Sensors | |
Real-Time Identification of Irrigation Water Pollution Sources and Pathways with a Wireless Sensor Network and Blockchain Framework | |
Chiao-Ming Lin1  Hussnain Mukhtar1  Yu-Pin Lin1  Joy R. Petway1  Kuan-Ting Huang1  Shih-Wei Liao2  Cheng-Fu Chou2  | |
[1] Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan;Department of Computer Sciences and Engineering, National Taiwan University, Taipei 10617, Taiwan; | |
关键词: Internet of Things; pollution source trace; blockchain; GIS; pollution pathway; wireless sensor network; | |
DOI : 10.3390/s20133634 | |
来源: DOAJ |
【 摘 要 】
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.
【 授权许可】
Unknown