MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202644087184 A) filed by C Pavani; Kavita Kori; Dr. Shruthishree S. H; Pallavi C V; Bonamsetty Hymavathi; and Dayananda Sagar Academy Of Technology And Management on July 16, 2026, for Digital Twin-Enabled Aiot Framework For Multi-Layer Crop Intelligence In Smart Farming.
Inventors include C Pavani; Kavita Kori; Dr. Shruthishree S. H; Pallavi C V; Bonamsetty Hymavathi; and Dayananda Sagar Academy Of Technology And Management.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: Precision agriculture is increasingly adopting Artificial Intelligence of Things (AIoT) technologies to improve crop productivity and resource management. However, existing smart farming systems often lack real-time predictive capabilities and fail to provide a unified view of dynamic farm conditions. This paper proposes a Digital Twin-Enabled AIoT Framework for Multi-Layer Crop Intelligence in Smart Farming, integrating AIoT sensors, edge-cloud computing, and Digital Twin technology to create a real-time virtual representation of agricultural fields. The framework collects multi-layer data, including soil conditions, crop health, weather, irrigation, and nutrient status, through distributed sensors. Artificial intelligence models analyze the collected data to support disease prediction, irrigation scheduling, nutrient optimization, and yield forecasting. The Digital Twin continuously synchronizes with the physical farm, enabling simulation, predictive analysis, and evaluation of farming strategies before implementation. Edge computing ensures low-latency data processing, while cloud platforms provide scalable storage and advanced analytics. Farmers receive real-time insights and intelligent recommendations through a decision-support dashboard, enabling timely and informed interventions. Experimental evaluation demonstrates that the proposed framework improves prediction accuracy, optimizes water and fertilizer usage, and enhances crop productivity compared with conventional IoT-based approaches. The proposed AIoT-enabled Digital Twin framework offers a scalable, adaptive, and sustainable solution for intelligent precision agriculture, supporting efficient resource utilization and resilient crop management.
Disclaimer: Curated by HT Syndication.
