Stay ahead of flood risks with FloodVision. This app delivers accurate, timely predictions to help you make informed decisions, protecting you, your loved ones, and your property. See the future and stay safe with FloodVision.
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Flood Vision is a web application powered by a Machine Learning model designed to assess flood severity. The model is based on flood prediction data specific to Kolhapur, Maharashtra, India. This region experiences a unique monsoon climate, marked by seasonal variations in rainfall and temperature. The monsoon season, typically lasting from June to October, plays a critical role in shaping the area's weather patterns and hydrological systems. However, variations in monsoon rainfall intensity and distribution across different years significantly influence flood risks and water availability.
Based on the provided flood severity classification:
• 0 - No Flood: Rainfall below 120 mm
• 1 - Normal: Rainfall ranging from 120 to 250 mm
• 2 - Moderate: Rainfall ranging from 250 to 400 mm
• 3 - Severe: Rainfall ranging from 400 to 510 mm
• 4 - Extreme: Rainfall above 510 mm
This dashboard is done using a software Jupyter Notebook. To see the visualizations interactive I am attaching my Jupyter Notebook file. This requires Jupyter Notebook or other Compatiable software to open the file. The usage of dashboards like these is to bring a better understanding about the dataset and also to bring some beautiful insights
Prof. Dr. Kamal Alaskar is a distinguished scholar with over three decades of teaching experience and 16 years of research expertise in Data Warehousing, Data Mining, and Big Data. He served as the Head of the Research Cell and Development at Bharati Vidyapeeth (Deemed to be University), Kolhapur, from 1994 to 2024, shaping academic and research excellence. With a Ph.D. in Computer Science from Shivaji University (2010), Prof. Alaskar has an impressive portfolio of research publications and technical contributions, including his role as a member of the Technical Committee for the International Arab Journal of Technology (2009–2022). His international tenure includes a five-year deputation to the Royal University of Bhutan, fostering academic growth under India’s Colombo Plan.
Mr. Deelip Patil, an Assistant Professor at Bharati Vidyapeeth (Deemed to be University), Institute of Management, Kolhapur, brings 14 years of rich teaching experience to academia. He holds a B.Sc. in Physics from Shivaji University and an MCA from Tilak Maharashtra Vidyapeeth, Pune. He is a qualified professional, having cleared the UGC-NET and SET exams, and is currently pursuing a Ph.D. under the esteemed guidance of Dr. K. M. Alaskar. Mr. Patil's academic journey includes tenure at Sant Rawool Maharaj Mahavidyalaya, Kudal, and Sanjay Ghodawat University, Kolhapur. With specialized skills in Artificial Intelligence, MongoDB, jQuery, JSON, PHP & MySQL, Python, and Advanced Java, Mr. Patil contributes to the advancement of computer science education and research.