Automated System for Detection of Floating Water Pollutants using Deep Learning Framework Metric for Sustainable Life

Journal: GRENZE International Journal of Engineering and Technology
Authors: Neeta Shirsat, V. Nirmalrani
Volume: 10 Issue: 2
Grenze ID: 01.GIJET.10.2.631 Pages: 1784-1789

Abstract

Massive increase in water pollutants is a critical issue found in sustainable life. Rise in floating water pollutants from million to trillion indicates failure of existing water pollutants detection system. Existing solutions for detection and classification of water pollutants requires massive human interventions. Automated system for detecting floating water pollutants will surely help authorities to detect and removal of water pollutants effectively and efficient manner. The objective of proposed Automated system for floating water pollutant detection system is to minimize human interventions to avoid delay in removing the hazardous waste from water. Proposed system will significantly detect concentration of hazardous waste and notify the local authorities and civilians for further actions. As notification is based on concentration of hazardous waste it will surely help authorities to take proper decision without continuous manual engagement.

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