A Comparative Study of Target Tracking Approaches in Wireless Sensor Networks

Ez-Zaidi, Asmaa; Rakrak, Said

doi:10.1155/2016/3270659

Cited by 38 publications

(32 citation statements)

References 44 publications

(47 reference statements)

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“…Conte et al studied on how to track underwater targets [16], Asmaa et al introduced target tracking in wireless sensor networks [17]. Moreover, there are other studies about target tracking, such as underwater passive target tracking [18], target tracking with range-only information [19], target tracking using interactive multiple model [20], target tracking utilizing underwater wireless sensor networks [21], multi-target tracking with multi-bernoulli filter [22].…”

Section: Related Workmentioning

confidence: 99%

A novel fast target tracking method for UAV aerial image

2017

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Unmanned aerial vehicles (UAV) are able to achieve autonomous flight without drivers, and UAV has been a key tool to extract space data. Therefore, how to detect the trajectories of targets from UAV aerial image sequences is of great importance. Because local features are suitable to detect target tracking, we exploit scaleinvariant feature transform (SIFT) features to describe the interesting keypoints of targets. The main innovation of this paper is to utilize Multiple hypothesis tracking (MHT) algorithm to track an object (target) in a series of image sequences. Particularly, we develop a MHT framework based on a multidimensional assignment formulation and a sliding time window policy. To obtain target tracking from UAV aerial image sequences, three steps should be done, that is, 1) Breaking each track set into tracklet at a specific time, 2) Estimating the association cost of each track set, 3) Merging trajectory fragments to a longer one iteratively. Finally, we collect several UAV aerial image sequences with different target density to construct a dataset, and experimental results demonstrate the effectiveness of the proposed algorithm.

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Section: Related Workmentioning

confidence: 99%

A novel fast target tracking method for UAV aerial image

2017

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“…There has been abundant researches on detecting and tracking single or multiple targets in sensor network [1] [3]. Recently, some researchers have begun to analyse detection and monitoring of continuous objects such as forest fires, mud flows, bio-chemical material diffusion and oil spills [2].…”

Section: Related Workmentioning

confidence: 99%

“…These sensor nodes situated in the surroundings of the sink node are subject to rapid energy consumption due to additional traffic load. Sensor nodes generally are battery powered and have limited, non-renewable energy capacity [3]. Consequently, such nodes deplete their battery power completely and create holes in the network.…”

Section: Introductionmentioning

confidence: 99%

A Twofold Sink Based Data Collection for Continuous Object Tracking in Wireless Sensor Network

Sh¹,

A²,

Ma³

et al. 2017

Preprint

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SUMMARYContinuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object's movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

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“…A wireless sensor network (WSN) is composed of hundreds of sensor nodes that are distributed over a large area to monitor and track physical phenomenon like humidity, temperature, sound and so forth. WSNs have a wide range of applications such as traffic monitoring [1], patient healthcare monitoring [2], target tracking [3], indoor living monitoring [4], localization [5], and many other interesting applications.…”

Section: Introductionmentioning

confidence: 99%

Mobility for an Optimal Data Collection in Wireless Sensor Networks

Ez-Zaidi¹,

Rakrak²

2017

ijacsa

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Abstract-Sensor nodes located in the vicinity of a static sink drain rapidly their batteries since they have to carry more traffic burden. This situation results in network partition, holes as well as data losses. To mitigate this issue, many research proposed the use of mobile sink in data collection as a potential solution. However, due to its speed, the mobile sink has very short communication time to pick up all data from the sensor nodes within the network, therefore the sink is forced to return back to gather the remaining data. In this paper, we propose a new data collection scheme that aims to decrease the latency and enlarge the staying time between the mobile sink and the meeting points that buffer data originated from the other sensor nodes. We have also handled the case of urgent data so that they can be delivered without any delay. Our proposed scheme is validated via extensive simulations using NS2 simulator. Our approach significantly decreases the latency and prolongs the contact time between the mobile sink and sensor nodes.

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A Comparative Study of Target Tracking Approaches in Wireless Sensor Networks

Cited by 38 publications

References 44 publications

A novel fast target tracking method for UAV aerial image

A novel fast target tracking method for UAV aerial image

A Twofold Sink Based Data Collection for Continuous Object Tracking in Wireless Sensor Network

Mobility for an Optimal Data Collection in Wireless Sensor Networks

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