MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641089659 A) filed by Dr. Resmi. A. M; Mithra V; Kruthika R; Jothi Keerthana Sri M; Dr. Nidhi Nagar; Charu Srivastava; Dr. Manikandan S; S. Revathi; Dr. V. Ravi Shankar; Thanigaivel Sundaram; Dr. Purra Anuradha; and E. Elakkiya on July 23, 2026, for Machine Learning-Based Smart Epidemic Intelligence System For Ebola Virus Disease Prediction And Prevention In Smart Healthcare Systems.
Inventors include Dr. Resmi. A. M; Mithra V; Kruthika R; Jothi Keerthana Sri M; Dr. Nidhi Nagar; Charu Srivastava; Dr. Manikandan S; S. Revathi; Dr. V. Ravi Shankar; Thanigaivel Sundaram; Dr. Purra Anuradha; and E. Elakkiya.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: The current innovation reveals a Machine Learning-Based Intelligent Epidemic Intelligence System for the Prediction and Prevention of Ebola Virus Disease (EVD) within Smart Healthcare Systems. The invention amalgamates Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT), Geographic Information Systems (GIS), Big Data Analytics, and Cloud Computing to facilitate real-time epidemic surveillance, early outbreak prediction, and intelligent decision support. The system gathers healthcare data from various sources, including electronic health records, hospitals, diagnostic laboratories, wearable health monitoring devices, IoT-enabled medical sensors, mobile health applications, environmental monitoring systems, travel databases, and public health surveillance networks. The gathered data is subjected to preprocessing, feature engineering, and predictive analysis employing machine learning algorithms such as Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Logistic Regression, Artificial Neural Networks (ANN), and deep learning models including Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The system detects infection hotspots via GIS-based spatial analysis, predicts outbreak trends, evaluates individual and regional risk levels, optimises healthcare resource distribution, and produces automated recommendations for quarantine, contact tracing, vaccination prioritisation, and emergency response. A secure cloud-based dashboard offers real-time visualisation of epidemic statistics, predictive insights, hotspot maps, healthcare resource availability, and AI-driven decision support for healthcare professionals and public health authorities. The invention bolsters epidemic preparedness, enhances prediction precision, diminishes disease transmission, optimises medical resource allocation, and facilitates proactive management of Ebola outbreaks within intelligent healthcare systems.
Disclaimer: Curated by HT Syndication.
