Indoor Localization Using Local Node Density In Ad Hoc WSNsjoaquin_gonzalez
Presentation for Master Thesis "Indoor Localization Using Local Node Density In Ad Hoc WSNs", research supported by Free University Berlin. Coordinators: Freddy Lopez Villafuerte, Gianluca Cornetta.
Virtual 2 d positioning system by using wireless sensors in indoor environmentijwmn
A 2D location detection system is constructed by using Wireless Sensor Nodes (WSN) to create aVirtual
Fingerprint map, specifically designed for use in an indoor environment. WSN technologies and
programmable ZigBee wireless network protocols are employed. This system is based on radio-location
fingerprinting technique. Both Linear taper functions and exponential taper functions are utilized with the
received signal strength distributions between the fingerprint nodes to generate virtual fingerprint maps.
Thus, areal and virtual combined fingerprint map is generated across the test area. K-nearest
neighborhood algorithm has been implemented on virtual fingerprint maps, in conjunction with weight
functions used to find the coordinates of the unknown objects. The system Localization accuracies of less
than a grid space areproved in calculations.
Indoor Localization Using Local Node Density In Ad Hoc WSNsjoaquin_gonzalez
Presentation for Master Thesis "Indoor Localization Using Local Node Density In Ad Hoc WSNs", research supported by Free University Berlin. Coordinators: Freddy Lopez Villafuerte, Gianluca Cornetta.
Virtual 2 d positioning system by using wireless sensors in indoor environmentijwmn
A 2D location detection system is constructed by using Wireless Sensor Nodes (WSN) to create aVirtual
Fingerprint map, specifically designed for use in an indoor environment. WSN technologies and
programmable ZigBee wireless network protocols are employed. This system is based on radio-location
fingerprinting technique. Both Linear taper functions and exponential taper functions are utilized with the
received signal strength distributions between the fingerprint nodes to generate virtual fingerprint maps.
Thus, areal and virtual combined fingerprint map is generated across the test area. K-nearest
neighborhood algorithm has been implemented on virtual fingerprint maps, in conjunction with weight
functions used to find the coordinates of the unknown objects. The system Localization accuracies of less
than a grid space areproved in calculations.
Wireless sensor networks localization algorithms a comprehensive surveyIJCNCJournal
Wireless sensor networks (WSNs) have recently gained a lot of attention by scientific community. Small
and inexpensive devices with low energy consumption and limited computing resources are increasingly
being adopted in different application scenarios including environmental monitoring, target tracking and
biomedical health monitoring. In many such applications, node localization is inherently one of the system
parameters. Localization process is necessary to report the origin of events, routing and to answer
questions on the network coverage ,assist group querying of sensors. In general, localization schemes are
classified into two broad categories: range-based and range-free. However, it is difficult to classify hybrid
solutions as range-based or range-free. In this paper we make this classification easy, where range-based
schemes and range-free schemes are divided into two types: fully schemes and hybrid schemes. Moreover,
we compare the most relevant localization algorithms and discuss the future research directions for
wireless sensor networks localization schemes.
A New Approach for Error Reduction in Localization for Wireless Sensor Networksidescitation
Localization is one of the most challenging and
important issues in wireless sensor networks (WSNs),
especially if cost effective approaches are demanded. Distance
measurement based on RSSI (Received Signal Strength
Indication) is a low cost and low complexity of the distance
measurement technique, and it is widely applied in the range-
based localization of the WSN. The RSS (Received Signal
Strength) used to estimate the distance between an unknown
node and a number of reference nodes with known co-ordinates.
Location of the target node is then determined by trilateration.
Log-normal shadowing model, can better describe the
relationship between the RSSI value and distance. Non-line
of sight and multipath transmission effects as the indoor
environment, the distance error or ranging error is large. In
this paper, experimental results that are carried out to analyze
the sensitivity of RSSI measurements in an indoor
environment for various power levels are presented. Location
error influenced by distance measure error and network
connectivity is analyzed.
Index Terms—
Determining a person’s physical position in a multi-building indoor space using wifi fingerprinting on UJIIndoor Data Set to construct machine learning models.
Optimization of Average Distance Based Self-Relocation Algorithm Using Augmen...csandit
Mobile robots with sensors installed on them are used in wireless sensor networks to generate information about the area. These mobile robotic sensors have to relocate themselves after initial location in the field to gain maximum coverage The average distance based algorithm for relocation process of mobile sensors does not require any GPS system for tracking the robotic sensors, thus avoiding cost, but increasing energy consumption. Augmented Lagrangian method is introduced in average distance based algorithm to reduce the extra energy
consumption by sensors in average distance based relocation process. This modified average distance relocation scheme also improves the coverage area and the time taken by mobile
robotic sensors to come to their final positions.
Lift using projected coded light for finger tracking and device augmentationShang Ma
We present Lift, a visible light-enabled finger
tracking and object localization technique that allows users to
perform freestyle multi-touch gestures on any object’s surface in
an everyday environment. By projecting encoded visible patterns
onto an object’s surface (e.g. paper, display, or table), and
localizing the user’s fingers with light sensors, Lift offers users a
richer interactive space than the device’s existing interfaces.
Additionally, everyday objects can be augmented by attaching
sensor units onto their surface to accept multi-touch gesture
input. We also present two applications as proof of concept.
Finally, results from our experiments indicate that Lift can
localize ten fingers simultaneously with an average accuracy of
1.7 millimeter and an average refresh rate of 84 Hz with 31
milliseconds delay on WiFi and 23 milliseconds delay on serial
communication, making gesture recognition on non-
instrumented objects possible.
Modelling of wireless sensor networks for detection land and forest fire hotspotTELKOMNIKA JOURNAL
Indonesia located in South East Asia countries with tropical region, forest fires in Indonesia is
one of big issue and disaster because it happens in almost of every year, this is because of some of region
consist of peat land that high risk for fire especially in dry season. Riau Province is one of region that
regularly incident of forest fire with affected the length and breadth of Indonesia. Propose development of
Wireless Sensor Networks (WSNs) for detection of land and forest fire hotspot in Indonesia as well as one
of the main consents in this research, case location in Riau province is at one of the regions that high risk
forest fire in dry season. WSNs technology used for ground sensor system to collect environmental data.
Data training for fire hotspot detection is done in data center to determine and conclude of fire hotspot then
potential to become big fire. The deployment of sensors located at several locations that has potential for
fire incident, especially as data shown in previous case and forecast location with potential fire happen.
Mathematical analysis is used in this case for modelling number of sensors required to deploy and the size
of forest area. The design and development of WSNs give high impact and feasibility to overcome current
issues of forest fire and fire hotspot detection in Indonesia. The development of this system used WSNs
highly applicable for early warning and alert system for fire hotspot detection.
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.
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.
Computational Geometry based Remote Networkingidescitation
In recent years wireless sensor networks (WSNs) have become one of the most
active research areas due to the bright and interesting future promised to the world of
information technology. It is an emerging field which is accomplishing much importance
because of its vast contribution in varieties of applications. Coverage is one of the important
aspects of WSNs and many approaches are introduced to maximize it. It is the key research
issue in WSN as it can be considered as the measure of the Quality of Service (QoS) of
sensing function for a sensor network. The goal of coverage is to have each location in the
physical space of interest within the sensing range of at least one sensor. By combining
computational geometry and graph theoretic techniques, specifically the Voronoi Diagram
(VD), Delaunay Triangulation (DT) and Graph Search algorithms, can solve the problem.
This paper defines some recent research approaches on coverage of WSNs using VD and
DT. Also shows how they are being utilized in various research works.
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.
Wireless sensor networks localization algorithms a comprehensive surveyIJCNCJournal
Wireless sensor networks (WSNs) have recently gained a lot of attention by scientific community. Small
and inexpensive devices with low energy consumption and limited computing resources are increasingly
being adopted in different application scenarios including environmental monitoring, target tracking and
biomedical health monitoring. In many such applications, node localization is inherently one of the system
parameters. Localization process is necessary to report the origin of events, routing and to answer
questions on the network coverage ,assist group querying of sensors. In general, localization schemes are
classified into two broad categories: range-based and range-free. However, it is difficult to classify hybrid
solutions as range-based or range-free. In this paper we make this classification easy, where range-based
schemes and range-free schemes are divided into two types: fully schemes and hybrid schemes. Moreover,
we compare the most relevant localization algorithms and discuss the future research directions for
wireless sensor networks localization schemes.
A New Approach for Error Reduction in Localization for Wireless Sensor Networksidescitation
Localization is one of the most challenging and
important issues in wireless sensor networks (WSNs),
especially if cost effective approaches are demanded. Distance
measurement based on RSSI (Received Signal Strength
Indication) is a low cost and low complexity of the distance
measurement technique, and it is widely applied in the range-
based localization of the WSN. The RSS (Received Signal
Strength) used to estimate the distance between an unknown
node and a number of reference nodes with known co-ordinates.
Location of the target node is then determined by trilateration.
Log-normal shadowing model, can better describe the
relationship between the RSSI value and distance. Non-line
of sight and multipath transmission effects as the indoor
environment, the distance error or ranging error is large. In
this paper, experimental results that are carried out to analyze
the sensitivity of RSSI measurements in an indoor
environment for various power levels are presented. Location
error influenced by distance measure error and network
connectivity is analyzed.
Index Terms—
Determining a person’s physical position in a multi-building indoor space using wifi fingerprinting on UJIIndoor Data Set to construct machine learning models.
Optimization of Average Distance Based Self-Relocation Algorithm Using Augmen...csandit
Mobile robots with sensors installed on them are used in wireless sensor networks to generate information about the area. These mobile robotic sensors have to relocate themselves after initial location in the field to gain maximum coverage The average distance based algorithm for relocation process of mobile sensors does not require any GPS system for tracking the robotic sensors, thus avoiding cost, but increasing energy consumption. Augmented Lagrangian method is introduced in average distance based algorithm to reduce the extra energy
consumption by sensors in average distance based relocation process. This modified average distance relocation scheme also improves the coverage area and the time taken by mobile
robotic sensors to come to their final positions.
Lift using projected coded light for finger tracking and device augmentationShang Ma
We present Lift, a visible light-enabled finger
tracking and object localization technique that allows users to
perform freestyle multi-touch gestures on any object’s surface in
an everyday environment. By projecting encoded visible patterns
onto an object’s surface (e.g. paper, display, or table), and
localizing the user’s fingers with light sensors, Lift offers users a
richer interactive space than the device’s existing interfaces.
Additionally, everyday objects can be augmented by attaching
sensor units onto their surface to accept multi-touch gesture
input. We also present two applications as proof of concept.
Finally, results from our experiments indicate that Lift can
localize ten fingers simultaneously with an average accuracy of
1.7 millimeter and an average refresh rate of 84 Hz with 31
milliseconds delay on WiFi and 23 milliseconds delay on serial
communication, making gesture recognition on non-
instrumented objects possible.
Modelling of wireless sensor networks for detection land and forest fire hotspotTELKOMNIKA JOURNAL
Indonesia located in South East Asia countries with tropical region, forest fires in Indonesia is
one of big issue and disaster because it happens in almost of every year, this is because of some of region
consist of peat land that high risk for fire especially in dry season. Riau Province is one of region that
regularly incident of forest fire with affected the length and breadth of Indonesia. Propose development of
Wireless Sensor Networks (WSNs) for detection of land and forest fire hotspot in Indonesia as well as one
of the main consents in this research, case location in Riau province is at one of the regions that high risk
forest fire in dry season. WSNs technology used for ground sensor system to collect environmental data.
Data training for fire hotspot detection is done in data center to determine and conclude of fire hotspot then
potential to become big fire. The deployment of sensors located at several locations that has potential for
fire incident, especially as data shown in previous case and forecast location with potential fire happen.
Mathematical analysis is used in this case for modelling number of sensors required to deploy and the size
of forest area. The design and development of WSNs give high impact and feasibility to overcome current
issues of forest fire and fire hotspot detection in Indonesia. The development of this system used WSNs
highly applicable for early warning and alert system for fire hotspot detection.
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.
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.
Computational Geometry based Remote Networkingidescitation
In recent years wireless sensor networks (WSNs) have become one of the most
active research areas due to the bright and interesting future promised to the world of
information technology. It is an emerging field which is accomplishing much importance
because of its vast contribution in varieties of applications. Coverage is one of the important
aspects of WSNs and many approaches are introduced to maximize it. It is the key research
issue in WSN as it can be considered as the measure of the Quality of Service (QoS) of
sensing function for a sensor network. The goal of coverage is to have each location in the
physical space of interest within the sensing range of at least one sensor. By combining
computational geometry and graph theoretic techniques, specifically the Voronoi Diagram
(VD), Delaunay Triangulation (DT) and Graph Search algorithms, can solve the problem.
This paper defines some recent research approaches on coverage of WSNs using VD and
DT. Also shows how they are being utilized in various research works.
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.
IJCER (www.ijceronline.com) International Journal of computational Engineeri...ijceronline
Call for paper 2012, hard copy of Certificate, research paper publishing, where to publish research paper,
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJCER, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, research and review articles, IJCER Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathematics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer review journal, indexed journal, research and review articles, engineering journal, www.ijceronline.com, research journals,
yahoo journals, bing journals, International Journal of Computational Engineering Research, Google journals, hard copy of Certificate,
journal of engineering, online Submission
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Unit III - Solved Question Bank- Robotics Engineering -Sanjay Singh
This Question Bank for Robotics Engineering is only for academic purpose and not for any commercial use. Students of Anna University and other Universities can use it for reference and knowledge.
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,
Greedy – based Heuristic for OSC problems in Wireless Sensor NetworksIJMER
This paper contains optimize set coverage problem in wireless sensor networks with adaptable sensing range. Communication and sensing consume energy, so efficient power management can extended the network lifetime. In this paper we consider a enormous number of sensors with adaptable sensing range that are randomly positioned to monitor a number of targets. Every single target may be redundantly covered by various sensors. For preserving energy resources we organize sensors in sets stimulated successively. In this paper we introduce the Optimize Set Coverage (OSC) problem that has in unbiased finding with an extreme number of set covers in which every sensor node to be activated is connected to the base station. A sensor can be participated in various sensor sets, but the overall energy consumed in all groups is forced by the primary energy reserves. We show that the OSC problem is NP-complete and we propose the solutions: an integer programming for OSC problem, a linear programming for OSC problem with greedy approach, and a distributed and localized heuristic. Simulation results are presented and validated to our approaches.
Network Lifetime Enhancement by Node Deployment in WSNIJTET Journal
Abstract— The key challenge in wireless sensor network is network lifetime so it is necessary to increase the network lifetime. The work deals with the enhancement of the network lifetime for target coverage problem in wireless sensor network while deploying the sensor nodes. Initially sensor nodes and targets are placed randomly, where the targets are the not sensor nodes its external parameter. Network lifetime for this scenario is computed, where the sensing range and initial energy of the battery are assumed. Network lifetime is based on sensor nodes that monitor the targets and lifetime of battery. The randomly placed sensor nodes are redeployed using optimization algorithm called Artificial Bee Colony (ABC). The network lifetime for redeployed sensor nodes are computed and compared with randomly deployed sensor nodes.
The autonomous Test Bench is the growing field of
testing device. The Rapid production firms require rapid testing
infrastructure. Many firms till now use legacy system. The
Autonomous Test Bench is a Rapid Application Development tool
to accelerate the device testing rapid. To implementation ATB
(Autonomous Test Bench) the major requirement is to measure
the target object distance from robotic arm to trigger the device
(like push button, gripping something etc.) Not only Robotic
system, many fields of industry are required to capture ultrasonic
scan data. Sometimes it should be wireless system which may be
positioned anywhere. This paper describes a novel way to capture
surrounded ultrasonic scan data. The device is portable and
wireless and as well as cost effective. To measure object distance,
ultrasonic peripatetic scanner uses two servo motors to scan the
object horizontally and vertically. The main controller is a credit
card sized computer Raspberry pi with high processing capability
and portability. The programs are written using Python which is
an interpreted language.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Recent advances in radio and embedded systems for completing the procedure of location estimation most
of the time sensor networks are fully dependent on the distance measurements that is present between the
sensor neighbourhood node. Techniques used for the localization can be categorized differently.
Techniques used for the measurement of the distance between the wireless sensor nodes, dependent upon
the physical means are divided into three broader categories namely Received signal strength (RSS), Angle
of Arrival (AOA) and propagation base on time measurements. This paper discusses the most of the
approached of WSN and IoT based positioning system.
Popularity of ubiquitous computing increases the importance of location-aware applications,
which increases the need for finding location of the user. In this paper, we present a novel localization method
for indoor environments using Wi-Fi infrastructure.
While localization using Wi-Fi is cost effective, handling the obstructions which are the main cause of
signal propagation error in indoor environments is a challenging task. We address this problem in two levels,
resulting in increased accuracy of localization. In the first level, we "localize" the residing area of user node in
coarse granularity. Then, we use building layout to find the objects that attenuate the signal between the
reference node and the coarse estimate of the location of user node. Using multi-wall propagation model, we
apply corrections for all obstructions and find the location of user node. Empirical results based on experiments
conducted in lab-scale, shows meter-level accuracy.
Indoor localization in sensor network with estimation of doa and rssi measure...eSAT Journals
Abstract Due to advancement in MEMS technology today wireless sensor network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper we provide study and prototype implementation of architecture and algorithm for network of tiny wireless sensors for localization purpose. Key Words— sensor network; localization, RSSI; Angle-of-arrival (AoA); direction-of-arrival (DoA).
Optimum Sensor Node Localization in Wireless Sensor Networkspaperpublications3
Abstract: Scientists, engineers, and researchers use wireless sensor networks (WSN) for a wide array of applications. Many of these applications rely on knowledge of the precise position of each node. An optimum localization algorithm can be used for determining the position of nodes in a wireless sensor network. This paper provides an overview of different approach of node localization discovery in wireless sensor networks. The overview of the schemes proposed by different scholars for the improvement of localization in wireless sensor networks is also presented. Experiments were performed in a testbed area containing anchor and blind nodes deployed in it to characterize the pathloss exponent and to determine the localization error of the algorithm. Details regarding the implementation of new algorithm are also discussed in this paper.
Adaptive Monitoring and Localization of Faulty Node in a Wireless Sensor Netw...Onyebuchi nosiri
Abstract
This work seeks to solve the problem that is being experienced in most existing remote monitoring systems by coming up with an enhanced monitoring system called Wireless Sensor Network. A Personal Area Network was evolved to increase the coverage area by spatially distributing Sensor nodes to capture and transmit physical parameters like temperature and Carbon monoxide in an indoor local cooking environment. Faulty node detection and localization was also realized, this was achieved by coming up with an algorithm that logically considers the receive signal strength value of -100 dbm as threshold, Result of data transmitted were viewed via a C-Sharp interface for Adaptive monitoring. The result from the Visual Basic plot shows that the Sensor nodes were able to capture temperature range of between 250C to 510C while the result of the CO emission shows an interval of 0.01g/m3 to 30.0 g/m3. A comparison between data transmitted at source and data received at the destination (sink) was carried out, a ranking test was used to validate the data received, a 0.9325 correlation value was obtained which shows a high level of integrity of 93.25% .
[Ubicomp'15]SakuraSensor: Quasi-Realtime Cherry-Lined Roads Detection throug...Ubi NAIST
SakuraSensor, a system which senses and shares the information of roads with flowering cherries by leveraging car-mounted smart-phones.
Honorable Mention Award of UbiComp2015.
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
Sharpen existing tools or get a new toolbox? Contemporary cluster initiatives...Orkestra
UIIN Conference, Madrid, 27-29 May 2024
James Wilson, Orkestra and Deusto Business School
Emily Wise, Lund University
Madeline Smith, The Glasgow School of Art
Have you ever wondered how search works while visiting an e-commerce site, internal website, or searching through other types of online resources? Look no further than this informative session on the ways that taxonomies help end-users navigate the internet! Hear from taxonomists and other information professionals who have first-hand experience creating and working with taxonomies that aid in navigation, search, and discovery across a range of disciplines.
0x01 - Newton's Third Law: Static vs. Dynamic AbusersOWASP Beja
f you offer a service on the web, odds are that someone will abuse it. Be it an API, a SaaS, a PaaS, or even a static website, someone somewhere will try to figure out a way to use it to their own needs. In this talk we'll compare measures that are effective against static attackers and how to battle a dynamic attacker who adapts to your counter-measures.
About the Speaker
===============
Diogo Sousa, Engineering Manager @ Canonical
An opinionated individual with an interest in cryptography and its intersection with secure software development.
This presentation by Morris Kleiner (University of Minnesota), was made during the discussion “Competition and Regulation in Professions and Occupations” held at the Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found out at oe.cd/crps.
This presentation was uploaded with the author’s consent.
Acorn Recovery: Restore IT infra within minutesIP ServerOne
Introducing Acorn Recovery as a Service, a simple, fast, and secure managed disaster recovery (DRaaS) by IP ServerOne. A DR solution that helps restore your IT infra within minutes.
Supercharge your AI - SSP Industry Breakout Session 2024-v2_1.pdf
Cost-Efficient Sensor Deployment in Indoor Space with Obstacles
1. Cost-Efficient Sensor Deployment
in Indoor Space with Obstacles
Nara Institute of Science and Technology
*Tokyo University of Science, Yamaguchi
Nanan Marc Thierry Kouakou, Keiichi Yasumoto,
Shinya Yamamoto*, and Minoru Ito
2. Overview
2
Indoor Wireless Sensor Network (indoor WSN)
Monitor/Collect various information of indoor space
Human position, temperature, humidity, illuminance, etc
Application
Human activity prediction, energy-saving
appliance control, security, etc
Challenges
Coverage of target 3D space
Connectivity among sensor nodes
3. Design of Indoor WSN
Characteristics of indoor WSN
Target monitoring space is three dimensional
Constraints on installing positions (cost, defiling)
Ex. Easy on ceiling/wall, but not easy on floor/in the air
Many obstacles
Influence on sensing and wireless communication
Requirements for indoor WSN
Minimize deployment cost
Guarantee full coverage and wireless connectivity
3
take into account shape of
target space, deployment
cost, influence of obstacles
5. Related Work:
Coverage of 2D space with Obstacles
5
[1] proposed a method using Delaunay triangulation
First apply the contour deployment (around obstacles), then
cover the remaining space by triangles
Problem
The deployment is only considered in 2D space, leading to some
inaccuracies when applying to 3D space
Deployment cost depending on position is not considered
[1] Wu et al., “A Delaunay Triangulation based method for wireless
sensor network deployment”, Computer Communications, 2007
Delaunay
triangulation
6. Related Work:
Coverage/connectivity in 3D space without obstacles
6
[2] Bai et al., “Full-Coverage and k-Connectivity (k=14,6) Three
Dimensional Networks”, Infocom 2009
[3] Bai et al., “Low-Connectivity and Full-Coverage Three Dimensional
Wireless Sensor Networks”, MobiHoc 2009
[2][3] showed optimal deployment patterns guaranteeing full
coverage and wireless connectivity in 3D space
Several different optimal deployment patterns depending on relationship
between sensing and communication radii rs and rc
Problem
Not consider influence of obstacles and position-dependent
deployment cost
7. Human Body Shadowing Problem
7
• No approach focusing on the indoor WSN deployment problem that
takes into account the human body shadowing effects
[4][5] discussed effects of the human body and its mobility
on indoor communications
[4] Klepal et al., Influence of People Shadowing on Optimal Deployment of
WLAN Access Points, VTC2004-Fall.
[5] Collonge et al., Influence of the human activity on wide-band characteristics
of the 60 GHz indoor radio channel, IEEE Trans. Wireless Commun., 3(6), 2004.
8. Contribution of this Work
Cost-efficient deployment methods for 3D WSNs in
indoor environment taking into account obstacles
Coverage of 3D space with static and mobile obstacles
(human body)
8
10. Assumptions
Sensor nodes
Shape of sensing range and communication range: sphere
Sensing radius rs, communication radius rc (fixed)
10
Target space
Deployable area
Sensor can be installed
Cost of each point in area given
Monitoring space
Space to be monitored
Obstacles (static and mobile) exist
Deployable
area
Obstacle
Monitoring
space
11. Assumptions for Obstacles
Influence on sensing
Sensor can NOT sense Information
from shadow area
Influence on wireless comm.
Sensors can NOT communicate
when obstacle is on the line of sight
11
Sensor
Sensing range
Obstacle
Shadow area
s0 s1
Wireless
communication range
Obstacle
12. Problem Definition
12
Input
Target space, monitoring space
Deployable area with cost of each point
Sensing and communication radii rs，rc
Output
Number of sensors, sensor positions
Constraints
Monitoring space is k-covered
Wireless connectivity between sensors
Objective
Minimize overall deployment cost
This is NP-hard problem (minimum set cover)
Any point of monitoring
space is covered by at
least k sensors
13. Assumption for Mobile Obstacles
m
s
mobile
obstacle
pos
s
m
mobile
obstacle
ceiling
ground
pos
mh
Only human body considered as mobile obstacle
Represented by cylinder: radius mr, height mh
Mobile obstacle obstructs monitoring point m from some sensors
sensing ranges obstructed sensors change by mobile’s position
We assume each point is affected by only one mobile obstacle at one time
Top view Side view
13
Sensors
14. Mobile k-Coverage Problem
Target problem for mobile obstacle
Determine the number of sensor nodes and their installing
positions to achieve mobile k-coverage with the minimal
deployment cost
Mobile k-Coverage
A monitoring point m is mobile k-covered if for any location of
the mobile obstacle, m is k-covered
14
16. Discretization of Problem
Complexity
Modified problem still NP-hard
Discretization
Deployable area Deployable points
Target monitoring space Monitoring points
Heuristic algorithms to achieve
a near-optimal solution in a reasonable amount of time
16
17. Algorithm for Minimal Cost
k-Coverage (only static obstacles)
per-cost volume: how many monitoring points are covered
by the deployable point per unit deployment cost
Places sensor node on the grid point
with the highest per-cost volume
Repeats until all the monitoring points
are sufficiently covered
per-cost volume =
Number of monitoring points covered
Deployment cost of the deployable point
0.65 0.75
0.150.350.35
0.25
0.2 0.65 0.25
0.45
0.050.250.35
0.25
0.2 0.150.55
0.050.250.35
0.25 0.40
0.1 0.05
17
18. Influence of the Mobile Obstacle
Vertical plane Δ
tangent to the monitoring point
orthogonal to the mobile obstacle
Shaded area: half-space divided by Δ
that contains the mobile obstacle
Nodes in the shaded area cannot sense
the monitoring point
(Δ)
shaded area
monitoring
point
Sufficient condition for mobile k-coverage:
For arbitrary position of the mobile obstacle,
the half-sphere that is not in the shaded
area, contains at least k sensor nodes
18
19. Sensor Placement for
Mobile k-Coverage (1)
Basic Idea
Consider sphere with radius: rs centered at the monitoring point
Divide it into 2k equivalent portions (spherical wedges)
Put one sensor in each wedge
k2
2
Spherical wedge
19
wedge
sensor
(Δ)
??
sensor
4
obstacle
4
Dividing into 2k wedges
(k=4)
Dividing into 2k+1 wedges
(k=2)
21. Heuristic Algorithm for Minimal Cost
Mobile k-Coverage
per-cost volume: for a deployable point, the number of covering
wedges in which it is located per unit deployment cost
For each monitoring, compute covering spherical wedges
monitoring
points
deployable
points
deployed
nodes
1. For each monitoring
point, determine its covering wedges
2. Set a node on the deployable
point with the highest per-cost volume
3. Repeat until each wedge contains
at least one node
21
k=1
23. Evaluation
Purpose
1. Understand to what extent the deployment cost can be reduced
2. Investigate the effectiveness of the computed deployment for
obstacles
23
24. Evaluation on Deployment Cost
Three deployable regions
region 1 (cost=1): on the ceiling
region 2 (cost=5): in the “air” (h = 2m)
region 3 (cost=2): on the partition walls
Target monitoring space
Horizontal plane (h = 1.5m)
Side view
floor
Top view of the indoor environment
Method # of nodes
Deploym
ent cost
Proposed Method 14 19
Triangular lattice [6] 7 35
The deployment cost is 45% smaller
[6] Bai et al., “Complete optimal deployment patterns for full-coverage and k-connectivity
(k≤ 6) wireless sensor networks”, 9th ACM Mobihoc, 2007
ceiling
24
25. Evaluation of Mobile 3-Coverage
sinktag node
sensor node
Purpose: investigate if beacon sent by tag node is received by at
least 3 sensors with sufficient RSSI for arbitrary position of user
1. The tag node broadcasts a beacon at some monitoring point
2. Sensor node which receives the beacon sends the RSSI with its ID to the sink
3. The message with (node_id, rssi) is logged with the timestamp at the sink
① ②
③
25
user
26. Coverage and Sensing Radius
rssi0 : average RSSI of a packet sent from
a ZigBee device placed at a distance 5m
rssi0 (d=5m) = -60dBm
Distance (m) 3 4 5 6
RSSI value (dBm) -56 -60 -60 -63
If a sensor node receives a beacon sent from monitoring point with
RSSI greater than rssi0, then this point is covered by the node.
ZigBee DeviceRSSI measurement without obstacle
26
27. Monitoring Area and User Position
Target monitoring area
2.5m x 2.5m, horizontal plane at height 1m above the floor
For each target point (P1…P4), the user stands at 4 positions
around the tag node at distance of 5 to 10 cm
UP1
UP2
UP3
UP4
tag node
Monitoring points User’s positions
27
5-10cm
29. Result of Mobile 3-Coverage
29
-70.0
-60.0
-50.0
-40.0
UP1 UP2 UP3 UP4
rssi0
At least 3 sensors received beacon with RSSI more than -60dbM for
any point P1—P4 and any user position UP1— UP4
mobile 3-coverage is achieved
P1
-70.0
-60.0
-50.0
-40.0
rssi0
P2
S1
S2
S3
S4
S5
S6
S7
S8
S9
UP1 UP2 UP3 UP4
30. Conclusion
Cost-efficient sensor deployment method for indoor
Defined problem taking into account position-dependent
installing cost and obstacle influence
Devised algorithm which places one sensor in each
1/2(k+1) spherical wedge for mobile k-coverage
Evaluated mobile 3-coverage on ZigBee testbed
Future work
Integrating more accurate model of radio signal
diffraction and fading effect
30
