Data Collection in Wireless Sensor Networks Using UAV and Compressive Data Gathering

Wireless sensor networks can be used in wind farm monitoring where periodic data collection about the sound generated inside the farm as well as detection and monitoring of faulty wind turbines is necessary. Periodic sound data collection requires reliability while faults detection necessitates timeliness. Simultaneous data gathering and faults monitoring was not well studied in literature. This paper proposed a system model that worked on homogeneous data gathering Wireless sensor networks deployed in wind farms. When a wind turbine became faulty, a cluster with a different transmission channel around that wind turbine was formed and both periodic sound data gathering and faults monitoring were performed at the same time. The proposed model had a novel routing strategy with a built-in congestion control technique to provide timely delivery of faults data. Experimental results show that the proposed method performed better than known similar techniques in terms of reliable data gathering and reliable timely faults monitoring. Due to lower number of high power transmissions, the proposed method had 8% to 17% higher success rate of regular system and 94% of accuracy at the fault monitoring. In terms of timely faults detection and notification, this method had a comparative performance to the existing methods. DOI: http://dx.doi.org/10.3329/jbau.v11i2.19936 J. Bangladesh Agril. Univ. 11(2): 321-330, 2013

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Monitoring Passive Wireless Devices

10.21203/rs.3.rs-488167/v1 ◽

2021 ◽

Author(s):

Zohar Naor

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Data Collection ◽

Data Gathering ◽

Geographic Area ◽

Sensor Nodes ◽

Wireless Sensor ◽

Wireless Devices ◽

Iot Devices ◽

Passive Rfid

Abstract This study suggests using a user-initiated detecting and data gathering from power-limited and even passive wireless devices, such as passive RFID tags, wireless sensor networks (WSNs), and Internet of Things (IoT) devices, that either power limitation or poor cellular coverage prevents them from communicating directly with wireless networks. While previous studies focused on sensors that continuously transmit their data, the focus of this study is on passive devices. The key idea is that instead of receiving the data transmitted by the sensor nodes, an external device (a reader), such as an unnamed aerial vehicle (UAV), or a smartphone is used to detect IoT devices and read the data stored in the sensor nodes, and then to deliver it to the cloud, in which it is stored and processed. While previous studies on UAV-aided data collection from WSNs focused on the UAV path planning, the focus of this study is on the rate at which the passive sensor nodes should be polled. That is, to find the minimal monitoring rate that still guarantees accurate and reliable data collection. The proposed scheme enables us to deploy wireless sensor networks over a large geographic area (e.g., for agricultural applications), in which the cellular coverage is very poor if any. Furthermore, the usage of initiated data collection can enable the deployment of passive WSNs. Thus, can significantly reduce both the operational cost, as well as the deployment cost, of the WSN.

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An Energy Efficient Data Gathering in Dense Mobile Wireless Sensor Networks

ISRN Sensor Networks ◽

10.1155/2014/518268 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 9

Author(s):

R. Velmani ◽

B. Kaarthick

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Data Collection ◽

Cluster Formation ◽

Cluster Head ◽

Data Gathering ◽

Wireless Sensor ◽

End To End Delay ◽

End To End

Amidst of the growing impact of wireless sensor networks (WSNs) on real world applications, numerous schemes have been proposed for collecting data on multipath routing, tree, clustering, and cluster tree. Effectiveness of WSNs only depends on the data collection schemes. Existing methods cannot provide a guaranteed reliable network about mobility, traffic, and end-to-end connection, respectively. To mitigate such kind of problems, a simple and effective scheme is proposed, which is named as cluster independent data collection tree (CIDT). After the cluster head election and cluster formation, CIDT constructs a data collection tree (DCT) based on the cluster head location. In DCT, data collection node (DCN) does not participate in sensing, which is simply collecting the data packet from the cluster head and delivering it into sink. CIDT minimizes the energy exploitation, end-to-end delay and traffic of cluster head due to transfer of data with DCT. CIDT provides less complexity involved in creating a tree structure, which maintains the energy consumption of cluster head that helps to reduce the frequent cluster formation and maintain a cluster for considerable amount of time. The simulation results show that CIDT provides better QoS in terms of energy consumption, throughput, end-to-end delay, and network lifetime for mobility-based WSNs.

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