MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541122625 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy University; Malla Reddy Engineering College For Women; Malla Reddy College Of Engineering And Technology; and Malla Reddy Vishwavidyapeeth, Medchal-Malkajgiri, Telangana, on Dec. 5, 2025, for 'cloud native big data toolkit for disaster risk analytics.'
Inventor(s) include Dr. P. Raghunadh; Dr. B. Jogeswara Rao; L. C. Usha Maheswari; P. V. Naresh; and Dr. P. Laxmi Madhuri.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "It is a cloud-native big data toolkit that is created to provide real-time analytics on disaster risks based on scalable data integration, predictive modelling and spatial intelligence. The framework brings together the heterogeneous data sources like satellite images, IoT sensor data, meteorological repositories, and socio-economic signals to give singular insights on the disaster exposure, vulnerability, and resilience. The system is constructed upon a distributed cloud platform and provides scalability of resources and parallel data processing to effectively handle high-volume, high-speed datasets. The architecture combines geospatial analytics, time-series modeling modules, and machine learning modules to predict the possibility of disasters and evaluate the risk patterns at the regional level. Data ingestion pipelines taking automatic measures to preprocess and harmonise structured and unstructured data, whereas, analytical core platform deploys predictive models covering hazards like floods, cyclones, droughts, and seismic events. The visualization layer transforms the results of analytical work into interactive risk dashboards, in this way, allowing the stakeholders to define hotspots and prioritize mitigation measures. A contextual reasoning module considers the risk trend based on correlations between the hazard data with demographic and infrastructure variables with the help of the evidence-based decision-making. The cloud-based implementation enhances elasticity, resilience and compatibility with both open repositories and warning systems in the external world. The toolkit is capable of increasing disaster management agencies and urban planners preparedness, resource allocation and policy formulation by automating large scale disaster analytics and enhancing precision in disaster forecasts."
Disclaimer: Curated by HT Syndication.
