The system, being installed by the Amrita Vishwa Vidyapeetham, ranked India's eight best university by the ministry of union human resource development's National Institute Ranking Framework for 2018 -- and co-funded by the ministry of earth sciences, targets the Sikkim-Darjeeling belt, which is among the world's most prominent "landslide hotspots".
The new IoT (Internet of Things) system for landslides, that is being put in place, is custom developed for Himalayan geology, said Maneesha Sudheer, Director, Center for Wireless Networks and Applications, Amrita Vishwa Vidyapeetham.
Sudheer, Awho spearheads landslide research at the university, said the system consists of over 200 sensors which can measure geophysical and hydrological parameters like rainfall, pore pressure and seismic activity.
"It will monitor a densely populated area spanning 150 acres around the Chandmari village in Sikkim's Gangtok area. This area has seen landslides in the past, the first one being reported in 1997," she said.
The system collects real-time, continuous data from the sensors, performs basic analysis at the Field Management Center (FMC) located on the site in Sikkim, and relays it to the Data Management Center (DMC) at the university centre in Kerala's Kollam district.
"The university researchers are using the data to characterise and learn the geological and hydrological nature and response of the hill with respect to the dynamic and real-time meterological variations to develop the Landslide Early Warning Model for that area," she said.
To improve the system's reliability and enhance the early warning duration, a three-level Landslide Early Warning Model has been developed.
The first level, based on rainfall threshold, has successfully completed the testing phase and is ready to go live and issue alerts for potential landslides at the state level.
In the second level, the system would generate a Factor of Safety (FOS) value for various points on the hill in real-time that will provide a more specific warning for the Chandmari region based on the rainfall, moisture and pore pressure sensor data from the field.
In the third level, the system would use data derived from the movement and vibrational sensors to issue landslide detection warning, she pointed out.
"This multi-level warning system will help disaster management authorities to take steps to mitigate and manage potential landslide threats in a proactive and effective manner", she said.
As part of the project, Several Acommunity engagement programs have been performed to disseminate knowledge regarding the impact of the landslides, the working of the proposed warning system and its capability to warn about imminent landslides," she said.
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