MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641108667 A) filed by K. Suganya; Mamatha Besagaralli Nagaraju; Dr. Prakyath Dayananda; Mohan Bangalore Somasekar; Dr. Vijay Kumar Kalal; Ms. Kavitha Arunachalam; Padmapriya Mummoorthi; Dr. Aarthi Elangovan; Vivek Marotrao Korde; and Anitha Bangari on September 10, 2026, for Ai-Driven Iot And Cloud-Based System For Intelligent Electrical Theft Prediction And Real-Time Energy Monitoring.
Inventors include K. Suganya; Mamatha Besagaralli Nagaraju; Dr. Prakyath Dayananda; Mohan Bangalore Somasekar; Dr. Vijay Kumar Kalal; Ms. Kavitha Arunachalam; Padmapriya Mummoorthi; Dr. Aarthi Elangovan; Vivek Marotrao Korde; and Anitha Bangari.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: An AI-driven, IoT-and-cloud-based system for intelligent electrical theft prediction and real-time energy monitoring is disclosed. A plurality of internet-of-things sensing devices, comprising smart meters at consumer connection points and sensors at distribution nodes, senses electrical parameters, the energy consumed, current, and voltage, and transmits the data over a communication network to a cloud platform, which aggregates and stores it. A machine learning module on the cloud predicts and detects electrical theft by learned recognition of the patterns, anomalies, and discrepancies theft produces, comprising abnormal drops or anomalies in an individual consumer's consumption indicative of meter tampering or bypass, and a discrepancy between the energy supplied to a region, sensed at its node, and the energy consumed within it, sensed at its meters, indicative of unmetered abstraction. The module distinguishes theft from legitimate variation and technical loss, computes a confidence to guard against false accusation, and localizes the theft to a region and connection. A monitoring and alerting module presents real-time energy and predicted theft on a dashboard and alerts the utility in real time to the theft and its probable location, enabling prompt, targeted investigation.
Disclaimer: Curated by HT Syndication.
