Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Hybrid intelligent bayesian model for analyzing spatial data(Springer Verlag service@springer.de, 2018) Velmurugan, J.; Venkatesan, M.Spatial data mining refers to the extraction of Geo Spatial Knowledge, maintaining their spatial relationships, along with other interesting patterns not explicitly stored in spatial datasets. The overall objective of this research work is to apply GIS based data mining classification modeling techniques to assess the spatial landslide risk analysis in Nilgris district, Tamilnadu, India. Landslide is one of the most important hazards that affect different parts of India in the every year. Landslides cover broad range impact on the people of the affected area in terms of the devastation caused to material and human resources. Landslide is generated by various factors such as rainfall, soil, slope, land use and land covers, geology, etc. Each landslide factor has a different level of values. The ranking of values and assignment of weight to the landslide factor gives good classification of landslide risk level. Data science and soft computing play major role in landslide risk analysis. The rank and weight are assigned to the landslide factor and its different levels using classification data science techniques. In this paper, we proposed a new model with integration of rough set and Bayesian classification called Hybrid Intelligent Bayesian Model (HIBM) to analyze the possibilities of various landslide risk level. The proposed model is compared with real-time data, and performance is validated with other data science models. © 2018, Springer Nature Singapore Pte Ltd.Item Geohazard Investigation and Management: An Introduction(Springer Science and Business Media Deutschland GmbH, 2022) Adhikari, B.R.; Menon, V.; Kolathayar, S.The understanding of the systemic risk posed by multi-hazard is becoming a new area of research and adopted by the different global and national frameworks. This chapter summarizes the contents of the book titled geohazard mitigations, which contains thirty-eight chapters. These chapters are divided into three sections namely: multi-hazard assessment, landslide hazard assessment and mitigation, and geotechnical engineering. This chapter also includes basic definitions and introduction to geohazard investigation and management. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Review of Experimental Studies on Rainfall-Induced Landslide Using the Laboratory Flume Technique(Springer Science and Business Media Deutschland GmbH, 2024) Menon, V.; Kolathayar, S.Rainfall-induced landslides are one of the most influential disasters in the monsoon season for rainfall-rich parts of India, primarily southern and northeastern. Landslides are geotechnical phenomena that can be studied by conducting field experiments, laboratory experiments, and numerical modeling. Various methods can be adopted to study landslides, and the landslide flume seems to be one of the most widely used techniques for laboratory simulation of the landslides. The scaled models created in a flume can represent the real-world situations so far, which will be reviewed here. The essential aspects of this review include the practicality of the flume experiments from the previous findings, how they can be related to the real-world scenarios, the difference between field instrumentations and laboratory instrumentations, discrepancies that can occur due to the scaled effect of laboratory simulation, and recommended techniques for the future development of laboratory simulated landslides with tilting type flume incorporated with a rainfall simulator. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item An Analysis of Piled Slope with Single Row of Piles Using 2D Finite Element Analysis(Springer Science and Business Media Deutschland GmbH, 2024) Jose, D.; Kolathayar, S.; Nayak, S.The increased frequency of landslides and the associated damages emphasize the need to develop novel techniques for landslide mitigation. Among numerous methods developed till today, an anti-slide pile is an effective tool for controlling slides in landslide-prone areas. The present study assesses the suitability of 2-D FE analysis using the strength reduction method for analyzing a slope stabilized with anti-slide piles. A detailed parametric study was carried out to explore the influence of the position and length of the pile on the factor of safety of pile-reinforced slopes, and the failure mechanism was studied in detail. Fixed head piles improved the safety factor compared to free head piles, and an improvement of 1.5 times was obtained compared with unreinforced slope. Piles located at the crest and toe of the slope were not significantly improving compared to other locations. For fixed head piles, the length of the pile does not affect the factor of safety, and for free head piles, the factor of safety improves with an increase in the length of the pile. For the slope considered in the study, the optimum position of the pile is between the crest and middle portion of the slope, and the optimum length is found to be 20 m for free head piles and 10 m for fixed head piles. The failure mechanism of the piled slope is also explained in detail for each case. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.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 Earthquake-Induced Landslides in India—An Overview of Causes, Effects and Mitigation Strategies(Springer Science and Business Media Deutschland GmbH, 2025) Ajesh Sankar, M.; Sreevalsa, K.This review paper examines the landslides triggered by significant earthquakes in India over the past two decades, focusing on their causes, impacts, and mitigation strategies. The present study examines detailed case histories of earthquake-induced landslides from Kashmir (2005), Sikkim (2011), Gorkha (2015), Uttarakhand (2017), and Assam (2021) earthquakes. It has been observed that landslides are often associated with an earthquake of magnitude four or more. Also, the reported peak ground accelerations (PGA) were more than 0.05 g, sufficiently triggering the landslides. Other common factors contributing to the landslides are fragile geological conditions, steep slopes, hydrological influences, and human activities. The review highlights the distinct topographical and geological vulnerabilities of the Himalayan and northeastern parts of India. The paper also evaluates the effectiveness of various mitigation strategies adopted for effective future risk management. The findings aim to enhance the understanding and preparedness for earthquake-induced landslides, contributing to developing more resilient infrastructure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.