MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202641112748 A) filed by Mrs. Annabel Shimi S P; Mrs. Raja Kala P; Mrs G. Marly; Mrs. A. Ambika; Mrs. D. Maria Sowmini; Dr. N. Nisha Rosebel; Mrs. I Domilin Shyni; and Mr. Sankara Rao Allada on September 21, 2026, for Deep Learning Framework For Autonomous Iot Network Optimization.
Inventors include Mrs. Annabel Shimi S P; Mrs. Raja Kala P; Mrs G. Marly; Mrs. A. Ambika; Mrs. D. Maria Sowmini; Dr. N. Nisha Rosebel; Mrs. I Domilin Shyni; and Mr. Sankara Rao Allada.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The rapid growth of the Internet of Things (IoT) networks has led to many problems in managing large amounts of interconnected devices, dynamic traffic patterns, scarce energy supply and the heterogeneous communication environment. In this research, the authors suggest a Deep Learning Framework for Autonomous IoT Network Optimization, which will enable intelligent, adaptive and self-managing network operations. The framework uses deep learning models to study various real- time and historical IoT network parameters such as traffic pattern, bandwidth utilization, latency, packet loss, energy consumption, device connectivity and channel condition. The framework automatically adapts routing, resource management, load balancing, congestion control and communication scheduling based on learning from the network behavior. The models are updated continuously by an adaptive learning mechanism, which reflects real-time feedback from the network and ensures that the system adapts to varying network conditions and workloads with minimal human intervention. The framework also introduces edge intelligence to improve processing latency and communications overhead by implementing key optimizations near the IoT devices. Experimental evaluation can be done by analyzing the network performance indicator like throughput, latency, PDR, energy efficiency, congestion rate and resource utilization etc. The proposed approach will be more reliable, scalable, energy efficient and quality of service (QoS) compared to other conventional IoT network management techniques. The framework applies to the smart cities, the industrial IoT, intelligent transportation, smart healthcare, smart agriculture and other large-scale IoT networks that need autonomous and intelligent network optimization.
Disclaimer: Curated by HT Syndication.
