MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641081792 A) filed by Sathyabama Institute Of Science And Technology on July 02, 2026, for Ai-Iot Powered Precision Agriculture Platform For Intelligent Crop Health Assessment And Resource Optimization.
Inventors include Dr. D. Poornima; Dr. S. Gayathri; Ms. Abirami. R; Ms. S. Priyadharshini; and Dr. S. L. Jany Shabu.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: ABSTRACT Agriculture plays a vital role in ensuring food security, and effective crop health management is essential for maximizing productivity while minimizing resource wastage. This paper presents an AI-Powered Precision Agriculture Platform for Intelligent Crop Health Assessment and Resource Optimization, specifically designed for automated maize crop monitoring and sustainable pest management. Traditional pest detection and control methods rely heavily on manual field inspections, which are labor-intensive, time-consuming, and often result in delayed interventions. The proposed platform integrates Internet of Things (IoT) technologies with Artificial Intelligence (AI) to continuously monitor maize crop health through a multi-level sensing architecture. Level 1 employs camera sensors to capture leaf and crop images for visual disease and pest detection. Level 2 utilizes acoustic sensors to identify pest activities through sound pattern analysis, while Level 3 incorporates soil moisture sensors to evaluate environmental conditions affecting crop growth and pest infestation. Data collected from these heterogeneous sensors are transmitted to a cloud- based platform for centralized storage, processing, and analysis. Advanced pattern-matching algorithms, data analytics techniques, and deep learning models are employed to detect pest presence, classify pest types, assess crop health conditions, and generate actionable insights. Based on the analyzed data, the system autonomously determines the severity of infestations and recommends appropriate pest control measures. In critical situations, a GSM communication module is activated to provide real-time alerts and notifications to farmers, enabling timely intervention and informed decision-making. The proposed platform significantly enhances the efficiency, accuracy, and sustainability of maize crop management by reducing crop losses, minimizing unnecessary pesticide application, and optimizing resource utilization. By combining IoT-enabled sensing, cloud computing, and AI-driven predictive analytics, the system facilitates early disease and pest detection, improves maize yield, and promotes environmentally responsible farming practices. The developed solution represents a scalable and intelligent framework for next-generation precision agriculture and sustainable crop production.
Disclaimer: Curated by HT Syndication.
