IoT based Data Sensing System for AutoGrow, an Autonomous greenhouse System for Precision Agriculture
Pavan Patil, Ramesh Kestur, Madhav Rao, Aswath C†
Abstract
Rising global average temperature is associated with widespread changes in weather patterns. India is identified as one of the highly vulnerable countries to climate change. Climate change poses a significant threat to Indian agriculture and food security, it also affects nutritional value within the crop. Paradoxically, Agriculture generates 19-29% of total greenhouse gas (GHG) emissions. Precision farming using an instrumented greenhouse which falls under the ambit of Controlled Environment Agriculture (CEA) presents a plausible solution option for climate resilient agriculture.Artificial Intelligence has reached breakthroughs in several areas but in agriculture artificial intelligence could be applied easily with data collection from various types of sensors. It is obvious to use AI also for agricultural purposes. The twin levers of an instrumented Greenhouse using IoT and AI provides interesting options for autonomous food production in CEA. We envisage AutoGrow, a Greenhouse system that incorporates AI/ML to perform the control function of optimizing the use of resources. Data for AI/ML is acquired through an IoT system with a multitude of sensors. In this work, we present an IoT based data sensing and data logging subsystem. The sub-system includes sensing a multitude of parameters that includes temperature, moisture, humidity, pH and the big 3 primary nutrients (NPK). Further, the solenoid valves are incorporated as actuators for the control operation of administering irrigation and water soluble nutrients. A prototype lab system is successfully built and tested. The lab prototype showcases all the features to sense, communicate, and perform effective irrigation and controlled supply of nutrients.