Implementation of Composite LPWAN on the Slope Disaster Prevention Monitoring System

Following the integration of the Internet of Things (IoT) in daily life and the vigorous development of lowpower wide-area networks, IoT applications have gradually matured in various fields. Safety concerns cannot be overlooked in the construction of smart cities (direct buildings). This study focused on the aspects of disaster prevention (indirect care) and established a disaster prevention andmonitoring system to ensure the safety of pedestrians. Disaster prevention in slope areas is a crucial topic in Taiwan because of numerous slopes in mountainous regions. Adequate monitoring equipment was installed on the basis of principles in protection structure construction to display quantitative data of rockfall disasters. A disaster prevention and monitoring system for rockfall was established to estimate the scale and severity of disasters. Furthermore, maintenance indicators for the monitoring system and protection structure constructionwere established, andmanagement thresholds for disaster severitywere formulated according to the onsite disaster situation. In this study, one alarm is issued on the experimental day and it is detected by node C with a value of 26.5 degrees (vertical bar 26.5 degrees-22.18 degrees vertical bar >1 degrees), judging that the warning value is reached. And the measured value is within the measuring range, an alarmmessage is issued via mail to management personnel and government and import the alarm value on the monitoring page for the public to check.

Automated summary

With the development of IoT and the implementation of low-power wide-area networks, disaster prevention and monitoring have become crucial in the construction of smart cities. This study focuses on establishing a system to ensure pedestrian safety, particularly in slope areas in Taiwan. Monitoring equipment is installed based on protection structure principles to provide quantitative data on rockfall disasters. The study also establishes maintenance indicators and management thresholds for disaster severity.