Enhancing Disaster Preparedness in Mountainous Regions: A Review of IoT and Machine Learning Techniques

Abstract

This paper presents an extensive examination of contemporary methodologies, encompassing the integration of sensor networks within the framework of the Internet of Things (IoT) and the utilization of diverse machine learning (ML) techniques, including both statistical and image processing methodologies. These innovative approaches are employed with the specific aim of enhancing hazard preparedness and establishing early warning systems for catastrophic events, such as earthquakes and landslides, in the mountainous regions of India. The study places a significant emphasis on a comprehensive review of prior research endeavors, which collectively contribute to the progressive advancement of the field of geotechnical engineering. By exploring this interdisciplinary terrain, the research endeavors to bridge the gap between traditional geotechnical engineering and the cutting-edge application of IoT and machine learning methods. This comprehensive review holds substantial potential for prospective engineers and policymakers, offering valuable insights and guidance. The objective is to support the pursuit of the United Nations’ Sustainable Development Goals (SDGs), ultimately fostering a secure and sustainable societal development trajectory. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.