RSSI based localization techniques are effected by environmental factors which cause the RF
signalsemitted from transmitter nodes fluctuate in time domain. These variations generate fluctuations on
distance calculations and result false object position detection during localization.Smoothing procedures
must be applied on distance values either collectively or individually to minimize these fluctuations. In this
study,proposed detection system has two main phases. Firstly, calibration of RSSI values with respect to
distances and calculation of environmental coefficient for each transmitter.Secondly, position estimation of
objects by applyingiterative trilateration on smoothed distance values. A smoothing algorithm is employed
to minimize the dynamic fluctuations of RF signals received from each reference transmitter node.
Distances between the reference nodes and the objects are calculated by deploying environmental
coefficients. Experimental measurements are carried out to measure the sensitivity of the system. Results
show that the proposed system can be deployed as a viable position detection system in indoors and
outdoors.
Investigations on real time RSSI based outdoor target tracking using kalman f...IJECEIAES
Target tracking is essential for localization and many other applications in Wireless Sensor Networks (WSNs). Kalman filter is used to reduce measurement noise in target tracking. In this research TelosB motes are used to measure Received Signal Strength Indication (RSSI). RSSI measurement doesn‟t require any external hardware compare to other distance estimation methods such as Time of Arrival (TOA), Time Difference of Arrival (TDoA) and Angle of Arrival (AoA). Distances between beacon and non-anchor nodes are estimated using the measured RSSI values. Position of the nonanchor node is estimated after finding the distance between beacon and nonanchor nodes. A new algorithm is proposed with Kalman filter for location estimation and target tracking in order to improve localization accuracy called as MoteTrack InOut system. This system is implemented in real time for indoor and outdoor tracking. Localization error reduction obtained in an outdoor environment is 75%.
Adaptive Indoor Localization by using Environmental Thresholding and Virtual ...IJERA Editor
Environmental Thresholding and virtual fingerprinting techniques are deployed with Wireless Sensor Nodes (WSN) to create an adaptive localization system. A virtual fingerprint map of RSSI values is generated across the test area. RSSI amplitude correction phase is introduced with respect to local environmental parameters on virtual and recorded RSSI values at fingerprint grid points and unknown object points. Localization algorithms are employed to determine the unknown object locations. Localization accuracies of around 35cm at a grid space of 1m are obtained during the calculations.
A Novel Range-Free Localization Scheme for Wireless Sensor NetworksGiselleginaGloria
This paper present a low-cost yet effective localization scheme for the wireless sensor networks. There are many studies in the literature of locating the sensors in the wireless sensor networks. Most of them require either installing extra hardware or having a certain amount of sensor nodes with known positions. The localization scheme we propose in this paper is range-free, i.e., not requiring extra hardware devices, and meanwhile it only needs two anchor nodes with known position. Firstly, we install the first anchor node at the lower left corner (Sink X) and the other anchor node at the lower right corner (Sink Y). Then we calculate the minimum hop counts for each unknown node to both Sink X and Sink Y. According to the minimum hop count pair to Sink X and Sink Y of each node, we can virtually divide the monitored region into zones. We then estimate the coordinate of each sensor depending on its located zone. Finally, we adjust the location estimation of each sensor according to its relative position in the zone. We simulate our proposed scheme and the well-known DV-Hop method. The simulation results show that our proposed scheme is superior to the DV-Hop method under both low density and high density sensor deployments.
A New Approach for Error Reduction in Localization for Wireless Sensor Networksidescitation
This paper proposes an improved RSSI-based localization method for wireless sensor networks to reduce localization error. The key points are:
1) Experimental RSSI measurements are taken between sensor nodes at various transmission power levels in an indoor environment.
2) A path loss model is fitted to the RSSI data to estimate distances, but this results in significant errors.
3) The model is improved by incorporating the mean error observed for each power level, which reduces localization error by 31-53% across power levels.
4) The improved method provides more accurate localization especially at higher transmission powers, important for applications requiring precise location information.
TARGET LOCALIZATION IN WIRELESS SENSOR NETWORKS BASED ON RECEIVED SIGNAL STRE...sipij
We consider the problem of localizing a target taking the help of a set of anchor beacon nodes. A small
number of beacon nodes are deployed at known locations in the area. The target can detect a beacon
provided it happens to lie within the beacon’s transmission range. Thus, the target obtains a measurement
vector containing the readings of the beacons: ‘1’ corresponding to a beacon if it is able to detect the
target, and ‘0’ if the beacon is not able to detect the target. The goal is twofold: to determine the location
of the target based on the binary measurement vector at the target; and to study the behaviour of the
localization uncertainty as a function of the beacon transmission range (sensing radius) and the number of
beacons deployed. Beacon transmission range means signal strength of the beacon to transmit and receive
the signals which is called as Received Signal Strength (RSS). To localize the target, we propose a gridmapping
based approach, where the readings corresponding to locations on a grid overlaid on the region
of interest are used to localize the target. To study the behaviour of the localization uncertainty as a
function of the sensing radius and number of beacons, extensive simulations and numerical experiments
are carried out. The results provide insights into the importance of optimally setting the sensing radius and
the improvement obtainable with increasing number of beacons.
This document provides an overview of digital image processing. It discusses what image processing entails, including enhancing images, extracting information, and pattern recognition. It also describes various image processing techniques such as radiometric and geometric correction, image enhancement, classification, and accuracy assessment. Radiometric correction aims to reduce noise from sources like the atmosphere, sensors, and terrain. Geometric correction geometrically registers images. Image enhancement improves interpretability. Classification categorizes pixels. The document outlines both supervised and unsupervised classification methods.
Investigations on real time RSSI based outdoor target tracking using kalman f...IJECEIAES
Target tracking is essential for localization and many other applications in Wireless Sensor Networks (WSNs). Kalman filter is used to reduce measurement noise in target tracking. In this research TelosB motes are used to measure Received Signal Strength Indication (RSSI). RSSI measurement doesn‟t require any external hardware compare to other distance estimation methods such as Time of Arrival (TOA), Time Difference of Arrival (TDoA) and Angle of Arrival (AoA). Distances between beacon and non-anchor nodes are estimated using the measured RSSI values. Position of the nonanchor node is estimated after finding the distance between beacon and nonanchor nodes. A new algorithm is proposed with Kalman filter for location estimation and target tracking in order to improve localization accuracy called as MoteTrack InOut system. This system is implemented in real time for indoor and outdoor tracking. Localization error reduction obtained in an outdoor environment is 75%.
Adaptive Indoor Localization by using Environmental Thresholding and Virtual ...IJERA Editor
Environmental Thresholding and virtual fingerprinting techniques are deployed with Wireless Sensor Nodes (WSN) to create an adaptive localization system. A virtual fingerprint map of RSSI values is generated across the test area. RSSI amplitude correction phase is introduced with respect to local environmental parameters on virtual and recorded RSSI values at fingerprint grid points and unknown object points. Localization algorithms are employed to determine the unknown object locations. Localization accuracies of around 35cm at a grid space of 1m are obtained during the calculations.
A Novel Range-Free Localization Scheme for Wireless Sensor NetworksGiselleginaGloria
This paper present a low-cost yet effective localization scheme for the wireless sensor networks. There are many studies in the literature of locating the sensors in the wireless sensor networks. Most of them require either installing extra hardware or having a certain amount of sensor nodes with known positions. The localization scheme we propose in this paper is range-free, i.e., not requiring extra hardware devices, and meanwhile it only needs two anchor nodes with known position. Firstly, we install the first anchor node at the lower left corner (Sink X) and the other anchor node at the lower right corner (Sink Y). Then we calculate the minimum hop counts for each unknown node to both Sink X and Sink Y. According to the minimum hop count pair to Sink X and Sink Y of each node, we can virtually divide the monitored region into zones. We then estimate the coordinate of each sensor depending on its located zone. Finally, we adjust the location estimation of each sensor according to its relative position in the zone. We simulate our proposed scheme and the well-known DV-Hop method. The simulation results show that our proposed scheme is superior to the DV-Hop method under both low density and high density sensor deployments.
A New Approach for Error Reduction in Localization for Wireless Sensor Networksidescitation
This paper proposes an improved RSSI-based localization method for wireless sensor networks to reduce localization error. The key points are:
1) Experimental RSSI measurements are taken between sensor nodes at various transmission power levels in an indoor environment.
2) A path loss model is fitted to the RSSI data to estimate distances, but this results in significant errors.
3) The model is improved by incorporating the mean error observed for each power level, which reduces localization error by 31-53% across power levels.
4) The improved method provides more accurate localization especially at higher transmission powers, important for applications requiring precise location information.
TARGET LOCALIZATION IN WIRELESS SENSOR NETWORKS BASED ON RECEIVED SIGNAL STRE...sipij
We consider the problem of localizing a target taking the help of a set of anchor beacon nodes. A small
number of beacon nodes are deployed at known locations in the area. The target can detect a beacon
provided it happens to lie within the beacon’s transmission range. Thus, the target obtains a measurement
vector containing the readings of the beacons: ‘1’ corresponding to a beacon if it is able to detect the
target, and ‘0’ if the beacon is not able to detect the target. The goal is twofold: to determine the location
of the target based on the binary measurement vector at the target; and to study the behaviour of the
localization uncertainty as a function of the beacon transmission range (sensing radius) and the number of
beacons deployed. Beacon transmission range means signal strength of the beacon to transmit and receive
the signals which is called as Received Signal Strength (RSS). To localize the target, we propose a gridmapping
based approach, where the readings corresponding to locations on a grid overlaid on the region
of interest are used to localize the target. To study the behaviour of the localization uncertainty as a
function of the sensing radius and number of beacons, extensive simulations and numerical experiments
are carried out. The results provide insights into the importance of optimally setting the sensing radius and
the improvement obtainable with increasing number of beacons.
This document provides an overview of digital image processing. It discusses what image processing entails, including enhancing images, extracting information, and pattern recognition. It also describes various image processing techniques such as radiometric and geometric correction, image enhancement, classification, and accuracy assessment. Radiometric correction aims to reduce noise from sources like the atmosphere, sensors, and terrain. Geometric correction geometrically registers images. Image enhancement improves interpretability. Classification categorizes pixels. The document outlines both supervised and unsupervised classification methods.
This document summarizes positioning techniques for wireless sensor networks (WSNs) and Internet of Things (IoT) systems. It discusses both range-based and range-free localization methods. Range-based methods use distance or angle measurements between sensor nodes, including received signal strength indication (RSSI), time of arrival (TOA), time difference of arrival (TDOA), and angle of arrival (AOA). Range-free methods depend on node connectivity and do not require specialized hardware. The document reviews several algorithms and techniques for each category.
Accurate indoor positioning system based on modify nearest point techniqueIJECEIAES
This document presents an accurate indoor positioning system based on a modified nearest point technique. The system uses Wi-Fi signals to estimate distances and indoor locations. It builds a fingerprint database with reference points and signal measurements collected in different environments to account for changing conditions. The case study building is divided into 7 areas to allow dynamic parameter assignment. Locations are estimated by finding the nearest reference point within a specific environment by comparing at least four nearby points. The results showed errors of less than 0.102 meters for indoor localization.
Effective range free localization scheme for wireless sensor networkijmnct
Location aware sensors can be used in many areas such as military and civilian applications. Wireless
Sensor Networks help to identify the accurate location of the event. In this paper a cost effective schema for
localization has been proposed. It uses two beacon nodes to identify the location of unknown nodes. It
also uses flooding and estimating method to accurately identify the location of other nodes. Available area
is divided into zones and beacons are provided for each zone. Beacon nodes are placed in appropriate
locations normally two in a zone to provide location information. Using the two nodes location of unknown
nodes can be calculated accurately.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal,
Precise Attitude Determination Using a Hexagonal GPS PlatformCSCJournals
In this paper, a method of precise attitude determination using GPS is proposed. We use a hexagonal antenna platform of 1 m diameter (called the wheel) and post-processing algorithms to calculate attitude, where we focus on yaw to prove the concept. The first part of the algorithm determines an initial absolute position using single point positioning. The second part involves double differencing (DD) the carrier phase measurements for the received GPS signals to determine relative positioning of the antennas on the wheel. The third part consists of Direct Computation Method (DCM) or Implicit Least Squares (ILS) algorithms which, given sufficiently accurate knowledge of the fixed body frame coordinates of the wheel, takes in relative positions of all the receivers and produces the attitude. Field testing results presented in this paper will show that an accuracy of 0.05 degrees in yaw can be achieved. The results will be compared with a theoretical error, which is shown by Monte Carlo simulation to be < 0.001 degrees. The improvement to the current state-of-the-art is that current methods require either very large baselines of several meters to achieve such accuracy or provide errors in yaw that are orders of magnitude greater.
This document presents a localization technique for wireless sensor networks that combines genetic algorithms, Kalman filtering, and measurements of received signal strength indication (RSSI) and angle of arrival (AOA). The technique treats RSSI as a prior and AOA as a measurement in a Kalman filter to estimate sensor node positions. It defines objective functions based on RSSI, AOA, and their combination that are minimized using a genetic algorithm. Simulation results over different scenarios show the proposed technique achieves higher accuracy than using RSSI or AOA alone, with an average error of 1.01 meters using as few as three anchor nodes.
Enhanced Mobile Node Tracking With Received Signal Strength in Wireless Senso...IOSR Journals
Abstract : Node localization is important parameter in WSN. Node localization is required to report origin of
events which makes it one of the important challenges in WSN. Received signal strength (RSS) is used to
calculate distance between mobile node and reference node. The position of the mobile node is calculated using
multilateration algorithm (MA). Extended Kalman filter (EKF) is utilized to estimate the actual position. In this
paper, the implementation and enhancement of a tracking system based on RSS indicator with the aid of an
Extended Kalman Filter (EKF) is described and an adaptive filter is derived.
Keywords - Extended Kalman filter (EKF), mobile node tracking, multilateration algorithm (MA), received
signal strength (RSS), Wireless sensor networks (WSN)
Enhanced Mobile Node Tracking With Received Signal Strength in Wireless Senso...IOSR Journals
Node localization is important parameter in WSN. Node localization is required to report origin of
events which makes it one of the important challenges in WSN. Received signal strength (RSS) is used to
calculate distance between mobile node and reference node. The position of the mobile node is calculated using
multilateration algorithm (MA). Extended Kalman filter (EKF) is utilized to estimate the actual position. In this
paper, the implementation and enhancement of a tracking system based on RSS indicator with the aid of an
Extended Kalman Filter (EKF) is described and an adaptive filter is derived.
Minimization of Handoff Latency by Co-ordinate Evaluation Method Using GPS Ba...VLSICS Design
This document proposes a method to minimize handoff latency in mobile networks using GPS. It analyzes the existing handoff process and identifies scanning delay as the main contributor to latency. The proposed method uses GPS to track the coordinates and direction of movement of the mobile node. Based on this, it determines the neighboring access points the node is likely to connect to next, reducing the number of access points scanned during handoff. By scanning fewer access points, the overall scanning delay and handoff latency can be reduced by half to one third compared to existing methods.
MINIMIZATION OF HANDOFF LATENCY BY CO-ORDINATE EVALUATION METHOD USING GPS BA...VLSICS Design
Handoff has become an essential criterion in mobile communication system, specially in urban areas, owing to the limited coverage area of Access Points (AP). Handover of calls between two BS is encountered frequently and it is essentially required to minimize the delay of the process. Many solutions attempting to improve this process have been proposed but only a few use geo-location systems in the management of the handover. Here we propose to
minimize the handoff latency by minimizing the number of APs scanned by the mobile node (MN) during each handoff procedure. We consider the whole topographical area as a two dimensional plane. By GPS, we can note
down the co-ordinates of the MN at any instant. The average rate of change of its latitudinal distance and longitudinal distance with a specific time period is evaluated at the end of the given time period. With the knowledge of the given parameter, it is possible to determine the latitude and longitude of the MN after a particular instant of time. Hence the direction of motion of the MN can be determined which in turns gives the AP towards which the MN is heading towards. This reduces the number of APs to be scanned. Thus, on an overall basis, the handoff latency can be reduced by almost half to one third of its value.
Location Fingerprinting is a very familiar Wi-Fi positioning method, which determines a device by retrieving the information recorded containing the location fingerprint. These methods deploy the signal strength (RSS) to predict the coordinate. There are feedbacks for using the absolute RSS either the absolute RSS in a time interval may not be representable of the IEEE 802.11 signal, as the signal may fluctuate or a manual error prone calibration is needed across different mobile platform. The main target is to propose the use of Fourier descriptors in LF. We convert the IEEE 802.11b Wi-Fi signal into a Fourier domain. Then, the Fourier descriptors are used to predict the location by applying the K-Nearest Neighbor algorithm. The results show that the effectiveness of LF methods based on Fourier descriptors lead to substantially more accurate and robust localization.
The document discusses GPS receivers and positioning methods. It provides details on:
- How GPS receivers obtain data from at least 4 satellites to determine position through measuring pseudo-ranges or carrier phase.
- Modern receivers can track all visible satellites simultaneously through multiple channels.
- Basic positioning involves measuring distances to 3 satellites, but using 4 eliminates clock bias errors.
- Carrier phase measurements provide more accurate positioning needed for engineering surveys.
CHANNEL ESTIMATION AND MULTIUSER DETECTION IN ASYNCHRONOUS SATELLITE COMMUNIC...ijwmn
In this paper, we propose a new method of channel estimation for asynchronous additive white Gaussian noise channels in satellite communications. This method is based on signals correlation and multiuser interference cancellation which adopts a successive structure. Propagation delays and signals amplitudes are jointly estimated in order to be used for data detection at the receiver. As, a multiuser detector, a single stage successive interference cancellation (SIC) architecture is analyzed and integrated to the channel estimation technique and the whole system is evaluated. The satellite access method adopted is the direct sequence code division multiple access (DS CDMA) one. To evaluate the channel estimation and the detection technique, we have simulated a satellite uplink with an asynchronous multiuser access.
Modified Coverage Hole Detection Algorithm for Distributed WSNsidescitation
Wireless sensor networks (WSNs) are spatially
distributed sensors that find wide applications in various fields
such as environmental control, Medicine and Health care,
Military surveillance etc. The sensing and communication
within the network should be effective for such applications.
Holes are the voids created in the network when accidental
death of nodes is caused due to technical
or improper
coverage. The detection of the holes becomes essential after
the random deployment. The main objective of the work is to
detect the coverage holes using computational geometry
approach which uses co-ordinates of the sensors and to
implement it in the hardware. The communication range of a
node is considered to be equal to its sensing range. The protocol
is designed for irregular domain which is a real time scenario
and takes the help of two-hop neighbors’ of a node to detect
the hole around it. The proposed system also allows only few
nodes to initiate the detection algorithm so that the energy
and time is conserved.
LOCALIZATION ALGORITHM USING VARYING SPEED MOBILE SINK FOR WIRELESS SENSOR NE...ijasuc
Localization of sensor nodes is important in many aspects in wireless sensor networks. The known
location of sensor node helps in determining the event of interest. A mobile sink is introduced to track the
event driven sensor nodes in the path of the event, thus conserving energy and time. We present a novel
range based localization algorithm which helps the mobile sink to compute the location of the sensor
nodes efficiently. The data transfer from the mobile sink and the sensor nodes is used to estimate the
sensor location. The sensor nodes do not need to spend energy on neighbouring interaction for
localization. The localization mechanism has been implemented in TOSSIM. The simulation results show
that our scheme performed better than other range-based schemes.
Spectrum Sensing Detection with Sequential Forward Search in Comparison to Kn...IJMTST Journal
FCC is currently working on the concept of white space users “borrowing” spectrum from free license
holders temporarily to improve the spectrum utilization.
This project provides a relation between a Pf and the SNR value of any spectrum detector to have a
certain performance. Previous spectrum sensing detection techniques are only suitable for Low SNR and
are based on signal information values. But these methods are purely narrow band spectrum applications
In order to overcome the above said drawbacks we propose a novel method of spectrum sensing method
and is suitable for low and high SNR values, the sensed spectrum applicable for wide band applications.
Our proposed method does not require signal information at the receiver and channel information, because
this flexibility sensing rate is very high compared to previous techniques.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Horizontal and Vertical Zone Based Location Techniques for Wireless Sensor Ne...ijwmn
Localization is an important feature in Wireless sensor networks (WSNs). Accuracy in node localization with proper synchronization and required localization of sensor nodes, save node energy and enhance the performance of communication network protocols. In this paper we propose distributed localization algorithms and assume position known Cluster Head (CH) and position unknown three beacon nodes for each cluster. Using trilateration technique beacon nodes are located. Additional beacon node is added to confirm the location of beacon nodes and maintain location accuracy. These position localized beacon nodes help to locate other sensor nodes. The proposed two distributed zone based localization algorithms are (i) Horizontal Location Position System (H-LPS), where cluster is divided into Horizontal Zones (HZs) and beacon nodes locate in horizontal direction and (ii) Vertical Location Position System (V-LPS), where cluster is divided into Vertical Zones (VZs) and beacon nodes locate in vertical direction. The main advantage of zone based localization is nodes belonging to a bounded zone (horizontal or vertical) are localized and participate in WSN computing. If a bounded zone is eliminated during localization, then nodes do not participate in localization and thus save WSN computing. We provide zone based simulations for H-LPS and V-LPS in comparison with existing localization algorithms like Ad hoc Positioning System (APS), Recursive Positioning Estimation (RPE) and Directed Positioning Estimation (DPE). Performance evaluation of H-LPS and V-LPS illustrate that for zone based localization, H-LPS and V-LPS perform better that existing localization techniques. Bounded zone performance is optimal for H-LPS and V-LPS compared to existing localization techniques in WSN.
HORIZONTAL AND VERTICAL ZONE BASED LOCATION TECHNIQUES FOR WIRELESS SENSOR NE...ijwmn
Localization is an important feature in Wireless sensor networks (WSNs). Accuracy in node localization with proper synchronization and required localization of sensor nodes, save node energy and enhance the performance of communication network protocols. In this paper we propose distributed localization algorithms and assume position known Cluster Head (CH) and position unknown three beacon nodes for each cluster. Using trilateration technique beacon nodes are located. Additional beacon node is added to confirm the location of beacon nodes and maintain location accuracy. These position localized beacon nodes help to locate other sensor nodes. The proposed two distributed zone based localization algorithms
are (i) Horizontal Location Position System (H-LPS), where cluster is divided into Horizontal Zones (HZs) and beacon nodes locate in horizontal direction and (ii) Vertical Location Position System (V-LPS), where cluster is divided into Vertical Zones (VZs) and beacon nodes locate in vertical direction. The main advantage of zone based localization is nodes belonging to a bounded zone (horizontal or vertical) are localized and participate in WSN computing. If a bounded zone is eliminated during localization, then nodes do not participate in localization and thus save WSN computing. We provide zone based simulations for H-LPS and V-LPS in comparison with existing localization algorithms like Ad hoc Positioning System (APS), Recursive Positioning Estimation (RPE) and Directed Positioning Estimation (DPE). Performance evaluation of H-LPS and V-LPS illustrate that for zone based localization, H-LPS
and V-LPS perform better that existing localization techniques. Bounded z
Automatic target detection and localization using ultra-wideband radarIJECEIAES
The pulse ultra-wide band (UWB) radar consists of switching of energy of very short duration in an ultra-broadband emission chain, and the UWB signal emitted is an ultrashort pulse, of the order of nanoseconds, without a carrier. These systems can indicate the presence and distances of a distant object, call a target, and determine its size, shape, speed, and trajectory. In this paper, we present a UWB radar system allowing the detection of the presence of a target and its localization in a road environment based on the principle of correlation of the reflected signal with the reference and the determination of its correlation peak.
Home security is of paramount importance in today's world, where we rely more on technology, home
security is crucial. Using technology to make homes safer and easier to control from anywhere is
important. Home security is important for the occupant’s safety. In this paper, we came up with a low cost,
AI based model home security system. The system has a user-friendly interface, allowing users to start
model training and face detection with simple keyboard commands. Our goal is to introduce an innovative
home security system using facial recognition technology. Unlike traditional systems, this system trains
and saves images of friends and family members. The system scans this folder to recognize familiar faces
and provides real-time monitoring. If an unfamiliar face is detected, it promptly sends an email alert,
ensuring a proactive response to potential security threats.
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
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Similar to Environmentally Corrected RSSI Based Real Time Location Detection System
This document summarizes positioning techniques for wireless sensor networks (WSNs) and Internet of Things (IoT) systems. It discusses both range-based and range-free localization methods. Range-based methods use distance or angle measurements between sensor nodes, including received signal strength indication (RSSI), time of arrival (TOA), time difference of arrival (TDOA), and angle of arrival (AOA). Range-free methods depend on node connectivity and do not require specialized hardware. The document reviews several algorithms and techniques for each category.
Accurate indoor positioning system based on modify nearest point techniqueIJECEIAES
This document presents an accurate indoor positioning system based on a modified nearest point technique. The system uses Wi-Fi signals to estimate distances and indoor locations. It builds a fingerprint database with reference points and signal measurements collected in different environments to account for changing conditions. The case study building is divided into 7 areas to allow dynamic parameter assignment. Locations are estimated by finding the nearest reference point within a specific environment by comparing at least four nearby points. The results showed errors of less than 0.102 meters for indoor localization.
Effective range free localization scheme for wireless sensor networkijmnct
Location aware sensors can be used in many areas such as military and civilian applications. Wireless
Sensor Networks help to identify the accurate location of the event. In this paper a cost effective schema for
localization has been proposed. It uses two beacon nodes to identify the location of unknown nodes. It
also uses flooding and estimating method to accurately identify the location of other nodes. Available area
is divided into zones and beacons are provided for each zone. Beacon nodes are placed in appropriate
locations normally two in a zone to provide location information. Using the two nodes location of unknown
nodes can be calculated accurately.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal,
Precise Attitude Determination Using a Hexagonal GPS PlatformCSCJournals
In this paper, a method of precise attitude determination using GPS is proposed. We use a hexagonal antenna platform of 1 m diameter (called the wheel) and post-processing algorithms to calculate attitude, where we focus on yaw to prove the concept. The first part of the algorithm determines an initial absolute position using single point positioning. The second part involves double differencing (DD) the carrier phase measurements for the received GPS signals to determine relative positioning of the antennas on the wheel. The third part consists of Direct Computation Method (DCM) or Implicit Least Squares (ILS) algorithms which, given sufficiently accurate knowledge of the fixed body frame coordinates of the wheel, takes in relative positions of all the receivers and produces the attitude. Field testing results presented in this paper will show that an accuracy of 0.05 degrees in yaw can be achieved. The results will be compared with a theoretical error, which is shown by Monte Carlo simulation to be < 0.001 degrees. The improvement to the current state-of-the-art is that current methods require either very large baselines of several meters to achieve such accuracy or provide errors in yaw that are orders of magnitude greater.
This document presents a localization technique for wireless sensor networks that combines genetic algorithms, Kalman filtering, and measurements of received signal strength indication (RSSI) and angle of arrival (AOA). The technique treats RSSI as a prior and AOA as a measurement in a Kalman filter to estimate sensor node positions. It defines objective functions based on RSSI, AOA, and their combination that are minimized using a genetic algorithm. Simulation results over different scenarios show the proposed technique achieves higher accuracy than using RSSI or AOA alone, with an average error of 1.01 meters using as few as three anchor nodes.
Enhanced Mobile Node Tracking With Received Signal Strength in Wireless Senso...IOSR Journals
Abstract : Node localization is important parameter in WSN. Node localization is required to report origin of
events which makes it one of the important challenges in WSN. Received signal strength (RSS) is used to
calculate distance between mobile node and reference node. The position of the mobile node is calculated using
multilateration algorithm (MA). Extended Kalman filter (EKF) is utilized to estimate the actual position. In this
paper, the implementation and enhancement of a tracking system based on RSS indicator with the aid of an
Extended Kalman Filter (EKF) is described and an adaptive filter is derived.
Keywords - Extended Kalman filter (EKF), mobile node tracking, multilateration algorithm (MA), received
signal strength (RSS), Wireless sensor networks (WSN)
Enhanced Mobile Node Tracking With Received Signal Strength in Wireless Senso...IOSR Journals
Node localization is important parameter in WSN. Node localization is required to report origin of
events which makes it one of the important challenges in WSN. Received signal strength (RSS) is used to
calculate distance between mobile node and reference node. The position of the mobile node is calculated using
multilateration algorithm (MA). Extended Kalman filter (EKF) is utilized to estimate the actual position. In this
paper, the implementation and enhancement of a tracking system based on RSS indicator with the aid of an
Extended Kalman Filter (EKF) is described and an adaptive filter is derived.
Minimization of Handoff Latency by Co-ordinate Evaluation Method Using GPS Ba...VLSICS Design
This document proposes a method to minimize handoff latency in mobile networks using GPS. It analyzes the existing handoff process and identifies scanning delay as the main contributor to latency. The proposed method uses GPS to track the coordinates and direction of movement of the mobile node. Based on this, it determines the neighboring access points the node is likely to connect to next, reducing the number of access points scanned during handoff. By scanning fewer access points, the overall scanning delay and handoff latency can be reduced by half to one third compared to existing methods.
MINIMIZATION OF HANDOFF LATENCY BY CO-ORDINATE EVALUATION METHOD USING GPS BA...VLSICS Design
Handoff has become an essential criterion in mobile communication system, specially in urban areas, owing to the limited coverage area of Access Points (AP). Handover of calls between two BS is encountered frequently and it is essentially required to minimize the delay of the process. Many solutions attempting to improve this process have been proposed but only a few use geo-location systems in the management of the handover. Here we propose to
minimize the handoff latency by minimizing the number of APs scanned by the mobile node (MN) during each handoff procedure. We consider the whole topographical area as a two dimensional plane. By GPS, we can note
down the co-ordinates of the MN at any instant. The average rate of change of its latitudinal distance and longitudinal distance with a specific time period is evaluated at the end of the given time period. With the knowledge of the given parameter, it is possible to determine the latitude and longitude of the MN after a particular instant of time. Hence the direction of motion of the MN can be determined which in turns gives the AP towards which the MN is heading towards. This reduces the number of APs to be scanned. Thus, on an overall basis, the handoff latency can be reduced by almost half to one third of its value.
Location Fingerprinting is a very familiar Wi-Fi positioning method, which determines a device by retrieving the information recorded containing the location fingerprint. These methods deploy the signal strength (RSS) to predict the coordinate. There are feedbacks for using the absolute RSS either the absolute RSS in a time interval may not be representable of the IEEE 802.11 signal, as the signal may fluctuate or a manual error prone calibration is needed across different mobile platform. The main target is to propose the use of Fourier descriptors in LF. We convert the IEEE 802.11b Wi-Fi signal into a Fourier domain. Then, the Fourier descriptors are used to predict the location by applying the K-Nearest Neighbor algorithm. The results show that the effectiveness of LF methods based on Fourier descriptors lead to substantially more accurate and robust localization.
The document discusses GPS receivers and positioning methods. It provides details on:
- How GPS receivers obtain data from at least 4 satellites to determine position through measuring pseudo-ranges or carrier phase.
- Modern receivers can track all visible satellites simultaneously through multiple channels.
- Basic positioning involves measuring distances to 3 satellites, but using 4 eliminates clock bias errors.
- Carrier phase measurements provide more accurate positioning needed for engineering surveys.
CHANNEL ESTIMATION AND MULTIUSER DETECTION IN ASYNCHRONOUS SATELLITE COMMUNIC...ijwmn
In this paper, we propose a new method of channel estimation for asynchronous additive white Gaussian noise channels in satellite communications. This method is based on signals correlation and multiuser interference cancellation which adopts a successive structure. Propagation delays and signals amplitudes are jointly estimated in order to be used for data detection at the receiver. As, a multiuser detector, a single stage successive interference cancellation (SIC) architecture is analyzed and integrated to the channel estimation technique and the whole system is evaluated. The satellite access method adopted is the direct sequence code division multiple access (DS CDMA) one. To evaluate the channel estimation and the detection technique, we have simulated a satellite uplink with an asynchronous multiuser access.
Modified Coverage Hole Detection Algorithm for Distributed WSNsidescitation
Wireless sensor networks (WSNs) are spatially
distributed sensors that find wide applications in various fields
such as environmental control, Medicine and Health care,
Military surveillance etc. The sensing and communication
within the network should be effective for such applications.
Holes are the voids created in the network when accidental
death of nodes is caused due to technical
or improper
coverage. The detection of the holes becomes essential after
the random deployment. The main objective of the work is to
detect the coverage holes using computational geometry
approach which uses co-ordinates of the sensors and to
implement it in the hardware. The communication range of a
node is considered to be equal to its sensing range. The protocol
is designed for irregular domain which is a real time scenario
and takes the help of two-hop neighbors’ of a node to detect
the hole around it. The proposed system also allows only few
nodes to initiate the detection algorithm so that the energy
and time is conserved.
LOCALIZATION ALGORITHM USING VARYING SPEED MOBILE SINK FOR WIRELESS SENSOR NE...ijasuc
Localization of sensor nodes is important in many aspects in wireless sensor networks. The known
location of sensor node helps in determining the event of interest. A mobile sink is introduced to track the
event driven sensor nodes in the path of the event, thus conserving energy and time. We present a novel
range based localization algorithm which helps the mobile sink to compute the location of the sensor
nodes efficiently. The data transfer from the mobile sink and the sensor nodes is used to estimate the
sensor location. The sensor nodes do not need to spend energy on neighbouring interaction for
localization. The localization mechanism has been implemented in TOSSIM. The simulation results show
that our scheme performed better than other range-based schemes.
Spectrum Sensing Detection with Sequential Forward Search in Comparison to Kn...IJMTST Journal
FCC is currently working on the concept of white space users “borrowing” spectrum from free license
holders temporarily to improve the spectrum utilization.
This project provides a relation between a Pf and the SNR value of any spectrum detector to have a
certain performance. Previous spectrum sensing detection techniques are only suitable for Low SNR and
are based on signal information values. But these methods are purely narrow band spectrum applications
In order to overcome the above said drawbacks we propose a novel method of spectrum sensing method
and is suitable for low and high SNR values, the sensed spectrum applicable for wide band applications.
Our proposed method does not require signal information at the receiver and channel information, because
this flexibility sensing rate is very high compared to previous techniques.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Horizontal and Vertical Zone Based Location Techniques for Wireless Sensor Ne...ijwmn
Localization is an important feature in Wireless sensor networks (WSNs). Accuracy in node localization with proper synchronization and required localization of sensor nodes, save node energy and enhance the performance of communication network protocols. In this paper we propose distributed localization algorithms and assume position known Cluster Head (CH) and position unknown three beacon nodes for each cluster. Using trilateration technique beacon nodes are located. Additional beacon node is added to confirm the location of beacon nodes and maintain location accuracy. These position localized beacon nodes help to locate other sensor nodes. The proposed two distributed zone based localization algorithms are (i) Horizontal Location Position System (H-LPS), where cluster is divided into Horizontal Zones (HZs) and beacon nodes locate in horizontal direction and (ii) Vertical Location Position System (V-LPS), where cluster is divided into Vertical Zones (VZs) and beacon nodes locate in vertical direction. The main advantage of zone based localization is nodes belonging to a bounded zone (horizontal or vertical) are localized and participate in WSN computing. If a bounded zone is eliminated during localization, then nodes do not participate in localization and thus save WSN computing. We provide zone based simulations for H-LPS and V-LPS in comparison with existing localization algorithms like Ad hoc Positioning System (APS), Recursive Positioning Estimation (RPE) and Directed Positioning Estimation (DPE). Performance evaluation of H-LPS and V-LPS illustrate that for zone based localization, H-LPS and V-LPS perform better that existing localization techniques. Bounded zone performance is optimal for H-LPS and V-LPS compared to existing localization techniques in WSN.
HORIZONTAL AND VERTICAL ZONE BASED LOCATION TECHNIQUES FOR WIRELESS SENSOR NE...ijwmn
Localization is an important feature in Wireless sensor networks (WSNs). Accuracy in node localization with proper synchronization and required localization of sensor nodes, save node energy and enhance the performance of communication network protocols. In this paper we propose distributed localization algorithms and assume position known Cluster Head (CH) and position unknown three beacon nodes for each cluster. Using trilateration technique beacon nodes are located. Additional beacon node is added to confirm the location of beacon nodes and maintain location accuracy. These position localized beacon nodes help to locate other sensor nodes. The proposed two distributed zone based localization algorithms
are (i) Horizontal Location Position System (H-LPS), where cluster is divided into Horizontal Zones (HZs) and beacon nodes locate in horizontal direction and (ii) Vertical Location Position System (V-LPS), where cluster is divided into Vertical Zones (VZs) and beacon nodes locate in vertical direction. The main advantage of zone based localization is nodes belonging to a bounded zone (horizontal or vertical) are localized and participate in WSN computing. If a bounded zone is eliminated during localization, then nodes do not participate in localization and thus save WSN computing. We provide zone based simulations for H-LPS and V-LPS in comparison with existing localization algorithms like Ad hoc Positioning System (APS), Recursive Positioning Estimation (RPE) and Directed Positioning Estimation (DPE). Performance evaluation of H-LPS and V-LPS illustrate that for zone based localization, H-LPS
and V-LPS perform better that existing localization techniques. Bounded z
Automatic target detection and localization using ultra-wideband radarIJECEIAES
The pulse ultra-wide band (UWB) radar consists of switching of energy of very short duration in an ultra-broadband emission chain, and the UWB signal emitted is an ultrashort pulse, of the order of nanoseconds, without a carrier. These systems can indicate the presence and distances of a distant object, call a target, and determine its size, shape, speed, and trajectory. In this paper, we present a UWB radar system allowing the detection of the presence of a target and its localization in a road environment based on the principle of correlation of the reflected signal with the reference and the determination of its correlation peak.
Similar to Environmentally Corrected RSSI Based Real Time Location Detection System (20)
Home security is of paramount importance in today's world, where we rely more on technology, home
security is crucial. Using technology to make homes safer and easier to control from anywhere is
important. Home security is important for the occupant’s safety. In this paper, we came up with a low cost,
AI based model home security system. The system has a user-friendly interface, allowing users to start
model training and face detection with simple keyboard commands. Our goal is to introduce an innovative
home security system using facial recognition technology. Unlike traditional systems, this system trains
and saves images of friends and family members. The system scans this folder to recognize familiar faces
and provides real-time monitoring. If an unfamiliar face is detected, it promptly sends an email alert,
ensuring a proactive response to potential security threats.
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
Cloud Computing, being one of the most recent innovative developments of the IT world, has been
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in
recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized
application of MIMO technology within WSNs. This approach operates effectively, especially in
challenging and resource-constrained environments. By facilitating collaboration among sensor nodes,
Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments.
Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring,
industrial automation, and healthcare applications.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication. IJCSIT publishes original research papers and review papers, as well as auxiliary material such as: research papers, case studies, technical reports etc.
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
Welcome to AIRCC's International Journal of Computer Science and Information Technology (IJCSIT), your gateway to the latest advancements in the dynamic fields of Computer Science and Information Systems.
Computer-Assisted Language Learning (CALL) are computer-based tutoring systems that deal with
linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language
Processing (NLP) tools to diagnose student errors, especially in language grammar. However, most such
systems do not consider the modeling of student competence in linguistic skills, especially for the Arabic
language. In this paper, we will deal with basic grammar concepts of the Arabic language taught for the
fourth grade of the elementary school in Egypt. This is through Arabic Grammar Trainer (AGTrainer)
which is an Intelligent CALL. The implemented system (AGTrainer) trains the students through different
questions that deal with the different concepts and have different difficulty levels. Constraint-based student
modeling (CBSM) technique is used as a short-term student model. CBSM is used to define in small grain
level the different grammar skills through the defined skill structures. The main contribution of this paper
is the hierarchal representation of the system's basic grammar skills as domain knowledge. That
representation is used as a mechanism for efficiently checking constraints to model the student knowledge
and diagnose the student errors and identify their cause. In addition, satisfying constraints and the number
of trails the student takes for answering each question and fuzzy logic decision system are used to
determine the student learning level for each lesson as a long-term model. The results of the evaluation
showed the system's effectiveness in learning in addition to the satisfaction of students and teachers with its
features and abilities.
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This research aims to further understanding in the field of continuous authentication using behavioural
biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing
Minecraft with a Samsung Tablet, each for a duration of 15 minutes. Utilizing this dataset, we employed
machine learning (ML) binary classifiers, being Random Forest (RF), K-Nearest Neighbors (KNN), and
Support Vector Classifier (SVC), to determine the authenticity of specific user actions. Our most robust
model was SVC, which achieved an average accuracy of approximately 90%, demonstrating that touch
dynamics can effectively distinguish users. However, further studies are needed to make it viable option
for authentication systems. You can access our dataset at the following
link:https://github.com/AuthenTech2023/authentech-repo
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the
context of text understanding. We begin by describing the architecture and training process of GPT-3, and
provide an overview of its impressive performance across a wide range of natural language processing
tasks, such as language translation, question-answering, and text completion. Throughout this research
project, a summarizing tool was also created to help us retrieve content from any types of document,
specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the
summarizing, as well as question-answering capabilities of GPT-3 (0) via long text
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification.
This work highlights transfer learning’s effectiveness in image classification using CNNs and VGG 16 that
provides insights into the selection of pre-trained models and hyper parameters for optimal performance.
We have proposed a comprehensive approach for image segmentation and classification, incorporating preprocessing techniques, the K-means algorithm for segmentation, and employing deep learning models such
as CNN and VGG 16 for classification.
- The document presents 6 different models for defining foot size in Tunisia: 2 statistical models, 2 neural network models using unsupervised learning, and 2 models combining neural networks and fuzzy logic.
- The statistical models (SM and SHM) are based on applying statistical equations to morphological foot data.
- The neural network models (MSK and MHSK) use self-organizing Kohonen maps to cluster foot data and model full and half sizes.
- The fuzzy neural network models (MSFK and MHSFK) incorporate fuzzy logic into the neural network learning process to better account for uncertainty in foot sizes.
The security of Electric Vehicle (EV) charging has gained momentum after the increase in the EV adoption
in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a
cloud-based platform to host their services and data. Like many complex systems, cloud systems are
susceptible to cyberattacks if proper measures are not taken by the organization to secure them. In this
paper, we explore the security of key components in the EV charging infrastructure, including the mobile
application and its cloud service. We conducted an experiment that initiated a Man in the Middle attack
between an EV app and its cloud services. Our results showed that it is possible to launch attacks against
the connected infrastructure by taking advantage of vulnerabilities that may have substantial economic and
operational ramifications on the EV charging ecosystem. We conclude by providing mitigation suggestions
and future research directions.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This study Examines the Effectiveness of Talent Procurement through the Imple...DharmaBanothu
In the world with high technology and fast
forward mindset recruiters are walking/showing interest
towards E-Recruitment. Present most of the HRs of
many companies are choosing E-Recruitment as the best
choice for recruitment. E-Recruitment is being done
through many online platforms like Linkedin, Naukri,
Instagram , Facebook etc. Now with high technology E-
Recruitment has gone through next level by using
Artificial Intelligence too.
Key Words : Talent Management, Talent Acquisition , E-
Recruitment , Artificial Intelligence Introduction
Effectiveness of Talent Acquisition through E-
Recruitment in this topic we will discuss about 4important
and interlinked topics which are
Impartiality as per ISO /IEC 17025:2017 StandardMuhammadJazib15
This document provides basic guidelines for imparitallity requirement of ISO 17025. It defines in detial how it is met and wiudhwdih jdhsjdhwudjwkdbjwkdddddddddddkkkkkkkkkkkkkkkkkkkkkkkwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwioiiiiiiiiiiiii uwwwwwwwwwwwwwwwwhe wiqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq gbbbbbbbbbbbbb owdjjjjjjjjjjjjjjjjjjjj widhi owqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq uwdhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhwqiiiiiiiiiiiiiiiiiiiiiiiiiiiiw0pooooojjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj whhhhhhhhhhh wheeeeeeee wihieiiiiii wihe
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Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Determination of Equivalent Circuit parameters and performance characteristic...pvpriya2
Includes the testing of induction motor to draw the circle diagram of induction motor with step wise procedure and calculation for the same. Also explains the working and application of Induction generator
Levelised Cost of Hydrogen (LCOH) Calculator ManualMassimo Talia
The aim of this manual is to explain the
methodology behind the Levelized Cost of
Hydrogen (LCOH) calculator. Moreover, this
manual also demonstrates how the calculator
can be used for estimating the expenses associated with hydrogen production in Europe
using low-temperature electrolysis considering different sources of electricity
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
AI in customer support Use cases solutions development and implementation.pdfmahaffeycheryld
AI in customer support will integrate with emerging technologies such as augmented reality (AR) and virtual reality (VR) to enhance service delivery. AR-enabled smart glasses or VR environments will provide immersive support experiences, allowing customers to visualize solutions, receive step-by-step guidance, and interact with virtual support agents in real-time. These technologies will bridge the gap between physical and digital experiences, offering innovative ways to resolve issues, demonstrate products, and deliver personalized training and support.
https://www.leewayhertz.com/ai-in-customer-support/#How-does-AI-work-in-customer-support
We have designed & manufacture the Lubi Valves LBF series type of Butterfly Valves for General Utility Water applications as well as for HVAC applications.
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...DharmaBanothu
The Network on Chip (NoC) has emerged as an effective
solution for intercommunication infrastructure within System on
Chip (SoC) designs, overcoming the limitations of traditional
methods that face significant bottlenecks. However, the complexity
of NoC design presents numerous challenges related to
performance metrics such as scalability, latency, power
consumption, and signal integrity. This project addresses the
issues within the router's memory unit and proposes an enhanced
memory structure. To achieve efficient data transfer, FIFO buffers
are implemented in distributed RAM and virtual channels for
FPGA-based NoC. The project introduces advanced FIFO-based
memory units within the NoC router, assessing their performance
in a Bi-directional NoC (Bi-NoC) configuration. The primary
objective is to reduce the router's workload while enhancing the
FIFO internal structure. To further improve data transfer speed,
a Bi-NoC with a self-configurable intercommunication channel is
suggested. Simulation and synthesis results demonstrate
guaranteed throughput, predictable latency, and equitable
network access, showing significant improvement over previous
designs
Environmentally Corrected RSSI Based Real Time Location Detection System
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
DOI:10.5121/ijcsit.2016.8604 39
ENVIRONMENTALLY CORRECTED RSSI BASED
REAL TIME LOCATION DETECTION SYSTEM
Hakan Koyuncu and Baki Koyuncu
Final International University, Cyprus
ABSTRACT
RSSI based localization techniques are effected by environmental factors which cause the RF
signalsemitted from transmitter nodes fluctuate in time domain. These variations generate fluctuations on
distance calculations and result false object position detection during localization.Smoothing procedures
must be applied on distance values either collectively or individually to minimize these fluctuations. In this
study,proposed detection system has two main phases. Firstly, calibration of RSSI values with respect to
distances and calculation of environmental coefficient for each transmitter.Secondly, position estimation of
objects by applyingiterative trilateration on smoothed distance values. A smoothing algorithm is employed
to minimize the dynamic fluctuations of RF signals received from each reference transmitter node.
Distances between the reference nodes and the objects are calculated by deploying environmental
coefficients. Experimental measurements are carried out to measure the sensitivity of the system. Results
show that the proposed system can be deployed as a viable position detection system in indoors and
outdoors.
KEYWORDS
RSSI (received signal strength indication), environmental factor, dynamic fluctuation, iterative
trilateration, smoothing algorithm, localization technique.
I. INTRODUCTION
There are many localization techniques which focus on indoors or outdoors by using different
sensor devices such as RF-code andJennic [1, 2]. Some examples in the literature to determine the
object positions are Cricket [3], Radar [4] and GPS [5]. However, due to different environmental
characteristics, sensor devices are affected differently and the localization results will reflect
these effects. Hence the accurate calculation of object locations becomes a difficult task.
Sensor devices are called wireless sensor nodes and thesenodes can be transmitters or receivers.
Receiver nodes receive the transmitted RSSI values from transmitter nodes and transfer them to a
server. Localization procedures use existing WLAN infrastructures to communicate with the
server [6,7]. During the RF signal propagation from transmitters, signal amplitudes greatly vary
due to environmental conditions when they arrive to receivers. Some signals are weak and their
contributions with the distance calculations are minimal. Other signals have good signal strength
levels and contribute well in calculations
Hence RSSI values must be carefully considered and the effects of their fluctuations on distance
calculations in time domain must be minimized in order to integrate them in position calculations.
Many localization systems deal with the smoothing of RSSI values. Some other systems deal with
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
40
the smoothing of localization distances before determining the object location. Filtering
techniques such as Kalman filtering [8], Bandpass filtering [9] and etc, are utilized to reduce the
random variations of calculated distance values. Sudden changes in RSSI signal levels are also
eliminated by using outlier techniques [10].
In literature,many smoothing algorithms are employed in localization procedures.[11],[12] An
environmental factor is usually integrated collectively during smoothing as the average of
environmental effects for all the transmitters. In this case, localization errors are reduced but not
completely minimized due to the fact that environmental effects arequantized locally for each
transmitter. Hence, an environmental factor for each transmittermust be introduced during
calculations.
In the proposed approach, RSSI values arriving sequentially from each transmitter are considered
and an environmental factor for each transmitter is introduced as an environmental coefficient.
Each transmitter and receiver pair is calibrated with respect to distances between them and the
environmental coefficientis calculated for thattransmitter acrossthe test area. To estimate the
object location, there must be minimum 3 transmitters sending RSSI values to object receiver. An
initial estimated object location is deployed and the distances between this location and
transmitters are used together with environmentally corrected distances between transmitters and
objects. Iterative technique is carried out with Taylor expansion series of the above distance
differences by reducing the differencewhich is termed as error distanceat every iteration. Error
distance reduction eventually approaches to actual object coordinates.
Hence, a new localization technique is proposed in this study where an environmental coefficient
is calculated for each transmitter node and object position is determined by using iterative error
distance calculations. After a brief introduction in section 1, determination of environmental
coefficients and the theory of iterative error distance calculations are given in section 2. In section
3, implementation of the study is presented. Results and general discussions are given in section 4
together with conclusions in section 5.
II. SYSTEM THEORY
The system consists of a set of static reference transmitter WSNs at known coordinates and a
mobile object receiver WSN.Transmitter nodesat certain distances to object node broadcast RSSI
values to onboard object receiver. Received RSSIi data and is sent from the object receiver to a
base station through a wireless connection. Similarly, reference transmitter node position
information (xi, yi) is also sent to base station via a wireless LAN. Flow chart of the proposed
system is shown in Fig. 1.
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
41
Figure 1: Flow chart of the system.
a) RSSI CALIBRATION
This phase is identified as the calibration phase of the localization. RSSI values are received from
individual reference transmitters and gathered in a data base with respect to transmitter
coordinates in base station PC. RF signals travel through the environment and they exhibit path
loss in different transmission media and directions. In order to quantize these irregular path
losses, many RSSI measurements are carried out across the test area at various object distances
from transmitters. These RSSI values are plotted against distances and calibration curves are
obtained which are expressed empirically by the following equation (1).
n
Cx
RSSI −
= 10
log
10 (1)
where ‘n’ is taken as the environmental coefficient,( C
10
log
10 ) is the RSSI constant value at 1 m
across the test area and ‘x’ is termed as the distance between transmitter and receiver during the
calibration phase only. RF signal propagation across the test area is affected by different medium
surrounding the reference nodes. If identical environmental coefficients are considered for all the
reference nodes this situation introduces errors in distance calculations. Hence, different
environmental coefficients are determined for different reference node transmissions and
‘ni’environmental coefficient canbe definedin equation (2) as
i
i
i
x
C
RSSI
n
10
10
log
10
log
10
−
−
= (2)
where (i =1,2,3...N) and N is the number of RSSI measurements from one transmitter.
During the calibration of RSSIi values against a range of ‘xi’ distances, ‘n’ is calculated for each
RSSI and a known ‘x’ value. A set of ni values are generated and averaged out to give the
environmental coefficient navgfor one transmitter as shown in equation (3).
∑
=
=
N
i
i
avg n
N
n
1
1
(3)
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
42
Hence environmentally corrected or smoothed xj distances between a transmitter and the
objectlocation can be expressed in equation (4) as:
avg
j
n
RSSI
A
j
x
10
10
−
= (4)
j = (1,2,3,4….M) where M is the total number of RSSI measurements at object distance ‘xj’ with
average environmental coefficient navgand A constant of 10log10C.
Secondly, a well-known real time smoothing algorithm called KalmanFiltering is applied on
previous xjvalues to further smooth them for higher position accuracies. In conclusion, 2 levels of
smoothing are applied on x distance calculations, one with average environmental coefficient and
another with Kalman filtering.Hence, a sufficient reduction of distance variations due to RSSI
fluctuations is realized during localization.
b) GENERAL SYSTEM
The above smoothing mechanisms aredeployed on the object distances with transmitters to reduce
the effects of RSSIfluctuationsin time. In this section, smoothed x distances are termed as d
distances between transmitters and object receiver. N number of ‘T’ transmitters and the object
receiver are employed during measurements.There are ‘j’ numbers of ‘d’ distances calculated
from j number of RSSI measurements for each transmitter. This can be displayed for N
transmitter with the following set.
⊃
j
N
N
N
N
j
j
N d
d
d
d
d
d
d
d
d
d
d
d
T
T
T
,.....
,
,
,.....,
,
,
,......,
,
,
111
11
1
2
111
2
11
2
1
2
1
111
1
11
1
1
1
2
1
M
M
Hence there are j number object location calculations with N transmitters and each calculation
stage is defined as iteration. Each iteration contains N number of d values shown as { j
d1
j
d2 , j
d3
,…, j
N
d } corresponding to N transmitters.
c) LOCATION DETERMINATION
In order to estimate the object location, (x,y), there is a need for transmitter nodes with
coordinates (xi,yi) and their respective distances di, to object receiver.An iterative technique is
employed to calculate (x,y) location with respect to ‘di’ distances. Algorithm requires the
coordinates of minimum three transmitters and their ‘di’ distances with the object. Initially, a
finite estimated position, (xf,yf), is required to start the operation. Difference between the
distance ‘di’ and the estimated distance between (xi,yi) and (xf,yf) is calculated. Initially, (xf,yf) is
substituted for (x,y) and the difference is given by;
{ }
2
2
)
(
)
( f
i
f
i
i
i y
y
x
x
d
f −
+
−
−
= (5)
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
43
Correction parameters, (∆x, ∆y), are introduced to (xf, yf) in each iteration. These parameters are
added to (xf,yf) to approach object coordinates after a number of iterations.
d) CORRECTION PARAMETERS (∆X, ∆Y)
In calculus, a Taylor series represents a function as an infinite sum of terms which are calculated
by a function’s derivatives at a single point. For example,Taylor’s expansion of a function f(x) at
point c(x,y) can be expressed as:
.......
)
(
!
2
)
(
'
'
)
(
!
1
)
(
)
(
)
( 2
'
+
−
+
−
+
= c
x
c
f
c
x
c
f
c
f
x
f (6)
1st
degree Taylor series is defined by the first 2 terms of f(x) and it can be written for (xf,yf) as
)
)(
(
'
)
(
)
( f
f
f x
x
x
f
x
f
x
f −
+
= (7)
)
)(
(
'
)
(
)
( f
f
f y
y
y
f
y
f
y
f −
+
= (8)
Correction parameters (∆x, ∆y) can be calculated by using the 1st
order Taylor expansion of i
f in
equation (5). )
,
(
'
f
f y
x
f derivativeis given as )
,
(
f
i
f
i
y
f
x
f
D
∂
∂
∂
∂
= and it is expressed as shown
here.
−
+
−
−
−
+
−
−
=
2
2
2
2
)
(
)
(
,
)
(
)
( f
i
f
i
f
i
f
i
f
i
f
i
y
y
x
x
y
y
y
y
x
x
x
x
D (9)
Equations(7), (8) and (9) can be displayed in symbolic form as
∆
=
= *
)
,
( D
y
x
f
f (10)
where ∆= (∆x,∆y) and it is given in matrix form as ∆ =
∆
∆
y
x
By using 2D matrix calculations ∆ can be calculated as follows.
Multiplying both sides by D-1
, equation (10) becomes;
∆
=
−
f
D *
1
(11)
Both sides of the equation (11) is multiplied with (D-T
* DT
) where DT
is thetranspose matrix as
shownby
∆
= −
−
−
*
)
*
(
*
*
)
*
( 1 T
T
T
T
D
D
f
D
D
D
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, Dec
Left side of the above equation can be expressed as
(
∆x and ∆y values are added to xf
xf+1 and yf+1 for next iteration.
e) CASE STUDY
A numerical example is presented here to display the matrix operations to calculate (
values for the case of 3 transmitters.
Suppose D =
1 0
2 6
3 7
, f =
3
4
2
Hence, =
− T
T
D
D
D *
)
*
( 1 0.076
0.0081
Therefore =
∆ −
D
D
D T
T
*
)
*
( 1
III. IMPLEMENTATION
The approach presented here considers the environmental effects which cause the random
fluctuations on recorded RSSI values. These random fluctuations in return generates fluctuations
in distance calculations. In this study, environmental effects are incl
factorsin the calculations and they are deployed to reduce the distance fluctuations between the
transmitters and receivers due to RSSI variations. A Classical Kalman filtering stage is also
included on pre-smoothed distance values to
positioning accuracies. A living room with physical dimensions of 5m x 4m is considered as the
test area See block diagram in Fig.2.
International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, Dec
Left side of the above equation can be expressed as
∆
∆
=
∆
=
−
y
x
f
D
D
D T
T
*
*
)
*
( 1
f and yf initial values to generate the new estimated values of
A numerical example is presented here to display the matrix operations to calculate (
values for the case of 3 transmitters.
and DT
=
1 2 3
0 6 7
076 0.0081
0081 0.0126
1 2 3
0 6 7
=
1109
1 85 224 192
9 102 71
=
f
* 1.3841
0.2642
The approach presented here considers the environmental effects which cause the random
fluctuations on recorded RSSI values. These random fluctuations in return generates fluctuations
in distance calculations. In this study, environmental effects are included as environmental
factorsin the calculations and they are deployed to reduce the distance fluctuations between the
transmitters and receivers due to RSSI variations. A Classical Kalman filtering stage is also
smoothed distance values to smooth them further in order to increase the
positioning accuracies. A living room with physical dimensions of 5m x 4m is considered as the
test area See block diagram in Fig.2.
Figure 2: Experimental Test area
International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
44
initial values to generate the new estimated values of
A numerical example is presented here to display the matrix operations to calculate (∆x, ∆y)
192
71
The approach presented here considers the environmental effects which cause the random
fluctuations on recorded RSSI values. These random fluctuations in return generates fluctuations
uded as environmental
factorsin the calculations and they are deployed to reduce the distance fluctuations between the
transmitters and receivers due to RSSI variations. A Classical Kalman filtering stage is also
smooth them further in order to increase the
positioning accuracies. A living room with physical dimensions of 5m x 4m is considered as the
7. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, Dec
There are simple obstacles as tables, chairs and walls in the room. 4 transmitters are placed at the
corners of the ceiling. A mobile user with a receiver stands in the middle of the room.
Transmitters transmit RSSI data to receiver on the user. Base stat
WLAN. Experiments are conducted at a time when the room is empty.
a) CALIBRATION
RSSI values transmitted from transmitters are received by the object receiver at sequential
distances and they are plotted as graphs of RSSI
Fig.3 for an example transmitter.
Figure 3: RSSI values versus distances for transmitter A
Empirical formula in equation (1) is generated from these graphs in time domain and
environmental coefficient ‘n’ is calculated by using equation (2). Environmental coefficients for
each transmitter at 1 meter intervals are displayed for an example distance range together with
their average values in Fig.4. navg
smoothing factor in x distance calculations using equation (4) for each transmitter. Secondly,
smoothed distance values between transmitters and receivers are Kalman filtered after outliers are
checked and removed.
Figure 4: Plot of Environmentalcoefficients for A, B, C, D transmitters
where navgA= 3.35 navgB= 2.55 , n
International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, Dec
There are simple obstacles as tables, chairs and walls in the room. 4 transmitters are placed at the
corners of the ceiling. A mobile user with a receiver stands in the middle of the room.
Transmitters transmit RSSI data to receiver on the user. Base station is connected to receiver via
WLAN. Experiments are conducted at a time when the room is empty.
RSSI values transmitted from transmitters are received by the object receiver at sequential
distances and they are plotted as graphs of RSSI values versus distances across the test area. See
Fig.3 for an example transmitter.
Figure 3: RSSI values versus distances for transmitter A
Empirical formula in equation (1) is generated from these graphs in time domain and
ent ‘n’ is calculated by using equation (2). Environmental coefficients for
each transmitter at 1 meter intervals are displayed for an example distance range together with
avg value is derived for each transmitter from ‘n’ values and used as
smoothing factor in x distance calculations using equation (4) for each transmitter. Secondly,
smoothed distance values between transmitters and receivers are Kalman filtered after outliers are
f Environmentalcoefficients for A, B, C, D transmitters
= 2.55 , navgC=2.21 , navgD= 2.28
International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
45
There are simple obstacles as tables, chairs and walls in the room. 4 transmitters are placed at the
corners of the ceiling. A mobile user with a receiver stands in the middle of the room.
ion is connected to receiver via
RSSI values transmitted from transmitters are received by the object receiver at sequential
values versus distances across the test area. See
Empirical formula in equation (1) is generated from these graphs in time domain and
ent ‘n’ is calculated by using equation (2). Environmental coefficients for
each transmitter at 1 meter intervals are displayed for an example distance range together with
values and used as
smoothing factor in x distance calculations using equation (4) for each transmitter. Secondly,
smoothed distance values between transmitters and receivers are Kalman filtered after outliers are
8. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, Dec
b) CORRECTIVE POSITIONING
Correction parameters (∆x,∆y) are calculated as in section II.d.bydeploying (x
(xf,yf) coordinates. Object coordinates, (x,y), are estimated by adding (
for each iteration. For example, small random values of (x
coordinates are calculated for 10 iterations. These estimated c
number of iterations given in Fig.5, Fig.6 and Fig.7.
Figure 5: Estimated object (x,y) coordinates for object point (2,2) after 10 iterations
Figure 6: stimated object (x, y) coordinates for object point (3,2)
Figure 7: Estimated object (x, y) coordinates for object point (2, 1) after 10 iterations
International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, Dec
OSITIONING
∆ ∆y) are calculated as in section II.d.bydeploying (xi,y
coordinates. Object coordinates, (x,y), are estimated by adding (∆x,∆y) values to (x
for each iteration. For example, small random values of (xf,yf) = (0.5,0.75) are chosen and (x,y)
coordinates are calculated for 10 iterations. These estimated coordinates are plotted against the
number of iterations given in Fig.5, Fig.6 and Fig.7.
Figure 5: Estimated object (x,y) coordinates for object point (2,2) after 10 iterations
stimated object (x, y) coordinates for object point (3,2) after 10 iterations
Figure 7: Estimated object (x, y) coordinates for object point (2, 1) after 10 iterations
International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
46
,yi) values and
∆y) values to (xf,yf)
) = (0.5,0.75) are chosen and (x,y)
oordinates are plotted against the
Figure 5: Estimated object (x,y) coordinates for object point (2,2) after 10 iterations
after 10 iterations
Figure 7: Estimated object (x, y) coordinates for object point (2, 1) after 10 iterations
9. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
47
IV. DISCUSSIONS
A localization approach is presented by using‘d’ distances between the transmitters and receivers.
Calculated‘d’ distances with measured RSSI values and the estimated distances between the
transmitters and initial (xf, yf) valuesare utilized. Their difference is defined as a difference
function and it is expressed as a first order Taylor series. Correction parameters ∆x and ∆y are
added to user defined initialcoordinates, (xf,yf), inx and y direction. These parameters are changed
with the change of calculated‘d’ values at every iteration.After a number of iterations, the object
location coordinates are approached with the best possible error margin.
Recordings of the raw RSSI data by the receiver on the object are placed in a database in the base
station. These recordings contain variations due to RF signal variations. In the proposed study,
calculated object distances from transmitters are subjected to 2 level smoothing procedures one
with environmental coefficients and the other with Kalman filtering.
Examples in Figures (5), (6) and (7) show that an initial starting (xf,yf ) = (0.5,0.75) values are
iterated to (2.4 ,1.8) , (2.7, 1.6) and (2.3, 0.8) at the end of 10 iterations. These estimated object
coordinates correspond to physical object points of (2,2), (3,2) and (2,1) with error marginsof
0.45m, 0.50m and 0.36m respectively. Hence the proposedtechnique has a localization error of
average 0.44m in a grid space of 1m. This level of accuracy is reasonably good comparing to
many localization systems in literature where the localization accuracies are around 1 grid space.
In majority of localization procedures, RSSI measurements are carried out and different
algorithms are applied to find the object locations in real time. In some cases, prediction
techniques are applied and final object location is determined by using previous object location
calculations. Kalman filtering technique is one of them. Object location coordinates are calculated
in real time and Kalman filtering is applied to smooth these coordinates. Consequently,
fluctuations amongthem are reduced and a final object location is obtained.
On the other hand, Taylor series method is employed in this study.. Initial values for object
coordinates are assumed approximately close to object location. Distance betweenthis locationand
the calculated location from RSSI measurements is taken as the error function. Taylor expansion
series of the error function approaches to the actual object location by reducing the amplitude of
the error function. This is an alternativesmoothing technique. In second stage Kalman filtering is
also applied to reduce the fluctuations further.
V. CONCLUSIONS
A new approach with an average positioning accuracy of half a grid space is introduced in
indoors. Measurements are carried out in an area with minor obstacles. Hence the effects of
environmental conditions are taken into account for every transmitted RF signal from the
transmitters. Each transmitter radiation is calibrated with respect to environmental effects and an
environmental factor‘n’ is introduced during the calculation of d distances between the
transmitters and receivers.
Distance difference between calculated and estimated object distances is considered as a function.
This function is used to introduce correction parameterson the initial estimated object
coordinatesduring every iteration.
10. International Journal of Computer Science & Information Technology (IJCSIT) Vol 8, No 6, December 2016
48
Positioning accuracies in literature is around the grid space of the test areas. In most of the
systems, a number of reference nodes are utilized across the test area. Fingerprint maps are
generated andk-NN algorithms are employed. The positioning accuracies are still around or
slightly less than the grid space. These techniques in return increase the cost and efforts.
In this approach cost and effort factors are reduced to minimum. An object receiver just collects
RSSI data from transmitters. The user only needs to introduce small initial coordinates as the
startup condition. An applied algorithm calculates the object location iteratively. In conclusion,
the system introduced here is a very simple and fairly accurate localization system.
VI. REFERENCES
[1] http://www.rfcode.com/
[2] http://www.jennic.com/jennic_support/application_notes/jnan-1052_home_sensor_demonstration
[3] Priyantha, N. B; The cricket indoor location system: PhD Thesis, Massachusetts Institute of
Technology. 199 p, June 2005
[4] P. Bahl, V.N. Padmanabhan; RADAR: An in-building RFbased user location and tracking system, in:
Proceedings of IEEE INFOCOM 2000, Tel-Aviv, Israel (March 2000),
[5] Garmin Corporation, About GPS, http://www.garmin.com/aboutGPS/
[6] Lionel M.NI, Yunhao Liu, Iu Cho Lau, Abhıshek P. Patil; LANDMARC: Indoor Location Sensing
Using Active RFID;Wireless Networks 10, 701–710, 2004
[7] J. Hightower, R. Want and G. Borriello; SpotON: An indoor 3D location sensing technology based on
RF signal strength, UW CSE00-02-02, February 2000,
[8] G.Binazzi ,L.Chisci,F.Chiti, R.Fantacci, S.Menci : Localization of a swarm of mobile agents via
unscented Kalman filtering, Proc. IEEE Int conf. of Communication. ICC, Germany, (2009).
[9] Sophocles J Orfanidis ,lecture notes on Elliptic Filer Design , www.ece.rutgers.edu/-orfanidi/ece521 ,
2006
[10] Steven Walfish, A review of statistical outlier methods, Pharmaceutical technology, 2008, pp1-5
[11] AdaVittoriaBosisio ,Performances of an RSSI-based positioning and tracking algorithm ,
International Conference on Indoor Positioning and Indoor Navigati(IPIN),pp 1-8, 21-23 September
2011, Portugal
[12] Alberto Colorni, Marco Dorigo, Vittorio Maniezzo , Distributed Optimization by Ant Colonies,
proceedings of ECAL91 – European conference on artificial Life ,Paris, FRANCE, Elsevier
publishing , pp 134-142 , 1991