Landslide Risk Estimation Based on 5G Network RSSI - Oliveira, Gabriel Vanderlei de; Balieiro, Andson; Brito, Gilmar; Dantas, Jamilson (Anais do Simpósio Brasileiro de Engenharia de Sistemas Computacionais (SBESC); 2024: Anais do XIV Simpósio Brasileiro de Engenharia de Sistemas Computacionais, 2024)
Landslides are downward movements of soil, rock, and debris along slopes, and pose significant risks to communities, especially in inhabited areas as they can cause severe damage, including the destruction of infrastructure and loss of life. Solutions for prediction and mitigation strategies are crucial, which often relying on rainfall forecasting and monitoring through sensor and IoT technologies. However, such solutions can be costly and challenging to implement, particularly in developing countries. By taking advantage of 5G networks, this paper proposes an innovative Received Signal Strength Indication (RSSI)-based solution to estimate the landslide risk and assist in mitigation actions in advance. Our solution also incorporates Software-Defined Networks (SDN) to manage the collected real-time data, compute the landslide risk, and notify users in the affected area. Results show that adopting 5G RSSI can significantly improve the accuracy in detecting rains and landslides, as shown by a high Pearson correlation coefficient (0.984), a Mean Squared Error (MSE) of 0.0087, and a coefficient of determination (R 2 ) of 0.6185 for the RSSI-bases solution.