Conference Papers
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Item Enhancing Disaster Preparedness in Mountainous Regions: A Review of IoT and Machine Learning Techniques(Springer Science and Business Media Deutschland GmbH, 2025) Varun Menon, O.; Kolathayar, S.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.Item Site-Specific Probabilistic Seismic Hazard Assessment of the New Indian Parliament Building Site in Delhi(Springer Science and Business Media Deutschland GmbH, 2025) Varma, N.; Kundu, P.; Kolathayar, S.Earthquakes are a significant geological hazard that causes destruction to life and property. A timely and thorough seismic hazard assessment of regions of national importance is necessary to ensure public safety. Delhi, the national capital of India, is classified as Zone IV in seismic zoning. A comprehensive probabilistic seismic hazard assessment (PSHA) was conducted to determine the seismic hazard at the site of the newly constructed Parliament building in New Delhi, focusing on seismically active faults in the area. The building was designed to withstand heavy earthquake loads, but the data used for its construction was based on older analytics. This study bridges that gap by using recent earthquake data. A catalogue completeness analysis was performed on homogenised and declustered earthquake data, and the area was divided into six subzones to calculate seismicity parameters for each source. Region-specific ground motion was evaluated using an attenuation relationship developed for North Indian states. The ground motion prediction equation (GMPE) specific to the region was integrated into the model to determine probabilistic seismic susceptibility. Peak ground acceleration (PGA) at the bedrock level was calculated for 2 and 10% probability of exceedance over a fifty-year period, and uniform hazard response spectra were determined for the site. The results show bedrock PGA values of 0.31 g and 0.14 g at 2% and at 10% exceedance probability over 50-years. These values are slightly higher than those found in previous studies of the region, indicating an increased seismic susceptibility. This study concludes that the region is susceptible to seismic activity, with an increase in bedrock PGA potentially leading to higher surface-level PGA. Further studies and geotechnical investigations are recommended to fully assess surface-level hazards. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.