A localization strategy based on <i>n</i>‐times trilateral centroid with weight

Qiu, Tie; Zhou, Yu; Xia, Feng; Jin, Naigao; Feng, Lin

doi:10.1002/dac.2332

Cited by 14 publications

(9 citation statements)

References 24 publications

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“…The latter problem can be solved by using a centroid algorithm [4]. This is only useful if there is a set of fixed nodes with an overlapping coverage area.…”

Section: A Range-based: Weightedmentioning

confidence: 99%

A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks

Haute¹,

Rossey²,

Becue³

et al. 2014

Annals of Computer Science and Information Systems

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Abstract-Indoor localization and navigation using wireless sensor networks is still a big challenge if expensive sensor nodes are not involved. Previous research has shown that in a sparse distributed sensor network the error distance is way too high. Even room accuracy can not be guaranteed. In this paper, an easy-to-use generic positioning framework is proposed, which allows users to plug in a single or multiple positioning algorithms. We illustrate the usability of the framework by discussing a new hybrid positioning solution. The combination of a weighted (range-based) and proximity (range-free) algorithm is made. Both solutions separately have an average error distance of 13.5m and 2.5m respectively. The latter result is quite accurate due to the fact that our testbeds are not sparse distributed. Our hybrid algorithm has an average error distance of 2.66m only using a selected set of nodes, simulating a sparse distributed sensor network. All our experiments have been executed in the iMinds testbed: namely at "de Zuiderpoort". These algorithms are also deployed in two real-life environments: "De Vooruit" and "De Vijvers".

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“…The latter problem can be solved by using a centroid algorithm [4]. This is only useful if there is a set of fixed nodes with an overlapping coverage area.…”

Section: A Range-based: Weightedmentioning

confidence: 99%

A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks

Haute¹,

Rossey²,

Becue³

et al. 2014

Annals of Computer Science and Information Systems

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“…In [25] a range-free algorithm is introduced that uses centroid of a polygon to estimate the position of an un-localized node v. This polygon is constructed by connecting the coordinates of all neighboring anchor nodes of v. The work performed in [41] uses trilateral centroid with weight. However, centroid requires many anchor nodes.…”

Section: Range-free Localization Approachesmentioning

confidence: 99%

Localization in terrestrial and underwater sensor‐based m2m communication networks: architecture,classification and challenges

Karim

Mahmoud

Anpalagan

et al. 2015

Int J Communication

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Localizing machine-type communication (MTC) devices or sensors is becoming important because of the increasing popularity of machine-to-machine (M2M) communication networks for location-based applications. These include such as health monitoring, rescue operations, vehicle tracking, and wildfire monitoring. Moreover, efficient localization approaches for sensor-based MTC devices reduce the localization error and energy consumption of MTC devices. Because sensors are used as an integral part of M2M communication networks and have achieved popularity in underwater applications, research is being conducted on sensor localization in both underwater and terrestrial M2M networks. Major challenges in designing underwater localization techniques are the lack of good radio signal propagation in underwater, sensor mobility management, and ensuring network coverage in 3D underwater M2M networks. Similarly, predicting the mobility pattern of MTC devices, trading-off energy consumption and location accuracy pose great design challenges for terrestrial localization techniques. This article presents a comprehensive survey on the current state-of-the-art research on both terrestrial and underwater localization approaches for sensor-based MTC devices. It also classifies localization approaches based on several factors, identifies their limitations with potential solutions, and compares them.

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“…Generally, these techniques require additional hardware. The most common ones are received signal strength indication (RSSI) , time of arrival , time difference of arrival , and angle of arrival . Range‐free: In these techniques, the position of non‐anchor nodes is obtained through implicit information provided by anchor nodes, usually based on exchanged messages, commonly called beacons. This information normally consists of different aspects, such as radio coverage membership or the number of hops between devices.…”

Section: Wireless Sensor Network Applied To Tracking Peoplementioning

confidence: 99%

Section: Wireless Sensor Network Applied To Tracking Peoplementioning

confidence: 99%

Securing a wireless sensor network for human tracking: a review of solutions

Carrasco

Alcaraz

Barbancho

et al. 2013

Int J Communication

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SUMMARYCurrently, wireless sensor networks (WSNs) are formed by devices with limited resources and limited power energy availability. Thanks to their cost effectiveness, flexibility, and ease of deployment, wireless sensor networks have been applied to many scenarios such as industrial, civil, and military applications. For many applications, security is a primary issue, but this produces an extra energy cost. Thus, in real applications, a trade-off is required between the security level and energy consumption. This paper evaluates different security schemes applied to human tracking applications, based on a real-case scenario.

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A localization strategy based on n‐times trilateral centroid with weight

Cited by 14 publications

References 24 publications

A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks

A hybrid indoor localization solution using a generic architectural framework for sparse distributed wireless sensor networks

Localization in terrestrial and underwater sensor‐based m2m communication networks: architecture,classification and challenges

Securing a wireless sensor network for human tracking: a review of solutions

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