MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115319 A) filed by Mr. Shyam Kondeti; Aparna Sandesh Patil; Dr. Dipmala Salunke; Dr. Pallavi Tekade; Dr. K. Muthulakshmi; Dr. V. Subba Ramaiah; Dr. D. Suresh; Dr. L. Rajeshkumar; Kuldeep Chouhan; Dr. Karthick R; Abhinav Parkhi; and Savleen Kaur on September 25, 2026, for Ai-Based Integrated Smart System For Adaptive Monitoring, Prediction, Automation, And Intelligent Decision Support.
Inventors include Mr. Shyam Kondeti; Aparna Sandesh Patil; Dr. Dipmala Salunke; Dr. Pallavi Tekade; Dr. K. Muthulakshmi; Dr. V. Subba Ramaiah; Dr. D. Suresh; Dr. L. Rajeshkumar; Kuldeep Chouhan; Dr. Karthick R; Abhinav Parkhi; and Savleen Kaur.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The present invention discloses an artificial intelligence-based integrated smart system for adaptive monitoring, prediction, automation, and intelligent decision support across diverse operational environments. The system comprises data acquisition, pre-processing, data management, adaptive monitoring, prediction, decision-support, automation, feedback-learning, security, and user-interface modules connected through wired or wireless communication networks. Heterogeneous real-time and historical data is acquired from sensors, cameras, machines, connected devices, databases, software applications, communication networks, users, and external services. The acquired data is validated, cleaned, normalised, synchronised, and converted into a unified representation before analysis. Artificial intelligence models, including machine learning, deep learning, statistical forecasting, and contextual reasoning models, analyse current conditions, detect abnormalities, and predict future events, risks, demands, failures, or operational states. The decision-support module evaluates predicted outcomes with confidence levels, safety limits, operational policies, user preferences, and resource constraints to produce prioritised recommendations or authorised control actions. The automation module communicates with actuators, controllers, devices, machines, or software services to perform preventive or corrective operations. A feedback-learning mechanism compares actual and predicted outcomes and updates models, thresholds, decision rules, and response priorities, thereby enabling continuous adaptation. Processing functions may be distributed among edge devices, local servers, and cloud platforms to reduce latency and communication overhead. Security mechanisms provide authentication, controlled access, encrypted communication, integrity verification, and audit logging. The invention improves monitoring accuracy, prediction reliability, response speed, automation effectiveness, safety, resource utilisation, and decision quality while supporting human supervision and manual override. The system supports deployment across industrial, healthcare, agricultural, transportation, energy, environmental, and security applications.
Disclaimer: Curated by HT Syndication.
