Real-time identification of irrigation water pollution sources and pathways with a wireless sensor network and blockchain framework
Journal
Sensors (Switzerland)
Journal Volume
20
Journal Issue
13
Pages
1-22
Date Issued
2020
Author(s)
Mukhtar, Hussnain
Huang, Kuan-Ting
Petway, Joy R.
Lin, Chiao-Ming
Abstract
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. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Subjects
Blockchain; GIS; Internet of Things; Pollution pathway; Pollution source trace; Wireless sensor network
SDGs
Other Subjects
Blockchain; Directed graphs; Internet of things; Irrigation; Oil spills; Water quality; Wireless sensor networks; Directed acyclic graph (DAG); Electrical conductivity; Internet of thing (IOT); Irrigation water quality; Real-time identification; Water quality analysis simulation program; Water quality monitoring; Water quality sensors; Water pollution
Type
journal article