LightAgro: Lightweight Blockchain IoT Based Fabrication for Smart Irrigation - Saha, Priya; Sinha, Ditipriya (Journal of Mobile Multimedia, 2025)
India is supposed to be the global agricultural powerhouse. Around three-quarters of Indian family rely on agriculture for their livelihood. Water is the most crucial resource that must be accounted for to create a better irrigation system. The introduction of IIoT 4.0 also expanded its contribution to smart irrigation (SI). IoT-based innovative irrigation management achieves optimum water-resource utilization, bridging the gap between cyber-physical Systems (CPS). This paper improves the prediction rate needed for irrigation by sensing different parameters like temperature, pH value, humidity, NPK fertilizer, and rainfall of the crop field. In this paper, Deep Learning, an AI-based proposed system, integrates remote sensor data to predict irrigation in intelligent agriculture correctly. As open-source technology is involved in decision-making, security and trust issues are at stake. We propose a shallow neural network model, namely, LightAgro autonomous network, to recover intruder issues. LightAgro outputs (local prediction) are securely signed using a lightweight secp256k1 curve for users’ authentication. The vast amount of sensor data stored in client-server architecture in traditional systems is challenging. The result shows ML accuracy of 85.26 % using Gradient boosting techniques.