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Open AccessArticle

Real-Time Identification of Irrigation Water Pollution Sources and Pathways with a Wireless Sensor Network and Blockchain Framework

1
Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan
2
Department of Computer Sciences and Engineering, National Taiwan University, Taipei 10617, Taiwan
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(13), 3634; https://doi.org/10.3390/s20133634
Received: 25 May 2020 / Revised: 13 June 2020 / Accepted: 19 June 2020 / Published: 28 June 2020
(This article belongs to the Special Issue Wireless Sensor Networks for Water and Environmental Monitoring)
Real-time identification of irrigation water pollution sources and pathways (PSP) is crucial to ensure both environmental and food safety. This study uses an integrated framework based on the Internet of Things (IoT) and the blockchain technology that incorporates a directed acyclic graph (DAG)-configured wireless sensor network (WSN), and GIS tools for real-time water pollution source tracing. Water quality sensors were installed at monitoring stations in irrigation channel systems within the study area. Irrigation water quality data were delivered to databases via the WSN and IoT technologies. Blockchain and GIS tools were used to trace pollution at mapped irrigation units and to spatially identify upstream polluted units at irrigation intakes. A Water Quality Analysis Simulation Program (WASP) model was then used to simulate water quality by using backward propagation and identify potential pollution sources. We applied a “backward pollution source tracing” (BPST) process to successfully and rapidly identify electrical conductivity (EC) and copper (Cu2+) polluted sources and pathways in upstream irrigation water. With the BPST process, the WASP model effectively simulated EC and Cu2+ concentration data to identify likely EC and Cu2+ pollution sources. The study framework is the first application of blockchain technology for effective real-time water quality monitoring and rapid multiple PSPs identification. The pollution event data associated with the PSP are immutable. View Full-Text
Keywords: Internet of Things; pollution source trace; blockchain; GIS; pollution pathway; wireless sensor network Internet of Things; pollution source trace; blockchain; GIS; pollution pathway; wireless sensor network
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MDPI and ACS Style

Lin, Y.-P.; Mukhtar, H.; Huang, K.-T.; Petway, J.R.; Lin, C.-M.; Chou, C.-F.; Liao, S.-W. Real-Time Identification of Irrigation Water Pollution Sources and Pathways with a Wireless Sensor Network and Blockchain Framework. Sensors 2020, 20, 3634.

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