Underwater wireless sensor network for tracking ships approaching harbor

Rao, Madhuri; Kamila, Narendra Kumar; Kumar, Kulamala Vinod

doi:10.1109/scopes.2016.7955771

Cited by 9 publications

(7 citation statements)

References 7 publications

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“…Much research and industrial effort has been dedicated to deep-sea applications, e.g., Reference [58]; yet relatively little effort has been spent on shallow-water sceneries such as coastal and in-shore environmental monitoring and disaster management at depths of normally double digits or at most a few hundred meters. Among existing applications are the investigation of sub-mesoscale eddies with miniature underwater robots in Reference [47], ship tracking with an underwater sensor system in harbors [55], and a low-cost underwater sensor node called HydroNode [54]. Recently, the EU-funded research projects SUNRISE [53] and SUNSET [39] have contributed to the development of an Internet of Underwater Things (IoUT).…”

Section: Applicationsmentioning

confidence: 99%

“…Wireless networked sensing has already conquered many application domains over the past two decades and is currently extending to the field of inshore and coastal underwater monitoring and control. Starting from stationary underwater sensor networks [17,32,39,45,54,55], a recent focus on co-operative, autonomous, mobile underwater robot swarms [20,30,36,47,60,61] has evolved in both academia and industry. Novel miniature mobile underwater robots with lengths well below 1 m and a unit cost between some hundred and a few thousand dollars have become available [30,34,48,59].…”

Section: Introductionmentioning

confidence: 99%

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ahoi

Renner

Heitmann

Steinmetz

2020

ACM Trans. Sen. Netw.

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The recent development of small, cheap AUVs enables a plethora of underwater near-and inshore applications. Among these are monitoring of wind parks, detection of pollution sources, water-quality inspection, and the support of divers during disaster management. These tasks profit from online reporting, control, and AUV swarm interaction; yet they require underwater communication. Unfortunately, commercial devices are prohibitively expensive and typically closed-source, hampering their application in affordable products and research. Therefore, we developed the open-source 1 ahoi acoustic modem. It is (i) small enough to be carried by micro AUVs, (ii) consumes little enough energy to not diminish operation times of its host, (iii) comes at an attractive unit cost below $600, (iv) can reliably communicate at distances of 150 m and more, and (v) supports ranging without additional hardware. Due to its modular build, the modem can be customized and is suitable as research platform to analyze, e.g., MAC and routing protocols. We conducted extensive real-world studies and present results of communication range, packet reception rate, ranging accuracy, and efficient and reliable self-localization. Finally, we draw conclusions regarding acoustic communication, ranging, and localization with inexpensive and low-power devices that go beyond a particular device. Our study, hence, encompasses general insights, observations, and recommendations.

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Section: Applicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

ahoi

Renner

Heitmann

Steinmetz

2020

ACM Trans. Sen. Netw.

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“…Tracking of the wave patterns generated by ships could help in tracking pirates and militants, for reporting and raising alarms. An initial model of how harbor surveillance can be made more effective with WSN was proposed by Rao et al [12]. Existing monitoring and tracking system can be enhanced in much better way, as currently satellite and radar is the most used and available commercial method of monitoring and tracking on sea.…”

Section: Related Workmentioning

confidence: 99%

“…By choosing to sleep on alternate cycles, the relay nodes save energy allowing the extension of their lifetime, and thereby contributing to the whole lifetime of the network. The existing approach consumes valuable node energy and shortens the network lifetime, however the proposed approach of 12 Wave generated by two pirate boats moving parallel to each other. a Wave pattern generated by two pirates boats moving parallely to each other at time t -1. b Wave pattern generated by two pirates boats moving parallely to each other at time t alternate duty cycles for relay nodes brings elongated network lifetime, as nodes will live longer.…”

Section: Performance Analysismentioning

confidence: 99%

Tracking intruder ship in wireless environment

Rao

Kamila

2017

Hum. Cent. Comput. Inf. Sci.

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BackgroundObject tracking is one of the most practical applications of WSN. Wireless network is itself vulnerable and when combined with sensors the other errors that add upon to it are sensor failures, localization errors, prediction, and detection errors. Robust and effective solutions that could recover the information of tracking object are required for making wireless sensor networks more acceptable. Efficient energy management and enhanced network lifetime are other desired design aspects of a wireless sensor network application. Rout and Ghosh [1] tackle the problem of the area around the sink node that is a bottleneck zone as more activity is reported there, causing improper load balance that affects the overall network lifetime. They attempted to solve this problem by proposing a duty cycled wireless sensor network. The sensor nodes in the bottleneck zone are divided into two groups in their approach: simple relay sensors and network coder sensors. While the relay nodes simply forward the received data, the network coder nodes transmit using a network coding based algorithm. Energy efficiency of the bottleneck zone hence increases as more volume of data will be transmitted to the Sink with the same number of transmissions. Park and Shi [2] suggest strategies of deploying additional sensors in the bottleneck zone in due course of time to maintain a desired level of network connectivity. The major concerns of WSNs are studied by Mohsin [3] who also Abstract It is a challenging task for all Harbors or Naval Administration to restrict and monitor the movement of defense or commercial ships. Most commonly used techniques of monitoring are radars and satellite images. These techniques are not reliable as radars can be turned off voluntarily and receptions of images are affected by adverse climatic conditions. This paper proposes a reliable ship intruder detection algorithm that classifies different types of objects approaching the model system in and out of phase with the ocean waves. The proposed technique also takes care of superimposition of temporal and spatial values of nodes that are presumably deployed in the sea surface up to a certain distance. Simulation results prove that the proposed algorithm detects and classifies objects efficiently even when 50% of the nodes reporting the tracking phenomenon are tampered. Rao and Kamila Hum. Cent. Comput. Inf. Sci. (2017) Comput. Inf. Sci. (2017) 7:14 survey the performance tradeoffs in terms of energy, tracking error and other performance metrics of the available sensors in established network architectures. Tracking and monitoring techniques need to be designed by taking account of these parameters. A simple and efficient tracking system based on Oriented FAST and Rotated BRIEF (ORB) is presented by Wu et al. [4]. It is a fast binary descriptor where good matched points are obtained by computing Hamming distance. Based on the matched points and temporal-spatial constraint, location of the object in new frame is obtained. Tracking applications of wire...

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“…Many wireless sensor network based underwater applications have been proposed. For instance, in [105], the authors propose a paradigm for tracking objects (like trespassing ships approaching a harbor) and monitoring the activities on the ocean surfaces; in [106], the mobile ad hoc network is used for the underwater plumes detection, inspection, and traction; in [107], the underwater WSN is used in the offshore oil field comprising; in [108], the underwater WSN is used for the submarine detection; in [109], the authors use the underwater WSN and underwater robotics to track the underwater targets; in [110], the authors introduce the WSN into the underwater localization scheme with the assists of the underwater vehicles. Not only in the underwater environment but also in the remote sensing, the WSN is applied widely.…”

Section: Underwater Wireless Sensor Network (Uwsn)mentioning

confidence: 99%

Contributions to robotic underwater perception and mapping based navigation

Yuan¹

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XVIII partial SSS image pairs where contains landmark pairs 1 and 2 ………… 5.1 A robot measuring relative observations to environmental landmarks……... 5.2 The flowchart of the SLAM process………………………………………... 5.3 The SLAM graphical model, redrawn after [123]………………………….. 5.4 (a) Before closing the loop; (b) After closing the loop……………………... 5.5 The AEKF estimator………………………………………………………... 5.6 The flow chart of SLAM procedure based on an AEKF…………………… 5.7 The architecture of AEKF-SLAM based robotic navigation system, as in [9]…………………………………………………………………………… 5.8 The robot motion model…………………………………………………….. 5.9 The robot observation model……………………………………………….. 6.1 The robot is observing the landmarks A and B in the AEKF-SLAM dense loop map; (b) The robot is getting measurements A and B in the FastSLAM 2.0 dense loop map………………………………………………………….. 6.2 (a) Partial magnification of the AEKF-SLAM line map; (b) Partial magnification of the FastSLAM 2.0 line map………………………………. 6.3 (a) The robot is observing the centroids of certain parts of the body before loop closure; (b) The final AEKF-SLAM loop map where the landmarks are detected by the improved Otsu TSM……………………………………. 6.4 (a) The robot is observing the centroids of certain parts of the body before loop closure; (b) The final AEKF-SLAM loop map where the landmarks are detected by the maximum entropy TSM………………………………... 6.5 The simulated SWARMs vehicles………………………………………….. 6.6 Link all the actors for landmark localization and seabed mapping in the SWARMs project…………………………………………………………… XIX

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Underwater wireless sensor network for tracking ships approaching harbor

Cited by 9 publications

References 7 publications

ahoi

ahoi

Tracking intruder ship in wireless environment

Contributions to robotic underwater perception and mapping based navigation

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