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70
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Introduction
Uday Kala currently works at the Department of Civil Engineering, Indian Institute of Technology Mandi. Their current project is 'Bio-Geotechnics', field testing of model micropiles, MEMS based Landslide monitoring and early warning sensors
Additional affiliations
April 2015 - present
July 2013 - March 2015
January 2010 - December 2012
Publications
Publications (70)
Landslides are a major natural hazard that can cause significant damage and loss of life. They are often triggered by heavy rainfall, earthquakes, or other factors that can destabilize the soil and rock. To mitigate risks associated with landslides, it is important to predict where and when they are likely to occur. In this study, we developed a mu...
Extreme weather events and global climate change have exacerbated the problem of evaporation rates. Thus, accurately predicting soil moisture evaporation rates affecting soil cracking becomes crucial. However, less is known about how novel feature engineering techniques and machine-learning predictions may account for estimating the soil moisture e...
This study focuses on predicting soil movement in the Himalayan region using machine learning models. It introduces a new model called Hierarchical Transformer Prediction Autoencoder (H-TPA) and compares it with other neural networks. The study also uses Variable Sensitivity Analysis to identify environmental triggers for soil movements. Results sh...
Landslides threaten human life and infrastructure, resulting in fatalities and economic losses. Monitoring stations provide valuable data for predicting soil movement, which is crucial in mitigating this threat. Accurately predicting soil movement from monitoring data is challenging due to its complexity and inherent class imbalance. This study pro...
A low-cost landslide monitoring system with sensing, decision-making, and alert generation components comprising of different MEMs-based sensors such as temperature and humidity sensor; atmospheric-pressure sensor; light-intensity sensor; rain gauge; accelerometer; soil-moisture sensor; and force sensors for sensing the on-site movement, soil, and...
The present invention relates to an IoT and MEMS-based low-cost subsurface landslide monitoring and early warning system comprising a sensing unit, data logging and thresholding unit, and an alerting unit. The sensing unit further consists of multiple nodes comprising of a plurality of sensors such that each sensor is connected to the master-microc...
Due to intensifying climate change impacts, landslides have become increasingly threatening in the Himalayan region, particularly in India's Kamand Valley. This study addresses the pressing need for accurate landslide prediction models by leveraging advanced Landslide Monitoring Systems (LMSs) and machine learning techniques. A significant challeng...
The Himalayan region, particularly Himachal Pradesh, faces an escalating threat from landslides intensified by climate change. These landslides imperil human lives and valuable properties, demanding effective prediction and mitigation measures. This study develops advanced machine learning (ML) models for soil movement prediction in landslide-prone...
Purpose
Soil erosion is a complex global environmental problem as it leads to land degradation, increase in sedimentation, triggering landslides, and pollution of the water bodies. Due to their adaptability, economy, and sustainability, nature-based mitigation strategies for erosion prevention have recently been renewed and developed. However, the...
In the Himalayan region, micropile is one of the effective foundation solution to resist uplift load of structures on inaccessible and steep slopes. The performance of micropile is highly influenced by multiple parameters, with limited studies attempting to understand their individual contribution. With this in view, the current research work eluci...
This study performs slope displacement-based probabilistic seismic landslide hazard assessment for Mandi town. Here, the slope angles of the concerned region are obtained from the digital elevation map (DEM), and the material properties are obtained from lithological information and literature. The critical acceleration of the slopes is estimated b...
Movement of soil and associated landslides frequently occur in hilly areas. Regular monitoring, accurate prediction, and timely alerting of people about soil movements on hills susceptible to landslides are essential due to the potential destruction to life and property. A more recent strategy for predicting soil movement is the use of machine lear...
The mountainous areas of the Indian Himalayan region are frequently affected by natural calamities, particularly slope failures, which cause damage to human lives and property. According to NIDM 2016, India reported that slope failures affected 15% of the total area. Because of climatic changes, the frequency of landslide occurrences was rapidly in...
Soil erosion is a serious global environmental problem as it leads to land degradation, an increase in sedimentation, and pollution in water bodies. In adverse conditions, an increase in the deterioration of soil due to erosion leads to an increase in the susceptibility of land to landslides, which makes the study of erosion important for environme...
The landslides are a challenging problem in the Himalayan states such as Himachal Pradesh and Uttarakhand in India and as well as in the world. Machine learning models could be developed to predict the movement of landslides in advance. In our proposed study, we developed a univariate, multivariate, and ensemble multilayer perceptron (MLP) and trai...
The Himalayan mountains are prone to landslide disasters, which cause injury and fatalities among people. Remote sensing, particularly interferometric synthetic aperture radar (InSAR) based analyses, may help find the surface subsidence velocities, the rate of vertical movement of the Earth's surface downward. These subsidence velocities may help i...
Landslides are a challenging problem in India and the world. Different weather conditions and soil properties could trigger landslides. The Machine learning (ML) models could predict landslides' movements. The ML model may overfit the high-dimensional feature of weather and soil data. Dimension reduction techniques could reduce the dimension of the...
Vegetation is needed to improve soil slope stability. The roots of different species stabilize the ground by their tensile strength. However, how the tensile strength is governed by different root and shoot characteristics is less known. In this study, root tensile strength was investigated, and root and shoot characteristics were simultaneously me...
Soil strength improvement employing microbial induced calcite precipitation (MICP) involves bio-geo-chemical interaction among bacteria (here, Sporosarcina pasteurii), sand, and cementing solution. A critical review of literature opened the gap in exploring the strength gain for a given amount of CaCO3 precipitation, investigating the influence of...
Plant root architecture plays a vital role in establishing its interaction and, thereby, performance in ground improvement. Root image analysis has been widely adopted to compute the root traits, but it has associated limitations related to traits correlation. Hence, the current study aims to develop a methodology such that constraints on adapting...
The slope failures cause significant damage, and the slope failure assessment can help understand the underlying factors contributing to these disasters. These disaster risks can be reduced through landslide monitoring and generating early warning alerts at vulnerable sites. Furthermore, the parameters to ascertain the instability for a given regio...
Landslide disaster risk reduction necessitates the investigation of different geotechnical causal factors for slope failures. Machine learning (ML) techniques have been proposed to study causal factors across many application areas. However, the development of ensemble ML techniques for identifying the geotechnical causal factors for slope failures...
Machine learning (ML) proposes an extensive range of techniques, which could be applied to forecasting soil movements using historical soil movements and other variables. For example, researchers have proposed recurrent ML techniques like the long short-term memory (LSTM) models for forecasting time series variables. However, the application of nov...
Natural disasters such as landslides cause a lot of damage to life and property. However, less is known on how one could generate accurate alerts against landslides sufficiently ahead in time. The primary objective of this research is to develop and cross-validate a new ensemble gradient boosting algorithm for generating specific alerts about impen...
Multidrug resistance is one of the worldwide public health concerns. Water represents the most suitable environment, for the exchange of antibiotic resistance genes among pathogenic to non-pathogenic bacteria. Therefore, we aimed to screen the presence of bla NDM-1 , bla TEM , bla SHV , bla CTX-M and mcr1–5 genes among water samples from different...
Landslides are widespread disasters in hilly regions. These disasters cause lots of injuries and deaths every year. Due to these injuries and deaths, it is imperative to monitor landslides and to warn people about impending disasters timely. It is also essential to predict slope movements ahead of time so that people get enough lead time to evacuat...
The Tangni landslide in Chamoli, India, has experienced several landslide incidents in the recent past. Due to the fatalities and injuries caused, it is essential to predict slope movements at this site. A recent approach to predicting slope movements is via machine-learning algorithms. In machine learning literature, recurrent neural networks (sim...
Ground improvement by the biological method is considered to be one of the most preferred sustainable methods for improving engineering properties of soil in comparison to the physical, mechanical and chemical methods. One of such biological method, ureolytic microbial-induced calcite precipitation (UMICP), utilizes urease active bacteria to precip...
Landslides are a major societal threat, causing adverse consequences to life, economy and environment. Mitigation of the potential negative effects of landslides commonly involves deployment of challenging and costly measures. This is often the case in the development and operation of linear infrastructures such as road, pipeline and railway networ...
The problem of soil movements and associated landslides is common in the areas of Himachal Pradesh state in India due to the hilly terrain. Prediction of soil movements ahead of time may help save lives and infrastructure. Prior research has used machine learning models to predict soil movements but a comparison of different models for soil movemen...
Shear strength of soil is a very important property in geotechnical engineering, in order to study the strength of soils. According to classical soil mechanics, the soil is generally assumed to be either fully saturated or completely dry conditions. However, 40% of the natural soil on the earth’s surface encountered as an unsaturated/partially satu...
In ground improvement techniques like micropiles, soil nailing, jet grouting, and reinforced earth structures, the values of skin friction and shearing resistance between geomaterials and construction materials are considered in their design. However, it is very essential to estimate the stresses transferred along with the interface between geomate...
Rainfall-induced landslides occur on soil slopes due to seepage of water through the interconnecting voids down the soil mass. Vegetation on the slopes is depicted to have hydrological properties that deplete the excessive soil moisture for photosynthesis, translocation, transpiration and structure. Contrarily, these roots present in the soil, form...
Landslide incidence is common in hilly areas. In particular, Tangni in Uttrakhand state between Pipalkoti and Joshimath has experienced a number of landslide incidents in the recent past. Thus, it is important to forecast slope-movements and associated landslide events in advance of their occurrence to avoid the associated risk. A recent approach t...
Landslides are widespread disasters in hilly regions. These disasters cause lots of injuries and deaths every year. Due to these injuries and deaths, it is imperative to monitor landslides and to warn people about impending disasters timely. It is also important to predict soil movements ahead of time so that people get enough lead time to evacuate...
Landslides are a major societal threat, causing adverse consequences to life, economy and environment. Mitigation of the potential negative effects of landslides commonly involves deployment of challenging and costly measures. This is often the case in the development and operation of linear in-frastructures such as road, pipeline, and railway netw...
Landslides are common in rural and mountainous areas of India, especially after heavy rain. Scientists now say they have developed a low-cost technology for detecting them, using a motion sensor commonly found in smartphones. The device is currently being trialled in more than 20 locations in the Himalayan state of Himachal Pradesh, where landslide...
Data is gaining more importance and significance these days. Starting from general information used by various user friendly interfaces like Google, Facebook, Amazon, Flipkart, Airtel, Jio, Tatasky etc., to data from satellite based imaging by satellite on weather, air, wind, precipitation and thereby weather forecasting has been daily to hourly le...
Landslides and associated soil movements (debris-flow) are the common natural calamities in the hilly regions. In particular, Tangni in Uttrakhand state between Pipalkoti and Joshimath has experienced a number of landslides in the recent past. Prior research has used certain machine-learning (ML) algorithms to predict landslides. However, a compari...
This is a video that appeared on BBC Click covering the low-cost landslide monitoring and warning system.
Landslides and associated slope movements are common occurrences in the hilly regions. In particular, Tangni in Uttrakhand state between Pipalkoti and Joshimath has experienced a number of landslides in the recent past. Prior research has used certain moving average and machine-learning (ML) algorithms to predict slope movements. However, a compari...
A large number of factors should be considered to understand landslide phenomena. The present study focused on the characterization of the debris material and its implication for slope stability using Field surveys and laboratory analyses. Field survey mainly includes UAV and drone techniques to determine the dimensions to prepare a landslide inven...
Landslide disasters cause massive damages in hilly areas around the world. Thus, improving understanding of landslides among people is critical. Prior research has investigated the effectiveness of computer games in causing learning from feedback. However, an evaluation of the effectiveness of computer games for landslide education has been less ex...
Among different natural disasters, landslides are widespread in hilly areas. For landslide monitoring, one needs to collect data via weather stations about the prevailing weather and soil properties at remote locations that are prone to landslides. Due to the non-availability of grid-power, one may need to depend upon large-sized solar panels and b...
Landslides plague the Himalayan region, and landslide occurrence is widespread in hilly areas. Thus, it is important to predict soil movements and associated landslide events in advance of their occurrence. A recent approach to predicting soil movements is to use machine-learning techniques. In machine-learning literature, both moving-average-based...
Vegetation improves the soil stability by virtue of its mechanical and hydrological characteristics that are governed by its root morphology. Root network supports the friction between the roots and soil thereby increasing the pull-out resistance and also imparts additional cohesion by induced suction characteristics. Therefore, in order to mitigat...
In ground improvement techniques like micropiles, soil nailing, jet grouting, and reinforced earth structures the values of skin friction and shearing resistance between geomaterials and construction materials are considered in their design. However, it is very essential to estimate the stresses transferred along with the interface between geomater...
The unsaturated soil behavior is one of the most significant areas of research in the geotechnical engineering. Desiccation cracking is one of such issues which results in variation of permeability, strength, and creation of zones of weakness. The cracks develop an irregular and/or preferential flow pattern for contaminant transport, thereby affect...
A landslide, that is, collapse of a mass of earth or rock from a mountain or cliff, is a common phenomenon in hills. Landslides pose a large threat to life and infrastructure and there is a need to develop low‐cost sensing frameworks that could help in monitoring landslides and alert people before they occur. Certain existing technologies have been...
Changes in the Earth's climate are likely to increase natural hazards like landslides in the hilly regions of north India. Thus, forecasting of these events at local-scale will help improve the preparedness of society in facing landslide disasters. There have been prior machine-learning research to predict landslide occurrence based on the statisti...
Landslides cause lots of damage to life and property world over. There has been research in machine-learning that aims to predict landslides based on the statistical analysis of historical landslide events and its triggering factors. However, prediction of landslides suffers from a class-imbalance problem as landslides and land-movement are very ra...
Extensive studies have been conducted, by earlier researchers, to understand cracking characteristics of the fine-grained soils. Based on these studies, several theories and models which facilitate understanding the effect of various soil and environment specific parameters (viz., clay content, plasticity, free swelling index, specimen dimensions,...
Aeolian sands, from Sam, Jaisalmer, Rajasthan, India, belong to the Great Indian Thar desert and, primarily, attract tourists from India and all over the world. Though, certain studies were conducted on the geological origin of these sand and deserts, results related to their physical, chemical, morphological, mineralogical, thermal, electrical and...
Tensile strength of fine-grained soils has been extensively investigated by earlier researchers and several methodologies have been evolved for its determination. However, either most of these methods are not valid/applicable for a wide range of moisture contents or they involve tedious sample/specimen preparation. In this context, the methodology...
Several theories and models that define cracking characteristics of fine-grained soils have been proposed by earlier researchers. However, it has been realized that cracking characteristics of these soils are mainly influenced by the environmental conditions to which they are exposed and on their mineralogical composition. To demonstrate this, inve...
Soil is a particulate material and its engineering properties are mainly controlled by the particle size and shape (i.e., morphological characteristics). In this context, earlier researchers have demonstrated dependence of soil specific parameters like permeability, shear strength, electrical conductivity, thermal conductivity and dielectric charac...
Most of the studies dealing with cracking characteristics of the fine-grained soils focus on establishing the influence of various factors affecting cracking, after effects of cracking, and cracking patterns. Mathematical models have also been developed based on the experimental results, from these studies, to estimate time of initiation of the cra...
industrialization and urbanization have led to generation of large amounts of solid and liquid wastes which are normally disposed off in the geoenvironment (i.e., soil mass, rock mass). Safe disposal and containment of these wastes in the geoenvironment pose a great challenge to engineers and planners. This can be attributed to the particulate and...
Several experimental techniques (viz., triaxial tests, direct tensile tests or suction measurements) have been developed and employed by earlier researchers to measure the tensile strength of fine-grained soils. However, these studies yield results that are soil specific and dependent on the methodology adopted. Apart from this, due to the bulk for...