MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115654 A) filed by Rajeesh Kumar N V; D. Anto Babiyola; Adlin Beenu V; Christal Anto V; Bratheesha S R; S. Afrin Banu; Arun Venkadesh N; and Jane Shifa I on September 27, 2026, for Autonomous Communication Management System For Iot Networks Using Predictive Artificial Intelligence Models.
Inventors include Rajeesh Kumar N V; D. Anto Babiyola; Adlin Beenu V; Christal Anto V; Bratheesha S R; S. Afrin Banu; Arun Venkadesh N; and Jane Shifa I.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The present invention relates to an IoT (Internet of Things) network Autonomous Communication Management System Using Predictive Artificial Intelligence Models. The proposed system is configured to continuously monitor the operating condition of a plurality of interconnected IoT nodes and is capable of predicting communication degradation or network failure prior to the actual occurrence of such failure. The system includes distributed IoT nodes, sensor and actuator interfaces, communication transceivers, an edge gateway, a network monitoring unit, a feature-processing unit, predictive artificial intelligence models, an autonomous decision controller, a communication management unit and a performance verification module. Every IoT node gathers application data and communication-related parameters like received signal strength, signal-to-noise ratio, packet loss, packet delivery ratio, latency, retransmission count, buffer occupancy, node energy, route condition and neighbouring-node availability. The collected parameters are sent to the edge gateway and are transformed into prediction features, which describes the current network operating condition. The predictive artificial intelligence model processes present and past communication features to forecast the likelihood of future link degradation, congestion, route failure, node disconnection, excessive communication delay, or energy-related communication interruption. The autonomous decision controller selects a preventive communication management action based on the predicted network condition prior to the predicted failure occurs. For example, the preventive actions are switching of communication channels, transmission-power adjustment, data-rate modification, packet-priority control, reporting-interval adjustment, alternate-parent selection, route reconstruction, load redistribution, gateway failover, node isolation or activation of a redundant communication path. The chosen action is sent to the affected IoT nodes and automatically performed without the need for continuous manual intervention. After the execution of the selected action, the performance verification module measures the resulting communication characteristics and checks whether the expected degradation has been avoided. The predicted action, selected action and resulting performance are stored in a communication-history database that can be used later to update or refine the predictive model. The artificial intelligence model can be implemented using artificial neural networks, recurrent neural networks, long short-term memory networks, decision-tree models, ensemble learning models, or other predictive machine learning architectures. The edge-based inference allows autonomous communication management, even in the absence of cloud connectivity. Thus, the proposed system improves the network reliability, communication availability, latency control, energy utilisation and continuity of critical IoT communication.
Disclaimer: Curated by HT Syndication.
