Enhancing RSSI-based tracking accuracy in wireless sensor networks

Blumrosen, Gaddi; Hod, Bracha; Anker, Tal; Dolev, Danny; Rubinsky, Boris

doi:10.1145/2480730.2480732

Cited by 48 publications

(28 citation statements)

References 33 publications

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“…La validación se ha realizado en entornos reales, analizando la influencia entre el número de muestras a promediar (es decir, tiempo de actualización de la posición), y la densidad de nodos en el escenario bajo estudio. Como se desprende de la Tabla IV, la precisión del sistema propuesto está en línea con la proporcionada por otros ILS tales como [11,17]. Nótese que con respecto a métodos basados en Zigbee que requieren calibración previa [8,18,19] el error relativo de posicionamiento promedio empeora solamente del 4.2% al 6.5%, mientras que el error máximo se mantiene por debajo del 20%.…”

Section: Conclusionesunclassified

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ZigBee-based Sensor Network for Indoor Location and Tracking Applications

Álvarez

Las-Heras

2016

IEEE Latin Am. Trans.

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Abstract-Practical asset and people tracking in indoor scenarios using Received Signal Strength (RSS) ZigBee-based sensor network is presented. The Indoor Location System (ILS) is based on a novel algorithm that uses relative field levels gathered by a set of transmitter nodes. These levels are introduced into a cost function which minimum gives the asset location estimation. The use of relative field levels-based algorithm avoids the need of system calibration due to signal strength fluctuation. The method is tested in two real indoor scenarios: the first example is devoted to evaluate the influence of the number of transmitting nodes on the position estimation accuracy as well as the number of samples to be averaged aiming to reduce uncertainty. The second example shows a realistic case of asset tracking, also studying the influence of sample averaging and number of transmitting nodes.

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Section: Conclusionesunclassified

“…Entre estas tecnologías, las más extendidas son ZigBee [7][8][9][10][11], RFID [12,13], Bluetooth [14] o WiFi [15]. En el caso de WiFi y Bluetooth, presentan la ventaja de que estas tecnologías se encuentran disponibles en muchos dispositivos móviles, así como su elevada penetración entre los usuarios.…”

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ZigBee-based Sensor Network for Indoor Location and Tracking Applications

Álvarez

Las-Heras

2016

IEEE Latin Am. Trans.

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“…W IRELESS sensor networks (WSNs) are currently used in a wide range of applications including environmental monitoring [1] and object tracking [2]. Target coverage and connectivity are two main challenging and practically important issues of WSNs.…”

Section: Introductionmentioning

confidence: 99%

Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks

Liao

Wang

Zhang

et al. 2015

IEEE Trans. Parallel Distrib. Syst.

174

114

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Abstract-Coverage of interest points and network connectivity are two main challenging and practically important issues of Wireless Sensor Networks (WSNs). Although many studies have exploited the mobility of sensors to improve the quality of coverage and connectivity, little attention has been paid to the minimization of sensors' movement, which often consumes the majority of the limited energy of sensors and thus shortens the network lifetime significantly. To fill in this gap, this paper addresses the challenges of the Mobile Sensor Deployment (MSD) problem and investigates how to deploy mobile sensors with minimum movement to form a WSN that provides both target coverage and network connectivity. To this end, the MSD problem is decomposed into two sub-problems: the Target COVerage (TCOV) problem and the Network CONnectivity (NCON) problem. We then solve TCOV and NCON one by one and combine their solutions to address the MSD problem. The NP-hardness of TCOV is proved. For a special case of TCOV where targets disperse from each other farther than double of the coverage radius, an exact algorithm based on the Hungarian method is proposed to find the optimal solution. For general cases of TCOV, two heuristic algorithms, i.e., the Basic algorithm based on clique partition and the TV-Greedy algorithm based on Voronoi partition of the deployment region, are proposed to reduce the total movement distance of sensors. For NCON, an efficient solution based on the Steiner minimum tree with constrained edge length is proposed. The combination of the solutions to TCOV and NCON, as demonstrated by extensive simulation experiments, offers a promising solution to the original MSD problem that balances the load of different sensors and prolongs the network lifetime consequently.

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“…Typically, an RSS-based mobile tracking approach usually consists of a set of static nodes with known location information, referred to as reference nodes. The tracking algorithm tries to continuously estimate the mobile target's location from the RSS measurements between the mobile target and its neighboring reference nodes [3], [4]. Since existence of multipath fading, reflections, diffraction and interference highly affects the correspondence between the RSS and relative distance, more works [5], [6] are proposed to minimize the dynamic fluctuation of the radio signal received from each reference node.…”

Section: Introductionmentioning

confidence: 99%

Wireless Sensor Network Based Mobile Tracking System

Maung¹,

Kikuchi²

2016

IJCCE

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Mobile target tracking through large-scale wireless sensor networks (WSN) demands a large number of reference nodes, which is not feasible for resource-constrained WSNs. This paper proposes a resource-efficient mobile tracking system which integrates connectivity-based range-free approach and Received Signal Strength (RSS) based ranging approach to improve the tracking performance while reducing the specialized hardware requirement. In our proposed system, regulated hop-count values between static unknown nodes and reference nodes in the targeted area of interest for mobile tracking are first estimated in the network configuration phase. Then, location of the mobile target is tracked based on the regulated hop-count values and the available RSS measurements from its surrounding nodes at each tracking point without any extra hardware. Additionally, estimated location is enhanced by correcting with the known information of maximum velocity of the mobile target. Simulation and experimental results show that the proposed system offers preferable mobile tracking performance with minimum reference node utilization in both small-scale and large-scale networks.

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Enhancing RSSI-based tracking accuracy in wireless sensor networks

Cited by 48 publications

References 33 publications

ZigBee-based Sensor Network for Indoor Location and Tracking Applications

ZigBee-based Sensor Network for Indoor Location and Tracking Applications

Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks

Wireless Sensor Network Based Mobile Tracking System

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