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Sensors 2018, 18(6), 1732; https://doi.org/10.3390/s18061732

Design of Compressed Sensing Algorithm for Coal Mine IoT Moving Measurement Data Based on a Multi-Hop Network and Total Variation

1
The National Joint Engineering Laboratory of Internet Applied Technology of Mines, Xuzhou 221000, China
2
IOT Perception Mine Research Center, China University of Mining and Technology, Xuzhou 221000, China
*
Author to whom correspondence should be addressed.
Received: 28 April 2018 / Revised: 23 May 2018 / Accepted: 25 May 2018 / Published: 28 May 2018
(This article belongs to the Special Issue Data and Information Fusion for Wireless Sensor Networks)
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Abstract

As the application of a coal mine Internet of Things (IoT), mobile measurement devices, such as intelligent mine lamps, cause moving measurement data to be increased. How to transmit these large amounts of mobile measurement data effectively has become an urgent problem. This paper presents a compressed sensing algorithm for the large amount of coal mine IoT moving measurement data based on a multi-hop network and total variation. By taking gas data in mobile measurement data as an example, two network models for the transmission of gas data flow, namely single-hop and multi-hop transmission modes, are investigated in depth, and a gas data compressed sensing collection model is built based on a multi-hop network. To utilize the sparse characteristics of gas data, the concept of total variation is introduced and a high-efficiency gas data compression and reconstruction method based on Total Variation Sparsity based on Multi-Hop (TVS-MH) is proposed. According to the simulation results, by using the proposed method, the moving measurement data flow from an underground distributed mobile network can be acquired and transmitted efficiently. View Full-Text
Keywords: compressed sensing; moving measurement data; multi-hop network; total variation; coal mine compressed sensing; moving measurement data; multi-hop network; total variation; coal mine
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Wang, G.; Zhao, Z.; Ning, Y. Design of Compressed Sensing Algorithm for Coal Mine IoT Moving Measurement Data Based on a Multi-Hop Network and Total Variation. Sensors 2018, 18, 1732.

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