Self-organizing ad-hoc robotic sensor networks based on locally communicative interactions

Tatara, Kazutaka; Lee, Geun-Ho; Chong, Nak Young

doi:10.1109/urai.2011.6145868

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…If the processing layer is connected to the Internet and the sensing layer transmits data in a wireless way, then the base stations or the WiFi access points play the roles of the physical infrastructures. In some of the solutions where ad-hoc is used to aggregate sensing data [11], the sensing 6 devices could also play the roles of the transmission infrastructures. In our implementation, the amount of each time's transmitted data is small, and a certain amount of latency is tolerable.…”

Section: B Transmission Layermentioning

confidence: 99%

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UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

Bai

Yang

et al. 2019

IEEE Network

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As air pollution is becoming the largest environmental health risk, the monitoring of air quality has drawn much attention in both theoretical studies and practical implementations. In this article, we present a real-time, fine-grained and power-efficient air quality monitoring system based on aerial and ground sensing. The architecture of this system consists of four layers: the sensing layer to collect data, the transmission layer to enable bidirectional communications, the processing layer to analyze and process the data, and the presentation layer to provide graphic interface for users. Three major techniques are investigated in our implementation, given by the data processing, the deployment strategy and the power control. For data processing, spacial fitting and short-term prediction are performed to eliminate the influences of the incomplete measurement and the latency of data uploading. The deployment strategies of ground sensing and aerial sensing are investigated to improve the quality of the collected data. The power control is further considered to balance between power consumption and data accuracy. Our implementation has been deployed in Peking University and Xidian University since February 2018, and has collected about 100 thousand effective data samples by June 2018.

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Section: B Transmission Layermentioning

confidence: 99%

“…An illustration of the short-term prediction in the processing layer, with (a) (b) (c) (d) for 2D predicting and (e) (f) (g) (h) for 3D predicting. 11…”

Section: Short-term Predictionmentioning

confidence: 99%

UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

Bai

Yang

et al. 2019

IEEE Network

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“…Finally, the control room receives the data from the sink node, which maintains contact with the situation, thus allowing first responders to be sent to the infected area, the steps that nodes reported the situation in real time through multiple hops. K Tatara et al 13 propose a decentralized solution to handle with the self-organization problem in many applications composed of a multitude of autonomous robotic sensors. This decentralized solution allows each robot to build and maintain the network, through local communication interactions with their neighbors, allowing robots choose as neighbors those with greater connectivity, adapting to the topological changes of the network through the robot's movements.…”

Section: Related Workmentioning

confidence: 99%

“…K Tatara et al 13 propose a decentralized solution to handle with the self-organization problem in many applications composed of a multitude of autonomous robotic sensors. This decentralized solution allows each robot to build and maintain the network, through local communication interactions with their neighbors, allowing robots choose as neighbors those with greater connectivity, adapting to the topological changes of the network through the robot's movements.…”

Section: Related Workmentioning

confidence: 99%

Exploiting self-organization and fault tolerance in wireless sensor networks: A case study on wildfire detection application

Giuntini

Beder

Ueyama

2017

International Journal of Distributed Sensor Networks

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The wildfires caused by human occupation is one of the factors that most contributes to deforestation of conservation areas, resulting in a number of issues for ecological systems. Premature fire detections lead to the elimination or reduction of the damage that will be caused by a fire incident. Wireless sensor networks have been shown to be a good alternative for environmental monitoring applications, as they can collect and send information in real time, such as humidity, wind, and temperature of various parts of the forest. Due to problems such as power limitation, communication failure, and loss of nodes, the network topology is constantly changing, requiring mechanisms to achieve self-organization and fault tolerance. This article proposes the development of a model and application in self-organizing and fault-tolerant wireless sensor networks for fire detection in conservation areas. To achieve self-organization and fault tolerance, we rely on encouraged local interactions between neighboring nodes that monitor the same region and the coordination of tasks, through a supervisor node, equipped with a framework for developing component-based fault-tolerant applications. For the analysis and validation of both model and application, it was simulated 60 events in the network of sensors in a real scenario using the simulator Sinalgo. The results were classified as True (partial or absolute) or False (partial or absolute). In all, 45% of consensus identified a possible fault in the application and in only 35% there was absolute consensus.

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Wave-propagation management in indoor environments using micro-radio-repeater systems

Oh¹,

Thiel²,

Sarabandi³

2014

IEEE Antennas Propag. Mag.

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Self-organizing ad-hoc robotic sensor networks based on locally communicative interactions

Cited by 4 publications

References 12 publications

UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

Exploiting self-organization and fault tolerance in wireless sensor networks: A case study on wildfire detection application

Wave-propagation management in indoor environments using micro-radio-repeater systems

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