SAFEHARBOR: A SMART IOT LANDSLIDE PRECAUTIONARY SYSTEM FOR ENHANCED COMMUNITY SAFETY

Abstract

A landslide poses a signicant threat to various locations, impacting social life. The current landslide monitoring systems lack efciency,
particularly in detecting rainfall, a crucial factor in tropical countries like India with intense rainfall. This research endeavors to develop a Smart
Landslide Precautionary System for real-time and advanced landslide detection. The chosen rainfall sensor serves as a key component, providing
early alerts to individuals, considering the diverse origins of people. Employing the NODE Mcu ESP3266 microcontroller with a Multiplexer for
analog pin extension, the system is divided into Central and Remote Servers. The Remote Server integrates rainfall, vibration, and soil moisture
sensors across different locations, transmitting real-time data to the Central Server via the Blynk IoT platform. In case of sensor values surpassing
thresholds, the District Administrative Center receives alert calls through the GSM module. The ndings indicate heightened landslide
susceptibility in soil samples, with rain sensor readings reaching 85mm and soil moisture sensor readings hitting 35%. The proposed system offers
enhanced accuracy for users to monitor and respond to landslide-triggering conditions effectively, showcasing a proactive approach to community
safety.