'Identification of flood-prone areas sans human involvement'

Researchers belonging to the BITS-Pilani, Hyderabad campus, have successfully assessed flood conditions using Machine Learning algorithms. Rampalli Madhuri, a research student led by K Srinivasaraja, Professor of Civil Engineering, conducted the research and successfully launched it. Chemical engineering student Shashank also helped them. This method allows the identification of flood-prone areas without human involvement.

Hyderabad:Researchers belonging to the BITS-Pilani, Hyderabad campus, have successfully assessed flood conditions using Machine Learning algorithms. Rampalli Madhuri, a research student led by K Srinivasaraja, Professor of Civil Engineering, conducted the research and successfully launched it. Chemical engineering student Shashank also helped them. This method allows the identification of flood-prone areas without human involvement.

Flood-hit areas in Hyderabad can be alerted and preventive measures can be taken if they are assessed in advance. They analyse the flood-prone areas with the help of Machine Learning based on the highest rainfall details of 2000, 2006 and 2016 from various departments, including the GHMC. The information provided to the computer about rainfall, surface conditions, sloping area, proximity to floodplains, surface temperatures and overgrown trees.

Madhuri explained that a comprehensive report is being prepared estimating the flood situation in 2040 and 2080. Details of this research were published in the prestigious UK Journal of Water and Climate Change in September.