A SYSTEM TO IDENTIFY THE CHEMICAL INDICATORS OF WATER WITH UNMANNED SURFACE VEHICLE

Abstract

The protection of the water's quality is an essential component of the planning, control, prevention, and preventative actions that must be taken to reduce the pollution of the water and the deterioration of aquatic habitat. Monitoring the water's quality on a consistent basis is an essential activity that contributes to keeping track of the hydrological particulars of any body of water. Many surviving systems and methods have been shown to be ineffective in achieving the same purpose, and only a small handful of other conventional methods have shown a remarkable outcome that has helped to reinstate and keep up water resources from piles of nutrients and organic composites that cause quality degradation. However, the figures collected from all corners of the world suggest that there is an immediate demand for an upgrade in the monitoring system for water quality. Based on the findings of the survey, the concept presented here entails the suggestion of a unique system that is able to maintain tabs on the quality of water, hence assisting the ongoing pollution control trends.. In this paper, a methodical approach is suggested for collecting the parametric quality indicators, most of which are chemical, which then leads to the production of a characteristic drawing for each of the variables relevant to the specific water resource that is the subject of the observation. The information that was gathered is, to put it another way, coupled with clouds. The suggested approach eliminates the most significant drawbacks of the present techniques, which results in an increase in the effectiveness of monitoring water quality and a reduction in water pollution.

Keywords

• water quality monitoring
• internet of aquatics
• machine learning
• internet of things
• chemical indicators
• unmanned surface vehicle.