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.