Development of Lora P2P Network for Autonomous Seawater Quality Monitor for Green Powered Desalination Project

Abstract

Scarcity of freshwater pushes countries impacted by climate change to investigate new sources of supply. Desalination plants powered by renewable energy can be the solution for a tropical developing country. Collection and treatment of seawater to produce freshwater generate an imbalanced water mass. In the case of a Reverse Osmosis Desalination Plant which pumps seawater to produce freshwater and brine as waste, the most important factor is the seawater quality, only available by observation. The design of a plant and its execution will depend on factors such as ambient temperature, salinity, and TDS. The main needs for a good multi-probe marine observation system are low energy consumption, simple monitoring, and coverage of a large area. For the sake of autonomy and ease of use, a functional and robust circuit can be set up using calibrated probes, micro-controllers, and small programmable boards. The use of programmable boards and connected probes are set up as network ‘nodes’ to send in-situ data measured from the water body. These nodes send the data using radio signal with LoRa protocol to a ‘gateway’ to store or transfer them. The parameters were measured at different time intervals, water depths, and distances from the coastline to observe how said factors affect the measurements. The results from the data collected are used to compare ocean modelling and satellite data. We present in this study the implementation of a long-range wireless autonomous sensor network and first validation tests in Jamaica and how it fills lack of information for a desalination project. Results indicate a good correlation between measure, modelling, and remote sensor. LoRa P2P network allows at an affordable price continuous monitoring of remote areas with great autonomy and resilience; results showed a successful transmission of > 80% within the network.