Development of An IoT-LoRaWAN Sensor-Enabled Photobioreactor System for Characterizing the Growth of Microalgae

Abstract

Microalgae cultivation is gaining attention in the food, pharmaceutical and biofuel sectors due to its potential to produce high-value products. However, relying on human interventions to monitor microalgae growth is labor-intensive and time-consuming. This study developed an Internet-of-Things (IoT) acquisition and monitoring system based on long-range wide area network (LoRaWAN) technology that integrates electrical conductivity (EC), oxidation-reduction potential (ORP), pH and temperature sensors to automate real-time microalgae growth monitoring. The data obtained from the sensors was sent to the InfluxDB cloud server for time-series database storage and visualized in the Grafana dashboard. The result of the study showed improvement in the efficiency and precision of monitoring, thus reducing reliance on manual data measurement. Incorporation of the system in microalgae cultivation also presents a source for continuous time series microalgae growth data. This approach will lead to strengthened automation in smart aquaculture and may provide a means to optimize microalgae productivity.