MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202541015790 A) filed by Arockia Mary P; V. Kumaresan; S. Nelson; V. S. B. Engineering College, Karur; S. Logeshwari; N. Kanika; M. Prabha; and R. Nishanthini on February 24, 2025, for A Machine Learning-Based Flood Detection And Mobile Alert System For Real- Time Disaster Monitoring Using Remote Sensing Data.
Inventors include Arockia Mary P; V. Kumaresan; S. Nelson; V. S. B. Engineering College, Karur; S. Logeshwari; N. Kanika; M. Prabha; and R. Nishanthini.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: Floods are among the most devastating natural disasters, causing widespread damage to property, infrastructure, and human lives. To address this challenge, we propose a software-based flood prediction and distance-based alerting system that leverages advanced technologies to provide early warnings and targeted alerts. This system integrates satellite data, machine learning algorithms [recurrent convolutional neural network (CRNN)], and geospatial mapping to monitor environmental parameters such as rainfall, river levels, soil moisture, and weather patterns in real-time. By analyzing this data, the system predicts flood risks with high accuracy and identifies potential flood zones. The core innovation of this system lies in its distance-based alerting mechanism. Using geospatial data, the software calculates the proximity of individuals, communities, and critical infrastructure to the predicted flood zones. It then sends customized alerts via SMS, mobile apps, or email to users within specific radii of the affected areas. For instance, those within 5 kilometers of a high-risk zone receive immediate evacuation alerts, while those farther away are advised to prepare for potential impacts. The system also provides actionable information, such as evacuation routes, safe zones, and emergency contacts, tailored to the user’s location. This software-based solution ensures timely, precise, and actionable alerts, enabling communities to take preventive measures and authorities to allocate resources efficiently. By combining real-time flood prediction with targeted distance- based notifications, the system aims to minimize damage, save lives, and enhance disaster preparedness. It is a scalable, cost-effective, and proactive approach to mitigating the impact of floods, making it an essential tool for flood-prone regions worldwide.
Disclaimer: Curated by HT Syndication.
