MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202621108693 A) filed by Dr. Neha Kudu; Dr. Rasika Ransing; and Dr. Vipul Dalal on September 10, 2026, for Adaptive Context-Aware Machine Learning System For Real-Time Anomaly Detection And Predictive Decision Optimization.
Inventors include Dr. Neha Kudu; Dr. Rasika Ransing; and Dr. Vipul Dalal.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: 7. ABSTRACT OF THE INVENTION ADAPTIVE CONTEXT-AWARE MACHINE LEARNING SYSTEM FOR REAL-TIME ANOMALY DETECTION AND PREDICTIVE DECISION OPTIMIZATION The invention relates to an adaptive context-aware machine-learning system that receives heterogeneous real-time data, determines an operating context, generates context-dependent features and dynamically selects a machine-learning model. An anomaly detection engine generates a context-aware anomaly score and evaluates temporal persistence. A predictive state estimation engine predicts a future operational state using the anomaly score, contextual state and historical information. A decision optimization engine evaluates candidate actions according to predicted risk, operational constraints and cost parameters and determines an optimized action. A feedback-learning module receives an actual outcome and adapts model parameters, feature weights, anomaly thresholds, model-selection parameters or decision-optimization parameters. The system provides real-time anomaly detection with contextual adaptation and a closed- loop predictive decision mechanism. FIG. 1 illustrates the overall system architecture.
Disclaimer: Curated by HT Syndication.
