Intelligent Irrigation Technique for LoRa Enabled Fog Assisted Smart Agriculture

Nowadays, the agricultural sector is facing significant challenges, and smart agriculture has emerged as a promising solution to address them. This approach involves advanced technologies, such as IoT, ML, and AI, to make farming more efficient and sustainable. One critical component of smart agriculture is smart irrigation, which helps farmers to conserve valuable resources while avoiding water stress in crops. In this paper, we propose and develop a micro service enabled Fog Server-based intelligent irrigation system to enhance existing methods. The aim of this work is to increase crop yield and reduce water wastage. Our proposed system collects various sensory data and control the irrigation system based on present soil moisture levels, and prediction of rainfall. We used LoRaWAN to communicate data from the sensor nodes to the fog server. Open source software tools, such as MQTT (mosquitto broker) and Node-Red are used to communicate the data between various micro-services present in fog server. Various Machine learning models are tested for rainfall prediction. Most appealing feature of this framework is it works in locations having Intermittent Internet connectivity.