Real Time Landslide Monitoring System Research Articles

Energy efficient wireless sensor network with efficient data handling for real time landslide monitoring system using fuzzy data mining technique

Energy efficient wireless sensor network with efficient data handling for real time landslide monitoring system using fuzzy data mining technique

Energy efficient wireless sensor network with efficient data handling for real time landslide monitoring system using fuzzy data mining technique

Wireless sensor network (WSN) is one of the emerging areas which are extensively being used for development of real time monitoring systems. Landslides are the major cause of loss of life, human settlements, agriculture, forestland, and lead to damage of communication routes. In this paper, we propose new landslide monitoring system with maximising the life time of sensor nodes by avoiding link failure in routing protocol. The cluster-based routing protocol with the sensor nodes is capable of data acquisition, data storage, data processing, and wireless data transmission. Then, collected data's are aggregated using fuzzy data mining technique which maximise lifetime of all sensor nodes in the network area. The proposed approach is implemented and results are obtained through NS-2 simulation shows that the proposed algorithm performs better than other landslide monitoring systems in terms of network life time, sensor node life time, data transmission and energy consumption.

A community-based disaster risk reduction system in Wanzhou, China

A series of disaster risk reduction (DRR) programs were carried out in landslide-prone areas in the Three Gorges Reservoir (TGR) to improve community resilience. The Wanzhou District in the TGR was selected as a case to introduce the community-based DRR (CBDRR) system. The system is community-based and government-led with the assistance of experts, police, Red Cross, etc. It involves risk investigation, education and training, landslide monitoring, information analysis, early warning system and emergency response. The landslide mechanism and element at risk were ascertained after detailed field investigation. Based on investigation, a characterized education and training to local residents was carried out. The local residents living on landslides carried out the community-based landslide monitoring. Some simple but effective monitoring methods were applied, such as steel piles, mosaic, convergence meters and smart phone, which are widely used in community-based landslide monitoring. To comprehensively understand the landslide and the data monitored by local residents, a real-time landslide monitoring system was established on several typical landslides. At last, a successful landslide emergency response was introduced to well explain the early warning system and emergency response. After carrying out the CBDRR for a decade, the landslide resilience has enhanced and the local residents are more relieved to live on landslides.