

Real-Time IoT-Based Landslide Detection and Early Warning System Using Fuzzy Logic and LoRa Communication.
Abstract
The goal of this paper is to describe an Internet of Things solution for landslide detection and alerting using the ESP32 microcontrollers, LoRa communication technology, and an Android application. The system adjusts the monitoring of environmental conditions such as soil moisture, ground shaking, pressure, and tilt angle. The intensity of rain, which is defined as the intensity of rainfall over a short duration, is also calculated because heavy and quick downpours are a major cause of landslides. The information is processed using fuzzy set theory to issue a real time warning through a web server and mobile application, and evaluate the possibility of landslide occurrences. This work illustrates the cost-effective approach possible with real time solutions in landslide risk management.
References
Rawat, P. S. Landslide Monitoring Using IoT System with Cloud Support. 2023 10th IEEE Uttar Pradesh Section International Conference.
Patel, A. Crowdsourced Landslide Reports for Enhanced Risk Assessment. Journal of Geospatial Analytics, 2022.
Mehta, R. Geospatial Analytics in IoT-Based Landslide Detection. IEEE Transactions on Geoscience, 2021.
Das, S. Multi-Sensor Fusion Techniques in Landslide Detection. International Journal of Sensor Networks, 2020.
Sharma, V. Data Preprocessing in IoT-Based Landslide Prediction. Sensors and Actuators Journal, 2019.
Joshi, T. Hybrid Fuzzy-ANN Models for Landslide Prediction. Machine Learning and Applications Journal, 2022.
Gupta, P. IoT-Based Landslide Monitoring System. International Journal of Advanced Research in Science, 2021.
Patel, M. LPWAN Technologies in Landslide Monitoring. IEEE Access, 2020.
Singh, R. Edge Computing for Real-Time Landslide Detection. Cloud Computing and Applications Journal, 2023.
Saxena, K. CNN-Based Landslide Detection Models. Neural Networks and AI Journal, 2022.
Refbacks
- There are currently no refbacks.