Publications
Patents
Dutt V., Kumar P., Sihag P., Mali N., Pathania A., and Uday K.V. A low cost, sub-surface iot framework for landslide monitoring and warning, January 12, 2021. Patent Application 202111001337, New Delhi, Patent Office Dwarka New Delhi 110078.
Dutt V., Kumar P., Saini T., Pathania A., Rana D. C., and Attri S. C. Low-power, low-cost air-quality monitoring, predicting & warning system, November 28, 2019. Patent Application 201911048755, New Delhi, Patent Office Dwarka New Delhi 110078.
Dutt V., Kumar P., Sihag P., Agrawal S., Mali N., Pathania A., and Uday K.V. Smart iot based test-bed system for lab scale landslide monitoring experiment, October 22, 2018. Patent Application 201813039735, New Delhi, Patent Office Dwarka New Delhi 110078.
Journal Articles
2021
Kumar P., Sihag P., Chaturvedi P., Uday. K.V., and Dutt V. (2021). BS-LSTM: An Ensemble Recurrent Approach to Forecasting Soil Movements in the Real World. Frontiers in Earth Science, volume 9, page 716. Frontiers. DOI:10.3389/feart.2021.696792.
Kumar P., Sihag P., Sharma A., Pathania A., Singh R., Chaturvedi P., Mali N., Uday. K.V., and Dutt V. (2021). Prediction of Real-World Slope Movements via Recurrent and Non-recurrent Neural Network Algorithms: A Case Study of the Tangni Landslide. Indian Geotechnical Journal,
SI: Landslides: Forecasting, Assessment and Mitigation, volume 51, page 788–810. Springer. DOI:10.1007/s40098-021-00529-4.
Book Chapter Publications
2021
Thakur V., Robinson K., Oguz E., Depina I., Pathania A., Kumar P., Chaturvedi P., Uday K.V, and Dutt V. (2021). Early Warning of Water-Triggered Landslides. Indian Geotechnical Conference 2019. Lecture Notes in Civil Engineering, volume 144. DOI:10.1007/978-981-33-6590-2_11.
Pathania A., Kumar P., Priyanka, Maurya A., Uday K.V, and Dutt V. (2021). Development of an Ensemble Gradient Boosting Algorithm for Generating Alerts About Impending Soil Movements. In: Gopi, E.S. (eds) Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication. Lecture Notes in Electrical Engineering, volume 749, pages 365–379. DOI:10.1007/978-981-16-0289-4_28.
Kumar P., Sihag P., Pathania A., Chaturvedi P., Uday. K.V., and Dutt V. (2021). Comparison of Moving-Average, Lazy, and Information Gain Methods for Predicting Weekly Slope-Movements: A Case-Study in Chamoli, India. In: Nicola Casagli, Veronica Tofani, Kyoji Sassa, Peter T. Bobrowsky, and Kaoru Takara, editors, Understanding and Reducing Landslide Disaster Risk. WLF 2020. ICL Contribution to Landslide Disaster Risk Reduction, volume 3, pages 321–330. Springer International Publishing, Cham, 2021. DOI:10.1007/978-3-030-60311-3_38.
ISBN:978-3-030-60311-3.
2019
Sharma R., Saini T., Kumar P., Pathania A., Chitineni K., Chaturvedi P., and Dutt V. (2020). An Online Low-Cost System for Air Quality Monitoring, Prediction, and Warning. Distributed Computing and Internet Technology. ICDCIT 2020. Lecture Notes in Computer Science, volume 11969, pages 311–324. Springer. DOI:10.1007/978-3-030-36987-3_20.
Conference Publications
2022
Kumar P., Priyanka P., Uday K.V., and Dutt V. (2022). DR-A-LSTM: A Recurrent Neural Network with a Dimension Reduction Autoencoder a Deep Learning Approach for Landslide Movements Prediction. In: 12th International Advanced Computing Conference (IACC), Hyderabad, India. (in press)
Priyanka P., Kumar P., Chaturvedi P., Uday K.V., and Dutt V. (2022). Data-driven Approach for Predicting Surface Subsidence Velocity from Geotechnical Parameters. In: 12th International Advanced Computing Conference (IACC), Hyderabad, India. (in press)
Priyanka P., Kumar P., Devi A., Kumar A., Gaurav G., Uday K.V., and Dutt V. (2022). Univariate, Multivariate, and Ensemble of Multilayer Perceptron Models for Landslide Movement Prediction: A Case Study of Mandi. In: 12th International Advanced Computing Conference (IACC), Hyderabad, India. (in press)
2020
Kumar P., Sihag P., Pathania A., Agarwal S., Mali N., Singh R., Chaturvedi P., Uday K.V., and Dutt V. (2020). Predictions of Weekly Slope Movements Using Moving-Average and Neural Network Methods: A Case Study in Chamoli, India. In: Nagar A., Deep K., Bansal J., and Das K., editors, Soft Computing for Problem Solving 2019. Advances in Intelligent Systems and Computing, volume 1139, pages 67–81. Springer. DOI:10.1007/978-981-15-3287-0_6.
Pathania A., Kumar P., Sihag P., Singh R., Chaturvedi P., Uday K.V., and Dutt V. (2020). A lowcost, sub-surface iot framework for landslide monitoring, warning, and prediction. In: In Proceedings of 2020 International conference on advances in computing, communication, embedded and secure systems. Springer, Cham.
Pathania A., Kumar P., Sihag P., Maurya A., Kumar M., Singh R., Chaturvedi P., Uday K.V., and Dutt V. (2020). Predictions of Soil Movements using Persistence, Auto-regression, and Neural network models: A case-study in Mandi, India. In: Bansal J., editor, International Conference on Paradigms of Computing, Communication and Data Sciences (PCCDS-2020). Springer. DOI:10.1504/IJSI.2022.10043800.
2019
Kumar P., Sihag P., Pathania A., Agarwal S., Mali N., Singh R., Chaturvedi P., Uday K.V., and Dutt V. (2019). Predictions of Weekly Soil Movements Using Moving-average and Support-vector Methods: A Case-study in Chamoli, India. In: Correia A., Tinoco J., Cortez P., and Lamas L., editors, Information Technology in Geo-Engineering. ICITG 2019. Springer Series in Geomechanics and Geoengineering, pages 393–405. Springer. DOI:10.1007/978-3-030-32029-4_34.
Kumar P., Sihag P., Pathania A., Agarwal S., Mali N., Chaturvedi P., Singh R., Uday K.V., and Dutt V. (2019). Landslide Debris-Flow Prediction using Ensemble and Non-Ensemble MachineLearning Methods: A case-study in Chamoli, India. In: O. Valenzuela, Rojas F., Pomares H., and Rojas I., editors, Contributions to Statistics: Proceedings of the 6th International Conference on Time Series and Forecasting (ITISE), Granda, Spain, pages 614–625. Springer. ISBN:978-84-17970-78-9.
Pathania A., Kumar P., Kesri J., Sihag P., Agarwal S., Mali N., Singh R., Chaturvedi P., Uday K.V., and Dutt V. (2019). Reducing power consumption of weather stations for landslide monitoring. In: Correia A., Tinoco J., Cortez P., and Lamas L., editors, Information Technology in Geo-Engineering. ICITG 2019. Springer Series in Geomechanics and Geoengineering, pages 144–158. Springer. DOI:10.1007/978-3-030-32029-4_13.
Under Review or Revision
Kumar P., Priyanka P., Dhanya J., Uday K.V., and Dutt V. (2022). Development and Comparison of Univariate and Multivariate Models for Soil Movement Predictions. Under Review.