RaspberryPi‐Arduino (RPA) powered smart mirrored and reconfigurable IoT facility for plant science research. Issue 1 (11th February 2021) - Arunachalam, Ajay; Andreasson, Henrik
Abstract : Continuous monitoring of crops is critical for the sustainability of agriculture. The effects of changes in temperature, light intensity, humidity, pH, soil moisture, gas intensities, etc. have an overall impact on the plant growth. Growth chambers are environmental controlled facilities which needs to be monitored round‐the‐clock. To improve both the reproducibility, and maintenance of such facilities, remote monitoring plays a very pivotal role. An automated re‐configurable & persistent mirrored storage‐based remote monitoring system is developed with low‐cost open source hardwares and softwares. The system automates sensors deployment, storage (database, logs), and provides an elegant dashboard to visualize the real‐time continuous data stream. We propose a new smart AGRO IoT system with robust data acquisition mechanism, and also propose two software component nodes, (i.e., Mirroring and Reconfiguration) running as an instance of the whole IoT facility. The former one is aimed to minimize/avoid the downtime, while the latter one is aimed to leverage the available cores, and better utilization of the computational resources. Our system can be easily deployed in growth chambers, greenhouses, CNC farming test‐bed setup, cultivation plots, and further can be also extended to support large‐farms with either using multiple individual standalone setup as heterogeneous instances of this facility, or by extending it as master‐slave cluster configuration for communication as a single homogeneous instance. Our RaspberryPi‐Arduino (RPA) powered solution is scalable, and provides stability for monitoring any environment continuously at ease. Abstract : The developed AGRO IoT platform is device‐agnostic, thereby making it easy to analyze the multi‐sensor data. The prototype allows for connecting different sensors, data storage, and dashboard for visualizing the incoming raw stream of continuous data with fancy gauges and time charts. Easy to use, and adapt. All the complexities are handled at the back‐end. No more complex procedures for getting started on‐the‐go.