Autonomous UAV-Mounted LoRaWAN System for Real-Time Monitoring of Harmful Algal Blooms (HABs) and Water Quality

Harmful algal blooms (HABs) frequently occur in coastal and inland water bodies, resulting in detrimental health and economic consequences. In freshwater, HABs are often dominated by cyanobacteria (CyanoHABs or cHABs), which produce a suite of secondary metabolites ranging from taste and odor compounds to liver and neurological toxins. Recently, uncrewed aerial vehicles (UAVs) have emerged as a cost-effective remote sensing solution for using imaging cameras to monitor the distribution of HABs. However, most of these systems are unable to concurrently measure crucial water parameters, requiring additional in situ measurements and sample collection. The UAV system developed in this work presents a comprehensive platform that integrates multiple water sensors, including near-infrared (NIR) multispectral cameras and temperature, pH, and turbidity sensors. The integrated sensor system can not only monitor HAB distributions but also measure essential water quality parameters. In addition, the electromechanical 3-D-printed water sampling structure is designed to collect water samples for laboratory analysis of chemical and biological samples. To ensure real-time data transmission, a long-range wide area network (LoRaWAN) is developed. An ArcGIS database is implemented for water quality and HAB distribution mapping. Comprehensive field tests have been performed for system performance validation and assessment.