we can find out the exact location of the mobile device under the indoor environment and can navigate to the destination using the navigation function and also can enable the low consumption of the smart mobile battery for the tracking purpose.
Goals:
1. Useful at the places where GPS cannot work
2. Reduces the battery consumption
3. Routers are used.
4. Provides the path as well as the information of the location as per the requirement of user.
Smart sensors represent the next generation of tools for monitoring the environment. They contain embedded processing capabilities that allow them to perform complex sensing, data interpretation from multiple sensors, and intelligent interaction with their surroundings. Large networks of interconnected smart sensors have potential applications in areas like environmental monitoring, transportation systems, health care, surveillance, and landmine detection. However, challenges remain in optimizing resources, addressing limitations in sensors, and managing network congestion in dense deployments.
NETWORK PERFORMANCE ENHANCEMENT WITH OPTIMIZATION SENSOR PLACEMENT IN WIRELES...ijwmn
From one side, sensor manufacturing technology and from other side wireless communication technology
improvement has an effect on the growth and deployment of Wireless Network Sensor (WSN). The
appropriate performance of WSN has abundant necessity which has dependent on the different parameters
such as optimize sensor placement and structure of network sensor. The optimized placement in WSN not
only would optimize number of sensors, but also help to reach to the more precise information. Therefore
different solutions are proposed to reduce cost and increase life time of sensor networks that most of them
are concentrated in the field of routing and information transmission. In this paper, places which they need
new sensors placement or sensor movements are determined and then with applying these changes,
performance of WSN will calculate. To achieve the optimum placement, the network should evaluate
precisely and effective criteria on the performance should extract. Therefore the criteria should be ranked
and after weighting with using AHP algorithms, with use of Geographical Information System (GIS), these
weighted criteria will combined and in the locations which WSN doesn’t have enough performance, new
sensor placement will create. New proposed method, improve 21.11% performance of WSN with sensor
placement in the low performance locations. Also the number of added sensor is 26.09% which is lowest
number of added sensors in comparison with other methods.
A NOVEL APPROACH TO DETECT THE MOVEMENT OF TARGET IN WIRELESS SENSOR NETWORKSEditor IJMTER
The document summarizes a novel approach to detect target movement in wireless sensor networks. It proposes a prediction-based target tracking and sleep scheduling protocol (PPSS) to improve energy efficiency. The protocol reduces actively awakened nodes and controls their active time. It uses a related neighborhood graph to divide the area into non-overlapping faces for target tracking. An edge detection algorithm identifies polygon locations and wakes nodes before a target crosses to continuously monitor mobile targets. The approach achieves high tracking accuracy while reducing energy costs in wireless sensor networks.
A personalized Wireless Sensor Network Communication Model for computerizatio...IOSR Journals
This document proposes a personalized wireless sensor network communication model for automating electric power distribution. It involves using sensor networks to monitor parameters like voltage, current, temperature across the distribution system. Sensors would be grouped into clusters and use a virtual MIMO scheme within clusters to reduce errors from transients. Between clusters, a location-aware GEAR routing protocol would be used to route data to monitoring stations efficiently. This decentralized approach could automate operations faster than current centralized SCADA systems while reducing power consumption. It could also help detect electricity theft by strategically placing sensor nodes along transmission lines.
This document discusses wireless micro-sensor network models and classifies them according to communication functions, data delivery models, and network dynamics. It describes four data delivery models for sensor networks: continuous, event-driven, observer-initiated, and hybrid. The continuous model involves sensors communicating data continuously at a pre-specified rate. This taxonomy framework can help network designers choose appropriate communication protocols for different sensor network applications. The classifications are meant to aid in defining communication infrastructure and selecting protocol architectures matched to specific application requirements.
This document discusses constrained passive tracking using wireless sensor networks. It begins with an introduction to wireless sensor networks and target tracking. It then describes the proposed system for passive tracking using a wireless sensor network. The system includes initializing the network, forming clusters using K-medoids clustering, creating an object to track, determining the sensor node nearest to the object, gathering information from sensors to the base station, and analyzing the results. It discusses the K-medoids clustering and Kalman filtering algorithms used for clustering and tracking, respectively. The document provides an example of applying the K-medoids algorithm to cluster a sample dataset.
This document summarizes a study on analyzing sensor network mobility using the OMNeT++ simulation framework and MiXiM modeling toolkit. The study models sensor node mobility and examines how various parameters affect mobility and energy consumption. The simulation involves 5 mobile sensor nodes moving randomly within a 700m x 700m area. Results show that average packet delay and energy consumption increase with higher node mobility. MiXiM provides mobility and connectivity handling in OMNeT++ and allows modeling mobile wireless networks like sensor networks.
Abstract: Wireless location finding is one of the key technologies for wireless sensor networks. GPS is the technology used but it can be used for the outdoor location. When we deal with the indoor locations GPS does not work. Indoor locations include buildings like supermarkets, big malls, parking, universities, and locations under the same roof. In these areas the accuracy of the GPS location is greatly reduced. Location showed on the map in not correct when the GPS is used under the indoor environments. But for the indoor localization it requires the higher accuracy sp GPS is not feasible for the current view. And also when the GPS is used in the mobile device it consumes a lot of the mobile battery to run the application which causes the drainage of the mobile battery within some hours. So to find out the accurate location for indoor environment we use the RSSI based trilateral localization algorithm. The algorithm has the low cost and the algorithm does not require any additional hardware support and moreover the algorithm is easy to understand. The algorithm consumes very less battery as compared to the battery consumption of the GPS. Because of these this algorithm has become the mainstream localization algorithm in the wireless sensor networks. With the development of the wireless sensor networks and the smart devices the WIFI access points are also increasing. The mobile smart devices detect three or more known WIFI hotspots positions. And using the values from the WIFI routers it calculates the current location of the mobile device. In this paper we have proposed a system so that we can find out the exact location of the mobile device under the indoor environment and can navigate to the destination using the navigation function and also can enable the low consumption of the smart mobile battery for the tracking purpose.
Goals:
1. Useful at the places where GPS cannot work
2. Reduces the battery consumption
3. Routers are used.
4. Provides the path as well as the information of the location as per the requirement of user.
Smart sensors represent the next generation of tools for monitoring the environment. They contain embedded processing capabilities that allow them to perform complex sensing, data interpretation from multiple sensors, and intelligent interaction with their surroundings. Large networks of interconnected smart sensors have potential applications in areas like environmental monitoring, transportation systems, health care, surveillance, and landmine detection. However, challenges remain in optimizing resources, addressing limitations in sensors, and managing network congestion in dense deployments.
NETWORK PERFORMANCE ENHANCEMENT WITH OPTIMIZATION SENSOR PLACEMENT IN WIRELES...ijwmn
From one side, sensor manufacturing technology and from other side wireless communication technology
improvement has an effect on the growth and deployment of Wireless Network Sensor (WSN). The
appropriate performance of WSN has abundant necessity which has dependent on the different parameters
such as optimize sensor placement and structure of network sensor. The optimized placement in WSN not
only would optimize number of sensors, but also help to reach to the more precise information. Therefore
different solutions are proposed to reduce cost and increase life time of sensor networks that most of them
are concentrated in the field of routing and information transmission. In this paper, places which they need
new sensors placement or sensor movements are determined and then with applying these changes,
performance of WSN will calculate. To achieve the optimum placement, the network should evaluate
precisely and effective criteria on the performance should extract. Therefore the criteria should be ranked
and after weighting with using AHP algorithms, with use of Geographical Information System (GIS), these
weighted criteria will combined and in the locations which WSN doesn’t have enough performance, new
sensor placement will create. New proposed method, improve 21.11% performance of WSN with sensor
placement in the low performance locations. Also the number of added sensor is 26.09% which is lowest
number of added sensors in comparison with other methods.
A Survey on Mobile Sensing Technology and its PlatformEswar Publications
Now a days, mobile networks is increasingly becoming important part of everyday life due which there is a rapid evolution mobile phone. Mobile phone comes into a powerful sensing platform. There are many scientists which are engaged in the emerging field of mobile sensing from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. The research and development in this field is rapid resulting in indispensable carry-on of daily life. But with the increase in development, data integrity and security has also become an important factor to take into consideration. Importantly, today’s smart phones are programmable and come with a growing set of cheap powerful embedded sensors, which are enabling the emergence of personal, group, and community scale sensing applications. The mobile sensing platform provides many facilities like, it helps to communicate to Wireless sensor networks through a mobile sensor router Which attached to a users mobile phone. It helps in analysis of the sensed data which is derived from networks by cooperating with sensor middle- ware on a remote server to capture ones contexts. It also helps in providing context aware services for mobile users of cellular telephones. In this paper, we will discuss about
different mobile sensing platforms that provides context-aware services for mobile users by accessing the surrounding wireless sensor networks. Along with this, we will briefly discuss some of the emerging sensing paradigms.
Collaborative Re-Localization Method in Mobile Wireless Sensor Network Based ...CSCJournals
Localization in Mobile Wireless Sensor Networks (WSNs), particularly in areas like surveillance applications, necessitates triggering re-localization in different time periods in order to maintain accurate positioning. Further, the re-localization process should be designed for time and energy efficiency in these resource constrained networks. In this paper, an energy and time efficient algorithm is proposed to determine the optimum number of localized nodes that collaborate in the re-localization process. Four different movement methods (Random Waypoint Pattern, Modified Random Waypoint pattern, Brownian motion and Levy walk) are applied to model node movement. In order to perform re-localization, a server/head/anchor node activates the optimal number of localized nodes in each island/cluster. A Markov Decision Process (MDP) based algorithm is proposed to find the optimal policy to select those nodes in better condition to cooperate in the re-localization process. The simulation shows that the proposed MDP algorithm decreases the energy consumption in the WSN between 0.6% and 32%.
Sensor Adhoc Networks SECOM paper-Final - formatJohn A. Serri
The document proposes a reference architecture called the Basic Sensor Network Framework (BSNF) for standardized management and coordination of ad hoc sensor networks. The BSNF defines six building blocks - sensors, sensor-attached users, free agent users, managers, communication nodes, and communication sub-networks. It specifies a layered model with standardized interfaces between these elements and proposes a management approach using a standardized Management Information Base similar to SNMP. The goal is to achieve interoperability across sensor network applications through a common framework while allowing for proprietary sensor and application functionality.
Issues in optimizing the performance of wireless sensor networkseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document summarizes and compares various routing protocols for wireless sensor networks. It categorizes routing protocols into three types: data-centric, hierarchical, and location-based. For each type, it describes some representative protocols, outlines their advantages and disadvantages, and discusses their application domains. The document concludes that routing in wireless sensor networks faces challenges due to constraints like limited energy, bandwidth and memory in sensor nodes, and more research is still needed to develop efficient and adaptive routing techniques.
IRJET- Flaw Detection in Wireless Sensor Network using a LDA ClassifierIRJET Journal
1) The document discusses fault detection in wireless sensor networks using an LDA classifier. It analyzes different types of faults that can occur in wireless sensor networks, including network-level, hardware-level, and software-level faults.
2) The proposed method uses a linear discriminant analysis classifier for fault diagnosis to reduce optimization. It detects faults based on the rate of change of sensed data and Fourier transform parameters of time, space, and attribute data.
3) Once a fault is detected, fault compensation is introduced to stabilize the faulted data. The method analyzes sensor data characteristics and proposes a belief rule base model for fault diagnosis in wireless sensor networks.
Final reportTracking And Positioning Of Mobile System In Telecommunication Ne...prasanna naik
Mobile tracking and positioning involves determining the location of mobile phones within telecommunication networks. There are several techniques used, including multilateration of radio signals, GPS, and calculating distances based on time of arrival or differences in arrival time of signals at base stations. The document proposes a new "location tracking curve method" that draws curves between intersection points of circles defined by distances to base stations, to improve accuracy over existing techniques which may be affected by factors like multipath fading or non-line-of-sight conditions between the mobile phone and some base stations. This method selects the curve with the base station having smaller variance in signal arrival time to define the location tracking curve and reduce errors.
Mobile Ad hoc Network is basically a crew of mobile traffic nodes, which figure an effectual dynamic topology and built a resource mannered network. Mobile Ad hoc Networks are exceptional cases of ad hoc networks that, but it is lacking infrastructure, communicating entities pass with various accelerations. For that reason, this impedes or delay lays the foundation of well built end-to-end communication paths. So Mobile Ad-hoc Network having efficient data transfer. In this manner, MANETs have out of the common network concerns and security challenges to get the advanced connectivity, immune communications, and reputation executives systems which have an impact on the trust in cooperation and settlement between mobile networking units. In this survey paper we confer about the security attributes, attacks, and challenges of MANETs.So, it is important to have a better and good formation algorithm to connect all the nodes to each other. There must be less time, low delay time, more battery life, more speeds of packets.
A SURVEY OF ENERGY-EFFICIENT COMMUNICATION PROTOCOLS IN WSNIAEME Publication
Wireless sensor networks are harshly restricted by storage capacity, energy and computing power. Wireless Sensor Networks have acquired a lot of attention by research community, manufacturer as well as actual users for monitoring remote trades and how to gather data in different environment. The wireless sensor nodes are especially battery powered devices having life can be extended for some times while long lasting and reliable for maintaining consumption of energy and network lifetime while designs applications and protocols. So it is essential to design effective and energy efficient protocol in order to enhance the network lifetime. In this paper we present the study of different energy efficient communication protocols of Wireless Sensor Networks (WSNs).Then some of the communication protocols which are widely used in WSNs to improve network performance are also discussed advantages and disadvantages of each protocols.
Reliable Data Aggregation Protocol (RDAT) uses functional reputation to improve data reliability in wireless sensor networks. It assigns separate reputation values for sensing, routing, and aggregation actions. Nodes monitor neighbors and exchange reputation tables. Before transmitting data, nodes evaluate aggregators' aggregation reputation to detect compromised ones. Aggregators run the Reliable Data Aggregation algorithm to further ensure integrity by using routing and sensing reputation to identify false reports. Simulation results show RDAT significantly improves data reliability over attacked networks compared to existing trust systems.
IRJET- Node Deployment for Improving Coverage Area in Wireless Sensor NetworkIRJET Journal
This document summarizes a research paper on node deployment strategies to improve coverage area in wireless sensor networks. It discusses how node deployment is a key design issue that affects network performance metrics like coverage, connectivity, lifetime and robustness. There are two main types of node deployment - manual and random. Manual deployment precisely positions nodes but is not feasible for large-scale networks. Random deployment using techniques like aerial dropping can achieve wide coverage but results may not be optimal. The paper then reviews several node deployment algorithms proposed in other research to optimize coverage through approaches like virtual force-based mobility and bee colony optimization algorithms. It concludes node deployment is important for wireless sensor network effectiveness.
Optimal Operating Performances of Wireless Protocols for Intelligent Sensors ...chokrio
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements…The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wire-less technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time con-straints.
WSN nodes power consumption using multihop routing protocol for illegal cutti...TELKOMNIKA JOURNAL
The need for an automation system from a remote area cannot be separated from the role of the wireless sensor network. However, the battery consumption is still a problem that influences the lifetime of the system. This research focused on studying how to characterize the power consumption on each sensor node using multihop routing protocol in the illegal logging field, to get the prediction lifetime of the network. The system is designed by using six sensor nodes in a master-slave connection and implemented in a tree topology. Each sensor node is consisting of a sound sensor, vibration sensor, Xbee communication, current and voltage sensor, and Arduino nano. The system is tested using battery 10050 mAH with several scenarios to have calculated how long the battery lifetime can be predicted. The results stated that the master node on the network depleted the power of the battery faster than the slave node since the more slaves connected to the master, the more energy the battery consumes.
Security threats and detection technique in cognitive radio network with sens...eSAT Journals
This document discusses security threats and detection techniques in cognitive radio networks. It begins with an introduction to cognitive radio networks and how secondary users can utilize unused spectrum bands of primary users. The main security threats discussed are primary user emulation attacks, where malicious secondary users pretend to be primary users in order to disrupt communications. Energy spectrum sensing techniques are described as a way for secondary users to detect unused spectrum bands without interfering with primary users. The document concludes that primary user emulation attacks and jamming attacks are major security threats in cognitive radio networks, and improving detection of these threats is important for securing cognitive radio communications.
International Journal of Computational Engineering Research (IJCER) ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
In this paper prepared a systems to that amount the units of the fitness about structural elements within Reinforced Concrete (RC), at total times, partially atop the perfect coverage concerning sensors is provided. As a result, the records about the distances within the sensor’s near nodes and its sensing areas are the only want because concerning every sensor into the recent algorithms. Furthermore, based totally completely regarding the simulations, great improvement performs stay seen along the lifespan regarding a variety concerning existing lifespan maximization algorithms, anybody is a cease end result related to the newly proposed algorithm. The promoted sensor mark hard-ware trigger the PZT sensor and collect the responses acquires beyond the structural element. It moreover send collected information to an information middle because of similarly science yet analysis within an energy efficient manner using low power wireless verbal exchange technology. The brought ingress in conformity with and the evaluation atop the accrued information operate lie remotely executed by means of using a net interface. Performance effects showcase therefore a good deal the fractures great enough within consequence including purpose structural problems be able continue to be efficiently detected together with the promoter rule
Energy Efficiency in Key Management of Body Sensor Networkiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Io t and cloud based computational framework, evolutionary approach in health...owatheowais
The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers’ heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries.
a data mining approach for location production in mobile environments marwaeng
The document proposes a three-phase algorithm for predicting the next location of mobile users. In the first phase, mobility patterns are mined from historical user trajectory data. In the second phase, mobility rules are extracted from these patterns. In the third phase, predictions are made by matching mobility rules to a user's current trajectory. The algorithm aims to overcome limitations of prior work by discovering regular patterns in user movements and distinguishing between random and regular movements. A simulation evaluation found the proposed method achieved more accurate predictions than other methods.
Real-time human activity recognition from smart phone using linear support ve...TELKOMNIKA JOURNAL
The recognition of human activity (HAR) the use of cell devices embedded in its exten sively disbursed sensors affords guidance, instructions, and take care of citizens of smart cities. Consequently, it became essential to analyze human every day sports. To examine statistical models of human conduct, synthetic intelligence strategies such as machine studying can be used. Many studies have not studied type overall performance in real-time due to statistics series. To remedy this trouble, this paper proposes a structure primarily based on open supply technology and platforms consisting of Apache Kafka, for messages to flow over the internet, method them and provide shape for existing facts in real-time and formulates the trouble of identifying human pastime by using a smartphone tool as a type hassle using statistics collection by telephone sensors. The proposed version is skilled by some machine learning algorithms. The algorithm that has proven superior and quality results helps a linear vector machines.
ANDROID APPLICATION DEVELOPMENT FOR ENVIRONMENT MONITORING USING SMART PHONESijmnct
Mobile devices (in particular smart phones and tablets) can be used to monitor quality of life parameters.
Today mobile devices use embedded sensors such as accelerometers, compasses, GPSs, microphones, and
cameras without considering, for example, the air quality or the pollutants of the environment. This paper
presents the possibility to use the smart phones capabilities to gather data from other phones or sensors.
The environment condition’s parameters such as temperature and humidity should be monitored. This point
can be obtained by using distributed devices in different environments that containing high-resolution
sensors and a wireless transmission apparatus for transferring data to smart phones. The Bluetooth was
chosen as a transmission tool since it is embedded in all smart phones
A Survey on Mobile Sensing Technology and its PlatformEswar Publications
Now a days, mobile networks is increasingly becoming important part of everyday life due which there is a rapid evolution mobile phone. Mobile phone comes into a powerful sensing platform. There are many scientists which are engaged in the emerging field of mobile sensing from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. The research and development in this field is rapid resulting in indispensable carry-on of daily life. But with the increase in development, data integrity and security has also become an important factor to take into consideration. Importantly, today’s smart phones are programmable and come with a growing set of cheap powerful embedded sensors, which are enabling the emergence of personal, group, and community scale sensing applications. The mobile sensing platform provides many facilities like, it helps to communicate to Wireless sensor networks through a mobile sensor router Which attached to a users mobile phone. It helps in analysis of the sensed data which is derived from networks by cooperating with sensor middle- ware on a remote server to capture ones contexts. It also helps in providing context aware services for mobile users of cellular telephones. In this paper, we will discuss about
different mobile sensing platforms that provides context-aware services for mobile users by accessing the surrounding wireless sensor networks. Along with this, we will briefly discuss some of the emerging sensing paradigms.
Collaborative Re-Localization Method in Mobile Wireless Sensor Network Based ...CSCJournals
Localization in Mobile Wireless Sensor Networks (WSNs), particularly in areas like surveillance applications, necessitates triggering re-localization in different time periods in order to maintain accurate positioning. Further, the re-localization process should be designed for time and energy efficiency in these resource constrained networks. In this paper, an energy and time efficient algorithm is proposed to determine the optimum number of localized nodes that collaborate in the re-localization process. Four different movement methods (Random Waypoint Pattern, Modified Random Waypoint pattern, Brownian motion and Levy walk) are applied to model node movement. In order to perform re-localization, a server/head/anchor node activates the optimal number of localized nodes in each island/cluster. A Markov Decision Process (MDP) based algorithm is proposed to find the optimal policy to select those nodes in better condition to cooperate in the re-localization process. The simulation shows that the proposed MDP algorithm decreases the energy consumption in the WSN between 0.6% and 32%.
Sensor Adhoc Networks SECOM paper-Final - formatJohn A. Serri
The document proposes a reference architecture called the Basic Sensor Network Framework (BSNF) for standardized management and coordination of ad hoc sensor networks. The BSNF defines six building blocks - sensors, sensor-attached users, free agent users, managers, communication nodes, and communication sub-networks. It specifies a layered model with standardized interfaces between these elements and proposes a management approach using a standardized Management Information Base similar to SNMP. The goal is to achieve interoperability across sensor network applications through a common framework while allowing for proprietary sensor and application functionality.
Issues in optimizing the performance of wireless sensor networkseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document summarizes and compares various routing protocols for wireless sensor networks. It categorizes routing protocols into three types: data-centric, hierarchical, and location-based. For each type, it describes some representative protocols, outlines their advantages and disadvantages, and discusses their application domains. The document concludes that routing in wireless sensor networks faces challenges due to constraints like limited energy, bandwidth and memory in sensor nodes, and more research is still needed to develop efficient and adaptive routing techniques.
IRJET- Flaw Detection in Wireless Sensor Network using a LDA ClassifierIRJET Journal
1) The document discusses fault detection in wireless sensor networks using an LDA classifier. It analyzes different types of faults that can occur in wireless sensor networks, including network-level, hardware-level, and software-level faults.
2) The proposed method uses a linear discriminant analysis classifier for fault diagnosis to reduce optimization. It detects faults based on the rate of change of sensed data and Fourier transform parameters of time, space, and attribute data.
3) Once a fault is detected, fault compensation is introduced to stabilize the faulted data. The method analyzes sensor data characteristics and proposes a belief rule base model for fault diagnosis in wireless sensor networks.
Final reportTracking And Positioning Of Mobile System In Telecommunication Ne...prasanna naik
Mobile tracking and positioning involves determining the location of mobile phones within telecommunication networks. There are several techniques used, including multilateration of radio signals, GPS, and calculating distances based on time of arrival or differences in arrival time of signals at base stations. The document proposes a new "location tracking curve method" that draws curves between intersection points of circles defined by distances to base stations, to improve accuracy over existing techniques which may be affected by factors like multipath fading or non-line-of-sight conditions between the mobile phone and some base stations. This method selects the curve with the base station having smaller variance in signal arrival time to define the location tracking curve and reduce errors.
Mobile Ad hoc Network is basically a crew of mobile traffic nodes, which figure an effectual dynamic topology and built a resource mannered network. Mobile Ad hoc Networks are exceptional cases of ad hoc networks that, but it is lacking infrastructure, communicating entities pass with various accelerations. For that reason, this impedes or delay lays the foundation of well built end-to-end communication paths. So Mobile Ad-hoc Network having efficient data transfer. In this manner, MANETs have out of the common network concerns and security challenges to get the advanced connectivity, immune communications, and reputation executives systems which have an impact on the trust in cooperation and settlement between mobile networking units. In this survey paper we confer about the security attributes, attacks, and challenges of MANETs.So, it is important to have a better and good formation algorithm to connect all the nodes to each other. There must be less time, low delay time, more battery life, more speeds of packets.
A SURVEY OF ENERGY-EFFICIENT COMMUNICATION PROTOCOLS IN WSNIAEME Publication
Wireless sensor networks are harshly restricted by storage capacity, energy and computing power. Wireless Sensor Networks have acquired a lot of attention by research community, manufacturer as well as actual users for monitoring remote trades and how to gather data in different environment. The wireless sensor nodes are especially battery powered devices having life can be extended for some times while long lasting and reliable for maintaining consumption of energy and network lifetime while designs applications and protocols. So it is essential to design effective and energy efficient protocol in order to enhance the network lifetime. In this paper we present the study of different energy efficient communication protocols of Wireless Sensor Networks (WSNs).Then some of the communication protocols which are widely used in WSNs to improve network performance are also discussed advantages and disadvantages of each protocols.
Reliable Data Aggregation Protocol (RDAT) uses functional reputation to improve data reliability in wireless sensor networks. It assigns separate reputation values for sensing, routing, and aggregation actions. Nodes monitor neighbors and exchange reputation tables. Before transmitting data, nodes evaluate aggregators' aggregation reputation to detect compromised ones. Aggregators run the Reliable Data Aggregation algorithm to further ensure integrity by using routing and sensing reputation to identify false reports. Simulation results show RDAT significantly improves data reliability over attacked networks compared to existing trust systems.
IRJET- Node Deployment for Improving Coverage Area in Wireless Sensor NetworkIRJET Journal
This document summarizes a research paper on node deployment strategies to improve coverage area in wireless sensor networks. It discusses how node deployment is a key design issue that affects network performance metrics like coverage, connectivity, lifetime and robustness. There are two main types of node deployment - manual and random. Manual deployment precisely positions nodes but is not feasible for large-scale networks. Random deployment using techniques like aerial dropping can achieve wide coverage but results may not be optimal. The paper then reviews several node deployment algorithms proposed in other research to optimize coverage through approaches like virtual force-based mobility and bee colony optimization algorithms. It concludes node deployment is important for wireless sensor network effectiveness.
Optimal Operating Performances of Wireless Protocols for Intelligent Sensors ...chokrio
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements…The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wire-less technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time con-straints.
WSN nodes power consumption using multihop routing protocol for illegal cutti...TELKOMNIKA JOURNAL
The need for an automation system from a remote area cannot be separated from the role of the wireless sensor network. However, the battery consumption is still a problem that influences the lifetime of the system. This research focused on studying how to characterize the power consumption on each sensor node using multihop routing protocol in the illegal logging field, to get the prediction lifetime of the network. The system is designed by using six sensor nodes in a master-slave connection and implemented in a tree topology. Each sensor node is consisting of a sound sensor, vibration sensor, Xbee communication, current and voltage sensor, and Arduino nano. The system is tested using battery 10050 mAH with several scenarios to have calculated how long the battery lifetime can be predicted. The results stated that the master node on the network depleted the power of the battery faster than the slave node since the more slaves connected to the master, the more energy the battery consumes.
Security threats and detection technique in cognitive radio network with sens...eSAT Journals
This document discusses security threats and detection techniques in cognitive radio networks. It begins with an introduction to cognitive radio networks and how secondary users can utilize unused spectrum bands of primary users. The main security threats discussed are primary user emulation attacks, where malicious secondary users pretend to be primary users in order to disrupt communications. Energy spectrum sensing techniques are described as a way for secondary users to detect unused spectrum bands without interfering with primary users. The document concludes that primary user emulation attacks and jamming attacks are major security threats in cognitive radio networks, and improving detection of these threats is important for securing cognitive radio communications.
International Journal of Computational Engineering Research (IJCER) ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
In this paper prepared a systems to that amount the units of the fitness about structural elements within Reinforced Concrete (RC), at total times, partially atop the perfect coverage concerning sensors is provided. As a result, the records about the distances within the sensor’s near nodes and its sensing areas are the only want because concerning every sensor into the recent algorithms. Furthermore, based totally completely regarding the simulations, great improvement performs stay seen along the lifespan regarding a variety concerning existing lifespan maximization algorithms, anybody is a cease end result related to the newly proposed algorithm. The promoted sensor mark hard-ware trigger the PZT sensor and collect the responses acquires beyond the structural element. It moreover send collected information to an information middle because of similarly science yet analysis within an energy efficient manner using low power wireless verbal exchange technology. The brought ingress in conformity with and the evaluation atop the accrued information operate lie remotely executed by means of using a net interface. Performance effects showcase therefore a good deal the fractures great enough within consequence including purpose structural problems be able continue to be efficiently detected together with the promoter rule
Energy Efficiency in Key Management of Body Sensor Networkiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Io t and cloud based computational framework, evolutionary approach in health...owatheowais
The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers’ heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries.
a data mining approach for location production in mobile environments marwaeng
The document proposes a three-phase algorithm for predicting the next location of mobile users. In the first phase, mobility patterns are mined from historical user trajectory data. In the second phase, mobility rules are extracted from these patterns. In the third phase, predictions are made by matching mobility rules to a user's current trajectory. The algorithm aims to overcome limitations of prior work by discovering regular patterns in user movements and distinguishing between random and regular movements. A simulation evaluation found the proposed method achieved more accurate predictions than other methods.
Real-time human activity recognition from smart phone using linear support ve...TELKOMNIKA JOURNAL
The recognition of human activity (HAR) the use of cell devices embedded in its exten sively disbursed sensors affords guidance, instructions, and take care of citizens of smart cities. Consequently, it became essential to analyze human every day sports. To examine statistical models of human conduct, synthetic intelligence strategies such as machine studying can be used. Many studies have not studied type overall performance in real-time due to statistics series. To remedy this trouble, this paper proposes a structure primarily based on open supply technology and platforms consisting of Apache Kafka, for messages to flow over the internet, method them and provide shape for existing facts in real-time and formulates the trouble of identifying human pastime by using a smartphone tool as a type hassle using statistics collection by telephone sensors. The proposed version is skilled by some machine learning algorithms. The algorithm that has proven superior and quality results helps a linear vector machines.
ANDROID APPLICATION DEVELOPMENT FOR ENVIRONMENT MONITORING USING SMART PHONESijmnct
Mobile devices (in particular smart phones and tablets) can be used to monitor quality of life parameters.
Today mobile devices use embedded sensors such as accelerometers, compasses, GPSs, microphones, and
cameras without considering, for example, the air quality or the pollutants of the environment. This paper
presents the possibility to use the smart phones capabilities to gather data from other phones or sensors.
The environment condition’s parameters such as temperature and humidity should be monitored. This point
can be obtained by using distributed devices in different environments that containing high-resolution
sensors and a wireless transmission apparatus for transferring data to smart phones. The Bluetooth was
chosen as a transmission tool since it is embedded in all smart phones
Engfi Gate: An Indoor Guidance System using Marker-based Cyber-Physical Augme...IJECEIAES
The document describes an indoor guidance system called Engfi Gate that uses augmented reality and markers. It consists of three subsystems: 1) a marker-based cyber-physical interaction system that connects the physical and digital environments using visible and invisible markers, 2) an indoor positioning system that tracks a user's location using visible markers or beacons, and 3) an augmented reality system that provides guidance information to users through their mobile device or head-mounted display. The system was implemented and tested on a university campus as a way to help new students navigate buildings.
The document discusses wireless sensor networks (WSNs). It describes WSNs as consisting of distributed sensors that monitor conditions like temperature, sound, and pressure and transmit data to a central location. Modern networks are bidirectional, enabling sensor control. WSNs were initially developed for military surveillance but are now used in industrial and consumer applications. They pose challenges in deployment, location tracking, coverage, and integration of different sensor types on a single platform. Advances in energy harvesting and self-organizing networks could enable millions of low-cost sensor nodes. WSNs have applications in intrusion detection, health monitoring, and location detection.
IRJET- Survey Paper on Human Following RobotIRJET Journal
The document summarizes research on developing an autonomous human following robot. It discusses using triangulation of radio signals from a tag worn by a human to calculate the tag's location using multiple antennas on the robot. The robot would use triangulation and received signal strength to determine the tag's position and direction to follow the human. It reviews several localization algorithms and navigation techniques used in other projects. The proposed method is to use triangulation of signals from three antennas to accurately calculate the tag's position and allow the robot to autonomously follow or be remotely controlled via Bluetooth.
Comparison of Health Care System ArchitecturesIJEACS
Body area sensor network is an important
technology which is suitable for monitoring the patient’s health
and real time diagnosing the diseases. The body area network
includes the sensors which can be spread over the body or the
wearable cloth and a coordinator node which can be a mobile
or a tablet or a PDA, which receives the signal of a person’s
sensors. In the new architecture the coordinator node sends the
information to the central data server via internet or GPRS or
MANET. The central data server is responsible for saving and
analyzing and representing the received data in the text and
graphical mode and sending SMS to the patient’s family or the
nearest ambulance or physician, or the operator can call them.
The received information is analyzed by the data mining tools.
The necessary information will be sent to the physician’s
computer. Every patient has a GPS, and it is supposed that the
encryption is used for transferring information. In this paper
the new architecture is compared with the traditional one
which includes the base station and relay nodes. It is shown
that the new architecture has less delay than the traditional
one.
Intelligent GIS-Based Road Accident Analysis and Real-Time Monitoring Automat...CSCJournals
This document summarizes an intelligent road accident analysis and monitoring system that uses GIS, WiMAX/GPRS, and location-based services. The system aims to help reduce road accidents by allowing real-time accident reporting and response. It collects accident data using mobile devices and transfers it to a database via wireless networks. The data is then analyzed using statistical reports, decision making tools, and smart diagnosis to identify accident patterns and recommend safety solutions. The system is intended to help police respond faster to accidents and notify other emergency services.
The document discusses implementing a smart antenna system in mobile ad hoc networks to improve throughput and bit error rate. A smart antenna system uses an array of antennas and digital signal processing to direct transmissions toward desired nodes, allowing for increased network capacity over omnidirectional antennas. The document reviews mobile ad hoc networks, smart antenna systems, and how using smart antennas in an ad hoc network can enhance performance metrics like throughput and bit error rate.
1) The document describes the analysis and design of an electronic device to aid navigation for the visually impaired using embedded systems.
2) The device uses sensors like GPS, light sensors, and ultrasonic sensors along with actuators like vibration motors and audio to provide information on location, obstacles, and lighting levels to users.
3) The development of the device involved requirements analysis using structured analysis techniques like data flow diagrams and state transition diagrams, as well as object-oriented design using UML diagrams. Software development is done in C/C++.
International Journal of Engineering (IJE) Volume (2) Issue (1)CSCJournals
The document summarizes an intelligent GIS-based road accident analysis and real-time monitoring system that uses WiMAX/GPRS. It discusses the motivation and need for such a system to better analyze accidents and identify accident-prone locations. It then describes the system architecture, which utilizes telegeoinformatics to enable interoperability across different components. It also discusses strategies for adapting the system to different client devices. Finally, it outlines the use of terminal-centric and network-centric positioning methods like A-GPS and CGI-TA for location services and monitoring within an open, IP-based telecommunications network.
Range Free Localization using Expected Hop Progress in Wireless Sensor NetworkAM Publications
Wireless sensor network (WSN) combines the concept of wireless network with sensors. Wireless Sensor Networks
have been proposed for a multitude of location-dependent applications. Localization (location estimation) capability is
essential in most wireless sensor network applications. In environmental monitoring applications such as animal habitat
monitoring, bush fire surveillance, water quality monitoring and precision agriculture, the measurement data are
meaningless without an accurate knowledge of the location from where the data are obtained. Finding position without the
aid of GPS in each node of an ad hoc network is important in cases where GPS is either not accessible, or not practical to use
due to power, form factor or line of sight conditions. So here we are going to used DV-Hop algorithm, i.e. distance vector
routing algorithm for finding the position of sensor. Here we summarizes the performance evaluation criteria of the
wireless sensor network and algorithms, classification methods, and highlights the principles and characteristics of the
algorithm and system representative of the field in recent years, and several algorithms simulation and analysis.
LIFETIME IMPROVEMENT USING MOBILE AGENT IN WIRELESS SENSOR NETWORKJournal For Research
Wireless sensor networks have attracted much attention in the research community over the last few years, driven by a wealth of theoretical and practical challenges and an increasing number of practical civilian application. ‘one deployment, multiple applications’ is an emerging trend in the development of WSN, due to the high cost of deploying hundreds and thousands of sensors nodes over a wide geographical area and the application-specific nature of tasking a WSN. A wireless sensor network is a collection of nodes organized into a cooperative network. To reduce the energy consumption, the transmission of data between sensor nodes must be reduced in order to preserve the remaining energy in cluster node. We propose a new energy balancing architecture based on cluster with hexagonal geometry with radius R.select the base station and after select the cluster head with maximum energy of the node and after select mobile agent in minimum distance to cluster head and second highest maximum energy. And then send the data mobile agent to cluster head and cluster head to base station.and we have energy management must be followed to balance the energy in the whole network and improving network lifetime.
Abstract - Positioning is a fundamental component of human life to make meaningful interpretations of the environment. Without knowledge of position, human beings are like machines and have very limited capabilities to interact with the environment. Even machines in today’s world can be made smarter if positioning information is made available to them. Indoor positioning of pedestrians is the broad area considered in this thesis. A foot mounted pedestrian tracking device has been studied for this purpose. Systems which utilize foot mounted inertial navigation system has been in the literature for more than two decades. However very few real time implementations have been possible. The purpose of this thesis is to benchmark and improve the performance of one such implementation.
The document discusses enhancing indoor localization using IoT techniques. It proposes a framework that uses a quaternion-based extended Kalman filter for heading estimation in pedestrian dead reckoning (PDR), along with low pass filtering and adaptive step length methodology. This approach achieved an average error of 0.16 meters, representing 0.07% of the total 210 meters traveled in experiments. The document also discusses using IoT devices to further improve indoor localization accuracy.
This document describes a proposed Arduino-based human health care monitoring and control system. The system consists of three main units:
1. A sensor unit that acquires medical data like ECG, temperature, heart rate, and blood pressure from various sensors.
2. A controller unit (using an Arduino microcontroller) that compares the sensor data to normal values and can send control signals to the patient if abnormalities are detected.
3. A monitoring unit with an LCD display to show the sensor readings and system status.
The system is intended to continuously monitor vital health parameters and provide treatment or alerts if issues arise. This could help elderly or vulnerable people receive medical help and oversight without needing to be in a clinical setting
Draft activity recognition from accelerometer dataRaghu Palakodety
This document describes a framework for classifying human activities like standing, walking, and running using data from an accelerometer sensor on a smartphone. It discusses collecting raw sensor data, preprocessing the data through smoothing and feature extraction, training classifiers on extracted features, and classifying new data in real-time. Random forest classification achieved 83.49% accuracy on this activity recognition task using accelerometer data from an Android application.
This document summarizes research on algorithms for proximity estimation in sensor networks. It discusses using sensor networks to detect events observed by nodes within a certain distance of each other. It proposes an algorithm that utilizes a distributed routing index maintained by nodes in the network to process multiple proximity queries involving different event types. The document reviews several related works on localization algorithms, data-centric sensor networks, geographic routing protocols, and node localization techniques. It evaluates different wireless sensor network simulators and deployment schemes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras KlobaFwdays
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
In this session, we'll share insights on how we used PostgreSQL to facilitate precise searches across multiple fields in our mobile application. The techniques include using LIKE and ILIKE operators and integrating a trigram-based search to handle potential misspellings, thereby increasing the search accuracy.
We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
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For more details and updates, please follow up the below links.
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Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
2. 1094 IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 62, NO. 3, MARCH 2014
Fig. 1. Wirelessly tethering the array to the smartphone and cognitively
controlling the scan angle (“Tethered Control” mode) using a motion-dynamic
user interaction; (far-left) tethering the coordinate systems of the smartphone
and phased array, (mid-left) calibrating main beam to broadside when both are
coplanar, and (right) using the smartphone’s orientation and motion to scan the
main beam and track a point directed normal to the smartphone.
1) Tethered Mode: This mode demonstrates cognitive con-
trol of the antenna array using the smartphone’s motion-dy-
namic sensors and geolocation capabilities. The main beam is
wirelessly tethered in this mode to the orientation and location
of the smartphone, and the main beam of the phased array tracks
a point normal to the remotely located smartphone. Fig. 1 il-
lustrates the calibration and operation of this mode, which be-
gins in the app by tethering the coordinate systems of the array
and smartphone using a nominal calibration which considers the
coplanar alignment of the smartphone and the fixed-position an-
tenna array. The smartphone then records location and orienta-
tion data from GPS and its inertial measurement unit (IMU),
respectively. The antenna is then electronically controlled from
the phone such that the main beam scans to track the smart-
phone’s orientation with respect to the calibrated position .
This mode is defined as the “Tethered Mode” since the smart-
phone controls the main beam by cognitively scanning it to point
in the user-defined direction.
2) Tracking Mode: A more generalized mode is considered
for object tracking. Continuous or event-triggered changes are
made remotely by the smartphone in this mode to compensate
for movement or rotation of the smartphone, array, or object
being tracked. The smartphone uses geolocation and orientation
information again to remotely scan the main beam, but it uses
its resources to cognitively track the desired target located at a
moving or fixed point . The app first triggers a recording of the
orientation and location of the smartphone and antenna array,
then the app starts similar to the tethered mode. It then runs as
a background application that monitors the IMUs of the smart-
phone and array as well as the desired direction to the tracking
object at to scan the main beam accordingly. The primary
difference between this and the “Tethered Mode” reside in de-
termining and updating the tracked point . An additional re-
quirement of this mode is bi-directional communication of IMU
and GPS data to monitoring the array itself; the smartphone cog-
nitively updates this information to ensure any movement or ro-
tation of the array is accounted for in the phasing of the array.
3) Benchmarking Mode: This is a feature of the aforemen-
tioned modes, and is a set-and-hold function to manually fix
the desired scan angle of the array. This is handled remotely
from the smartphone’s touchscreen interface and is the primary
method used for anechoic chamber measurements of the proto-
type system. This can be expanded through handles for control
that can be passed into and out-of other apps or used in other
processes.
B. Android Algorithm Development
The framework for a basic tracking algorithm on the Android
smartphone can be synthesized from the two aforementioned
modes of operation. The smartphone initializes a three-dimen-
sional unit vector in both a relative and global coordinate system
using the IMU and GPS. This vector remains normal to the plane
of the smartphone in the Tethered Mode and points to a nom-
inal point in space located normal to the smartphone. After
this calibration step, the smartphone continuously reads and up-
dates its orientation and geolocation information to determine
the required angular shift of array’s main beam so it remains
steered in the directed of . These new angles are computed in
a standard rotation matrix and used to determine the required
element-level phase shifts. The pseudocode for tracking a point
in the tethered mode is illustrated below.
//Initialize
Point[]=[ 1] // normal vector for broadside rad.
User_local=Get_orient_geolocat_data(IMU, GPS);
( )=calc_quaternions()//set relative coord. sys.
//Track
Track_point_P=Get_orient_geolocat_point_data(IMU,
GPS, P);
( )=calc_quaternions(User_local, Track_point_P)
New_point[]=Track_point_P[]*Rot_matrix ( )
( )=calc_new_point_angle(New_point[]);
( )=calc_phase_shifts ( ); //payload for
packet
//Send Update
Packet[startbyte, type, length, checksum];
Send_to_control_curcuit_via_bluetooth(Packet[]);
Send_to_server_via_wifi(Packet[]);
The initialization of the system includes the creation of
quaternions (yaw , pitch , and roll ) for the smartphone’s
relative coordinate system using IMU and GPS data. If broad-
side is desired, the orientation when the array and smartphone
are coplanar (similar to the example in Fig. 1). The tracking
phase updates the quaternions and point in space, and then
uses this information to calculate the required location of the
main beam and progressive phase shifts
required to point the main beam in the tracked direction (only
a 2-D planar periodic array is considered here so is not
used). The update bundles this phase data into a variable-length
packet and sends this information to the phased array controller
where it is decoded for control, and simultaneously forked to
the server for health and state monitoring. The packet structure
discussed later in this work can facilitate a number of different
physical events within the system including calibration and the
remote real-time reprogramming of the controller for different
array topologies or operating conditions.
3. HUFF et al.: COGNITIVE MOTION-DYNAMIC TETHERING OF A PHASED ARRAY TO AN ANDROID SMARTPHONE 1095
Fig. 2. Basic layout of the modules and the types of communication used to
pass information and control between them.
C. Physical System
There are numerous possibilities available to construct the
physical network of control modules which can execute the de-
sired operation of the system. A scalable, modular, and low-
cost system using off-the-shelf components is examined here
to make its operation scalable and multifunctional. Fig. 2 shows
the basic layout of the system in this work, and the types of com-
munication used to connect the modules. The smartphone in this
diagram shares two wireless connections; the first is the Blue-
tooth connection to a series of microcontrollers (MCUs) which
share control information and the second is the Wi-Fi connec-
tion with a remote server to capture network diagnostic infor-
mation. The “radio” block in this setup is not shown with any
connection to other system components, but it can be connected
into the wired or wireless networks; for this work it will only be
implemented as a CW source for RF measurements.
A master-slave MCU network has wireless master nodes that
reconfigure the role of slave nodes, processes control informa-
tion sent from the smartphone and route packet information to
slave controllers on a wired Inter Integrated Circuit net-
work. The slave nodes decode the payload to produce the DC
bias voltage on a control board and other operational or sensing
tasks. A bank of phase shifters feeding the antenna array through
a RF power divider network receives DC voltages from the
board to apply the desired phase shift at the carrier signal. In
this configuration the MCU network gathers information from
external sensors such as local IMUs and returns this to the smart-
phone. Additionally, the control board uses a Serial Peripheral
Interface (SPI) to communicate with the MCUs (as opposed
to since this can be implemented as a secondary bus for
information.
III. MODULES AND SUBSYSTEMS
A. Antenna Array
A 4 4 rectangular planar periodic array of probe-fed,
square, linearly polarized microstrip patch antennas with a
width and resonant length was designed on a 1.575 mm
Fig. 3. Measured impedances (overlaid Smith chart) and VSWR for each of
the sixteen elements of the fabricated array (overlaid photo).
(62 mil) thick RT/Duroid 5880® [7] substrate with a free-space
element spacing to test the proposed control
system. A design frequency within the 2.4–2.484 GHz ISM
band was desired so a resonant frequency of 2.45 GHz was
chosen for the patch antenna and array. The array was simu-
lated [8] then fabricated with elements using mm and
mm. The measured input impedances of the sixteen
patches in the 4 4 array from 2 GHz to 3 GHz on a Smith
chart and the corresponding measured VSWR are included in
Fig. 3 along with a photo of the fabricated array.
The measurements are in very close agreement with the
expected results (not shown) and all coupling behavior is
nominally within levels associated with this element and array
topology. Each element has a with a center fre-
quency GHz and an impedance variation of less than
3% at resonance amongst all patches. This is close to calculated
and simulated models, and the 2:1 VSWR matched impedance
bandwidth shared by all element falls within the ISM band. The
slight upward shift is attributed to the mechanical milling of
the array, but the matched impedance bandwidth still satisfies
the design criterion so no modifications were made.
B. Linearization and Control of Phase Shifters
Commercially available electronically-controlled analog
phase shifters [9] with a 0 –450 phase response over a 0–13
V DC control voltage range were chosen for the phased array
system (one at the output of each port of the power divider).
Each module was individually characterized using a custom
LabView VI [10] which automated measurements by repeat-
edly cycling a DC control voltage in 100 mV increments while
recording the unwrapped phase shift. A maximum variation of
3% from 9–12 Volts was observed as a maximum between the
sixteen phase shifters.
This characterization provided insight into the repeatability
and consistency amongst phase shifter units, but the primary
goal of the activity was to develop a mapping between the ap-
plied voltage and the corresponding phase shift that could be
linearized and programmed as a function in the control module.
To do this, a simple fourth-order polynomial was first generated
to fit the experimental data. This polynomial was then used to
linearize the phase shifter control data, such that the 0–12 V
range could be mapped in the control board to produce uniform
4. 1096 IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 62, NO. 3, MARCH 2014
Fig. 4. Linearizing mapping function used by control board to provide uniform
incremental phase shifts.
increments in the phase shift as a function of applied control
signal. The mapping has been plotted in Fig. 4, and is shown
as a control voltage that is plotted as a function of the desired
phase shift (as the slave MCUs interprets this).
C. Control Board
The control voltage to the analog phase shifter is the first link
in the control path (moving from the antenna array toward the
smartphone) and can be implemented in a variety of ways from
the MCU. Pulse width modulation (PWM) is a common fea-
ture of MCUs, but providing independent PWM signals for each
phase shifter is explicitly avoided since the number of PWM
output pins on a given MCU platform is typically quite small in
comparison to other I/O. This limits the scalability and increases
the susceptibility of the control signals to system noise. It is
also good practice to deploy current and/or voltage buffering
in stages to avoid placing a significant current draw on the lim-
ited resources of the low cost MCU, so an alternative approach
as developed.
A series of digital potentiometer [11] circuits are designed to
overcome the PWM limitations and provide the analog phase
shifters with a high fidelity DC control signal. They are assem-
bled using low power components and can be quickly reconfig-
ured to meet the demands of the algorithm. They use SPI com-
munication to write resistance values into its internal memory,
operate at the TTL voltage levels from the MCU, and are ca-
pable of producing highly accurate and reproducible voltages.
The digital potentiometers in this work accept commands on the
SPI bus to set the internal voltage divider to a desired position
(the 128-position wiper in this work), and they are capable of
communicating their resistance position to a central controller
for state and heath monitoring.
A series of operational amplifier circuits were designed to
achieve the maximum of 12 V DC for the phase shifter since the
digital potentiometers are only capable of producing a voltage
range of 0 V to 5 V, so simple non-inverting operational am-
plifier circuits with carefully selected resistances are used to
provide the appropriate amplification stage needed to both in-
crease the range from 5 V up to 12 V and buffer the TTL output
current capacity of the potentiometer. In this design, the slave
node MCUs act as local-level controller which is responsible
for a select subset of phase shifters. It must also be capable of
reading external devices and sensors, provide data processing
power, and provide open connections to other modules.
The MCU and control board are required to be modular in
this work to accommodate both small and large scale antenna
configurations (in subarrays). Each slave node’s MCU [12] in
this work is capable of handling communication for up to eight
phase shifters, which is limited only by the amount of digital
communications pins that the MCU has available. Two slave
nodes (denoted “A” and “B”) were therefore required a sixteen
element array. This could be reduced through multiplexing and
other techniques, but this limits the scalability of the system and
its ability to simultaneously control all sixteen phase shifters.
Slave nodes don’t necessarily need to communicate with each
other, but in this implementation each slave MCU must receive
the same information so algorithmic outcomes and control in-
formation are preserved across the array for integrity and error
checking.
The master node MCU [13] facilitates communication and
control. Its primary functions include communicating with
the smartphone via Bluetooth, communicating with the phase
shifter control modules, and maintaining inter-communication
at the control level. We establish this controller as the master
in a master-slave style of communication among the control
modules using . The master checks on how many control
modules are online and communicates operation and state and
information it receives from the smartphone via Bluetooth. The
master is also responsible for initially verifying data integrity
before passing information on to slaves and control networks.
It is also able to reconfigure the slave nodes so they can control
different types of phased array topologies.
D. Smartphone
An Android [14] smartphone ([15] in this work) serves as
the central controller of the phased array system in this work. It
is responsible for calculating phase shifts, communicating with
the server and control network, and addressing the interactive
needs of the user. This has been programmed in Java [16] using
the Android SDK [17] in Eclipse [18], and the resulting inter-
face allows the user to dynamically switch between the system
modes of operation while also providing interfaces to connect
to the server and control network. Important real time informa-
tion such as system status, phase shift, and main beam location
are shown in real time to the user. Notably, all controls and
information including network clock time, phase information,
and system power usage are derived from the algorithms pro-
grammed into the smartphone.
E. Fully Assembled System
Fig. 5 shows the fully assembled control board, power
divider/combiner, MCUs, and other components. These com-
ponents are mechanically fastened onto a 0.5 in thick Lucite
mounting plate using nylon hardware. This plate is affixed
to a square PVC frame (0.5 in diameter), which has PVC
connections below the power divider (not visible in the photo)
for mounting antenna arrays, and additional connections for
5. HUFF et al.: COGNITIVE MOTION-DYNAMIC TETHERING OF A PHASED ARRAY TO AN ANDROID SMARTPHONE 1097
Fig. 5. Fully assembled smartphone phased array controller.
mounting and mechanical stability to the rotating pedestal in
the anechoic chamber.
IV. APPLICATION (App) AND SYSTEM OPERATION
A. Synchronization
The smartphone serves a synchronizing module in this work
that all other modules and subsystems follow. It sets the master
clock and promotes an effective communications scheme be-
tween all other modules. As such, the smartphone is arguably
the most important part of the entire control system so it is nec-
essary to understand how the data will flow from one module to
the other (in a layered approach) to ensure each sub-module can
effectively use the same protocol. We adopt a model similar to
the Open Systems Interconnection (OSI) model to construct the
network architecture of the entire system. This is illustrated in
Fig. 6, where both wired and wireless physical implementations
are used to communicate data as it scales from physical trans-
mission to algorithms that run at the application layer. We use
existing routing and control protocols to interface the hardware
with the software at the data link and routing layer.
The networking of low-cost MCUs in this design and the con-
trol architecture that relies explicitly on the smartphone as a
decentralized resource for computing and synchronization are
two very unique features of this work. The MCUs’ roles in
translating control voltages from packetized information and
providing heath and state monitoring information are key pro-
cesses, but the master MCU also facilitates the wireless tether to
the smartphone. This deviates from traditional digital design im-
plementations which might rely more on centralized computing
resource such as field programmable gate arrays (FPGAs). The
streamlined interconnection of MCUs also provides a degree
of flexibility in the design since it is possible remotely repro-
gram or repurpose them once they are integrated into the system.
This requires a detailed examination of the communication and
networking protocols that link all of these different subsystems
together.
B. Packetization
There exists a significant amount of communication between
system subcomponents and the aforementioned modules.
Fig. 6. Application, routing, link, and physical layers in the Android program.
Fig. 7. Variable-payload packet structure used for network protocol.
Custom protocols are developed as an essential part of this
design so that each module may communicate in an emulating
architecture similar to the OSI model. The smartphone com-
municates phase information to the control network and server,
but also relays network information from onboard sensors
to the server as well (these are not used in this discussion).
Each antenna phase shifter is addressed in this model to allow
individual reconfiguration of antennas (if or when desired) and
accommodate various array structures and subsystems. The
concept packet structure shown in Fig. 7 was used to facilitate
this desired functionality.
The Startbyte is used to indicate to a device that a packet is
starting. Length indicates how many bytes after the Startbyte
exist in the packet, allowing a variable payload structure. Fram-
etype is used to distinguish the type of information passed in
the Payload. As stated, the information may be phase shifts, re-
configuration information for an antenna, power usage, or other
variables. FrameID permits the system to use handshakes if
needed emulating a SYN/ACK TCP approach. The Payload, or
information, is variable in length and is essential for system op-
eration. A Checksum is calculated at each reception endpoint to
ensure the integrity of data as it moves through system compo-
nents. If at any point the checksum is incorrect, the packet is
dropped and a new packet is requested.
C. Networking and Multithreading
Socket threads are initialized to have the smartphone create
a wireless connection to the server and Bluetooth master MCU.
These threads are separate processes which handle data trans-
mission and packet inspection for the aforementioned custom
protocol. The system enters into a continual while loop that may
6. 1098 IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 62, NO. 3, MARCH 2014
Fig. 8. High-level system operation and function representation for all
modules.
be interrupted from the socket threads when new data is avail-
able; however, it continues to loop checking for user input and
calculating the progressive phase shift values based on oper-
ating state. It forwards the information to the server and con-
trol network and continues to loop. At any time, the user may
change the input to adjust the operating state which is processed
to determine what data is calculated.
Each sub-module in this hardware arrangement is set-up to
maintain specific threads in the software to help implement spe-
cific functions. Fig. 8 shows the high level system and func-
tions for all modules. Handlers in this diagram denote threads
executed by the primary operating system which act asynchro-
nously with the overall synchronization clock and primary func-
tions under a specific thread are noted in Fig. 8 using “();”. The
use of the smartphone as a central controller is also illustrated in
Fig. 8; it contains the synchronization clock for the entire system
(i.e., the max rate in seconds at which the system can change its
operating state).
The smartphone also realizes the state of operation noted by
the control algorithms. Within this, the data handler realizes
the state and gathers the information from separate functions
to meet the state realization. It uses a socket handler to transfer
the calculated information from the data handler to the appro-
priate connection. The master controller also contains a socket
handler for the Bluetooth connection to receive packets from
the smartphone; it has a data handler to process the packet in-
formation to determine data integrity. It uses a network handler
and corresponding function to communicate with the slave
controllers and control board.
The slave controllers are responsible for conducting protocol
analysis for data integrity, converting phase shift information
into DC bias voltages, and realizing any external hardware that
may be connected on the bus. It also has a state realization
function for other uses that are beyond the scope of this paper.
A network handler is used to communicate with the control
board using SPI (this communication is unidirectional). The pri-
mary SPI function accesses the respective digital potentiometer
and writes the appropriate DC bias value to its memory. The
server has a socket handler to communicate with the smartphone
and display real time information remotely. Little data handling
must be conducted as the information from the smartphone is
already processed.
V. MEASURED RESULTS
Both the communications platform and the control board
were thoroughly tested to ensure that the system was producing
the correct phase shifting behavior results prior to testing the
array in the anechoic chamber. The master and slave MCUs
were programmed accordingly and connected to the control
board (with some additional logic) to test the protocols and
functionality in hard-coded tests, then the smartphone was
wirelessly tethered to the control network. Expected control
voltages were observed at all sixteen ports on the control board.
The discretized phase shifts from these measured voltages were
then inserted into simulation [8] to test beam steering accuracy.
These results indicated that the intercommunication between
modules and desired control was achieved, so the “Bench-
marking Mode” was chosen to control the array while testing
in the anechoic chamber. The following system algorithm is
programmed from the smartphone’s perspective for this; it
allows the user full control over the operating state of the beam
steering system from the user’s interface of the GUI running on
the smartphone.
SocketThread1=new
Thread(connect_Bluetooth_socket());
SocketThread2=new Thread(connect_Server_socket());
While True:
Check_user_input();
If(!manual_user_control())
Point[]=|object_position[]-our_position[]|
Else
Point[] = [ 1] //broadside radiation
If(!manual_object_tracking)
( )=Bluetooth.read(orientation_sensor);
Else
( )=Get_orientation_data();
New_Point[]=Point[]*Rot_matrix ( );
( )=calc_new_point_angles(New_Point[]);
( )=calc_phase_shifts( );
Packet[startbyte, type, length, checksum];
SocketThread1.send(Packet[]);
SocketThread2.send(Packet[]);
The measurement campaign for the antenna array only ex-
amined a classical progressive phase shift for the periodic array
7. HUFF et al.: COGNITIVE MOTION-DYNAMIC TETHERING OF A PHASED ARRAY TO AN ANDROID SMARTPHONE 1099
Fig. 9. Measured Co- and cross-pol E-plane radiation patterns.
Fig. 10. Measured Co- and cross-pol H-plane radiation patterns.
based on the user-input scan angle. This provides a baseline
performance metric for the system, but a range of more ad-
vanced array scanning profiles and element topologies are pos-
sible with this framework. In this work, the array was only
scanned symmetrically from through broadside in
both the E-plane and H-plane of the patch array using 15 in-
crements. Figs. 9 and 10 show the measured co- and cross-
pol. in the E- and H-planes, respectively. The main beam re-
mained within 2 of the desired angle in all tests; results for the
un-scanned plane were also measured and showed no anomalies
so this data was not included.
A visualization tool was connected to an Apache server to
remotely monitor and display real-time system information
(or from a database) such as the three-dimensional beam
location, phase shifts of elements, and other characteristics.
Network characteristics, such as power usage, are stored in a
database and can be accessed via web. The server is capable
of responding to HTTP and HTTPS requests; the latter being
useful for secure remote monitoring situations. The primary
tool used to construct the graphical interpretation of the beam
was through a tool called “Processing” [19], which like the
Android environment, is written in Java. The server display
in Fig. 11 includes the directional cosine angles from the
calibrated axis (shown as ) and the progressive phase
shifts are displayed as “B X” and “B Y” for the and
axes respectively. In addition, a color coded map of each
Fig. 11. Server display and real-time visualization tool created in Processing.
antenna element displays the phase shift corresponding to the
current data. The large rectangular object in the middle of the
screen represents the beam of the array, and moves in real-time
according to movement of the main beam’s direction.
VI. DISCUSSION
There are several notable achievements in this work from a
concept and operational perspective, but there are also several
limitations with respect to the implementation and components
used to execute the system. These are illuminated in this section
in an attempt to provide a broader view of the intended contri-
bution and highlight some potential directions for future work
in this area. One of these is a practical limitation that manifests
itself in the bandwidth provided by the antenna array. It is fully
acknowledged that this microstrip patch antennas in this work
do not provide continuous coverage across the entire ISM band.
The intent here is to provide a detailed system-level discussion
so the antenna was designed for experimental observations and
chosen to remain tractable, and purely for demonstrative pur-
poses. The discussion is application agnostic for this purpose
and it is assumed that any antenna (wideband, reconfigurable,
etc.) could be placed directly into this system and perform as
expected.
The array topology represents another potential concern in
the hierarchical view of complexity, although perhaps more
from the standpoint of electromagnetic novelty [20]–[24]. The
square array with equal spacing and a progressive phase shift
when scanning are clearly unremarkable in the context of the
complexity that these elements of the design can achieve.
However, like the antenna, this was chosen purely as a well-un-
derstood and tractable implementation of an antenna array
that could be used in this work without diluting the intended
discussion on the system. Items such as scan resolution also
arise in this context since the digital system quantizes the input
to the analog phase shifter. Hence, if the PWM signal was used
directly from the MCU the resolution would be limited to the
bit resolution of the PWM output ( steps for the 8-bit
PWM). Quantization is limited here only by the bit wiper
positions of the SPI digital potentiometers. These were chosen
for demonstrative purposes, so this granularity ( steps for
9. HUFF et al.: COGNITIVE MOTION-DYNAMIC TETHERING OF A PHASED ARRAY TO AN ANDROID SMARTPHONE 1101
Gregory H. Huff (S’03–M’07–SM’11) was born
in Oklahoma City, OK, USA, in 1975 and received
the B.S., M.S., and Ph.D. degrees in Electrical
Engineering from the University of Illinois at Ur-
bana-Champaign, IL, USA, in 2000, 2003, and 2006,
respectively.
He has been with the Electromagnetics and Mi-
crowave Laboratory in the Department of Electrical
and Computer Engineering at Texas A&M University
in College Station, TX, USA, since 2006 and is cur-
rently at the rank of Associate Professor. His trans-
disciplinary research in multifunctional antennas and superconfigurable systems
blends concepts from material science engineering, aerospace engineering, and
other focus areas to examine biologically inspired concepts for reconfigurable
antennas and smart skins, tunable fluidic and nanoparticle material systems, and
collaborative beamforming in autonomous and unpiloted vehicles, and other en-
abling technologies including the use of smartphones and tablets in embedded
systems for adaptive wireless sensor networks.
Prof. Huff was a recipient of the Presidential Early Career Award for Sci-
entists and Engineers (PECASE) award through the Department of Defense
in 2008 and the NSF CAREER award in that same year. Prof. Huff has been
awarded best paper and presentation awards as an author and co-author, in-
cluding the IEEE AP-S H. A. Wheeler Applications Prize Paper Award in 2004,
and teaching awards including the IEEE AP-S Donald G. Dudley, Jr. Undergrad-
uate Teaching Award in 2010. In addition to numerous other professional and
scholarly activities, Prof. Huff serves as the faculty mentor for the IEEE student
chapter at Texas A&M University and is involved in many project-based initia-
tives geared towards increasing undergraduate students in multidisciplinary
Jean-François Chamberland (S’98–M’04–SM’09)
received the Ph.D. degree in 2004 from the Uni-
versity of Illinois at Urbana-Champaign, IL, USA,
the M.S. degree in 2000 from Cornell University,
Ithaca, NY, USA, and the B.Eng. degree in 1998
from McGill University, Montreal, Canada, all in
electrical engineering.
He joined Texas A&M University in 2004, where
he is currently an Associate Professor in the Depart-
ment of Electrical and Computer Engineering. His
research interests include communication systems,
queueing theory, detection and estimation, and statistical signal processing.
Dr. Chamberland was the recipient of a Young Author Best Paper Award from
the IEEE Signal Processing Society in 2006. He also received a Faculty Early
Career Development (CAREER) Award from the National Science Foundation
in 2008.
Jeffery S. Jensen (S’14) received the B.S. and M.S.
degrees in electrical engineering in 2010 and 2012,
respectively, from Texas A&M University, College
Station, TX, USA, where he is currently working to-
ward the Ph.D. degree in the Electromagnetics and
Microwave Laboratory, Department of Electrical and
Computer Engineering.