IoT-Enabled Pneumatic Piston Load-Cell Water-Level Sensing and LoRa Mesh Networking for Automated Alternate Wetting and Drying (AWD) Irrigation Management in Rice Cultivation

Alternate Wetting and Drying (AWD) is a water saving rice irrigation method known to decrease irrigation water inputs by up to 38% with little impact on the yield. In practice, though, AWD application faces limitations due to the need for regular in-field visits, where a farmer comes to a water permeable tube placed in the field and measures the water depth with a tape measure one or two times per day. In this work we propose an automation of the classic AWD monitoring tube with the help of an Internet of Things (IoT) sensor based on the pneumatic load cell transducer: rising water level compresses the sealed air column inside the pipe, the air pressure is transferred through a narrow riser pipe to a roadside pole where the compressed air displaces a piston (syringe barrel in the prototype), the displacement is measured with a load cell connected to an Arduino Nano which sends the data via LoRa multi-hop wireless network to a mother node with GSM connectivity and cloud server. The mobile application integrates the live water-depth feed, planting date input, rice growth stage specific water requirement model, and free weather forecast data to give suggestions on or automatically control the pump operation. The sensor is completely isolated from standing water, does not require any active power consumption for ranging like ultrasonic and vision sensors, and scales across the field independently of the presence of gateway nodes via mesh communication.