Using Lora P2P Network for Autonomous Seawater Quality Monitor for Green Powering Desalination Plant
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 tropical developing country. Collection and treatment of sea water to produce freshwater generates unbalance of the water mass. Management of an industrial plant, particularly those which work with intermittent energy, needs continuous and accurate monitoring. Observation is a key factor to determine the yield and energy cost reduction.
In case of a Reverse Osmosis Desalination Plant which pumps sea water to produce freshwater and brine as waste, the most important factor is the sea water quality. The design of a plant and its execution will depend on those factors and other factors such as ambient temperature and humidity.
Main needs for a good multi-probe observation system are the low energy consumption, simple monitoring and coverage a large marine area. For the sake of autonomy and ease of use, a functional and robust circuit can be setup using calibrated probes, micro-controllers and small-board computers. The use of programmable boards and connected probes are set up as ‘nodes’ to send particular data measured from the water body in this case, seawater. These nodes send the data using LoRa protocol to a ‘gateway’ to store or transfer them to a secured sever.
The data is 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 long range wireless autonomous sensor network and first validation tests. Results indicate 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.