IoT technology and big data processing for monitoring and analysing land subsidence in Central Taiwan

Abstract

Over 1992-2018, groundwater overexploitation had caused large-scale land subsidence in the Choshui River Alluvial Fan (CRAF) in Taiwan. The Taiwan High Speed Railway (THSR) passes through an area of severe subsidence in CRAF, and the subsidence poses a serious threat to its operation. How to effectively monitor land subsidence here has become a major issue in Taiwan. In this paper, we introduce a multiple-sensor monitoring system for land subsidence, including 50 continuous operation reference stations (CORS), multi temporal InSAR (MT-InSAR), a 1000 km levelling network, 34 multi-layer compaction monitoring wells and 116 groundwater monitoring wells. This system can monitor the extent of land subsidence and provide data for studying the mechanism of land subsidence. We use the Internet of Things (IoT) technology to control and manage the sensors and develop a bigdata processing procedure to analyse the monitoring data for the system of sensors. The procedure makes the land subsidence monitoring more efficient and intelligent.