MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641009364 A) filed by KKR & KSR Institute of Technology and Sciences, Vatticherukuru, Andhra Pradesh, on Jan. 29, for 'iot based smart farming eco system.'
Inventor(s) include Mrs. Molla Khamar; Ms. K. Vasantha Sumanjali; Ms. K. Sri Sarayu; Ms. G. M. V. V. Priya; and Ms. R. Mythri.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "The proposed invention relates to an Internet of Things (IOT)-based smart farming system designed to enhance agricultural efficiency through real-time monitoring and intelligent decision-making. Traditional farming practices often suffer from challenges such as improper irrigation, limited environmental insight, delayed field observation, and reduced crop productivity. To address these limitations, the system integrates multiple distributed IOT sensors to continuously measure critical soil and environmental parameters including soil moisture, temperature, humidity, light intensity, pH level, and nutrient content (NPK). The collected data is transmitted to a centralized processing unit or cloud platform, where it is analyzed to assess field conditions, detect abnormalities, and generate actionable insights for farmers. [0016] The system further incorporates automated control mechanisms for irrigation and resource management, enabling precision farming and optimized input utilization. Based on sensor-derived intelligence and predefined threshold values, the system can trigger automated responses such as activating irrigation, recommending suitable fertilizers, or alerting farmers through a mobile or web interface. This innovative IOT-enabled smart farming solution improves crop yield, reduces water and fertilizer wastage, minimizes manual intervention, and supports sustainable agricultural practices. The invention is scalable, adaptable to diverse crop environments, and capable of integrating predictive analytics and decision-support models for future agricultural advancements."
Disclaimer: Curated by HT Syndication.
