MUMBAI, India, Sept. 7 -- Intellectual Property India has published a patent application (202611084185 A) filed by Upes on July 09, 2026, for A System And Method For Distributed Self-Calibration Of Sensor Mesh Nodes Using Trust-Weighted Consensus For Predictive Maintenance.
Inventors include Ayush Kumar Agrawal; Sushabhan Choudhury; Keshav Sinha; Oshan Paul; and Diwakar Chauhan.
The application for the patent was published on September 04, 2026, under issue no. 36/2026.
Abstract: A System and Method for Distributed Self-Calibration of Sensor Mesh Nodes Using Trust-Weighted Consensus for Predictive Maintenance. The invention relates to industrial sensor networks and, more particularly, to distributed self-calibration of sensor nodes in a wireless mesh for predictive maintenance. Each sensor node includes a sensing element, embedded processor, memory, wireless communication interface, data acquisition module, local preprocessing function, drift estimation module, dynamic trust scoring module, communication module, and trust-weighted consensus module. Real-time measurements are locally acquired and analyzed against historical baselines to estimate drift. Each node computes a trust score based on drift magnitude, historical consistency, neighboring sensor agreement, and reliability, and exchanges compact state information with neighboring nodes. Corrected sensor measurements are generated through trust-weighted aggregation, wherein higher-trust nodes exert greater influence and low-trust or drifting nodes are down-weighted or excluded. The corrected measurements support machine health monitoring, fault detection, remaining useful life estimation, and maintenance scheduling.
Disclaimer: Curated by HT Syndication.
