A Proposed Optimization Model for Water Quality Prediction in Internet of Things Environment

Gopal Chaudhary, Puneet Singh Lamba, Deepali Virmani

VIPS-TC, School of Engineering & Technology, New Delhi, India

Emails: Gopal.chaudhary88@gmail.com; puneet.lamba@vips.edu; deepalivirmani@gmail.com

Abstract

The application of industrialization and urbanization strategies results in the proliferation of waste products in water resources which is a serious public challenge. They have resulted in calls for advanced technologies of water quality mitigation and monitoring, as emphasized in the sustainable development objectives. Now, environmental engineering researcher is looking for a more complex process of implementing practical assessments and of monitoring the quality of ground and surface water that is quantifiable to human beings over different locations. Many current techniques use the Internet of Things (IoT) for water quality assessment and monitoring. This paper explores the proposal of African Buffalo Optimization with Deep Belief Network for Water Quality Prediction (ABODBN-WQPR) model in an IoT environment. The presented proposed model majorly concentrates on the identification of water quality.

Keywords: Internet of Things; Water quality prediction; Deep learning; Artificial buffalo optimization; Deep belief network; Hyperparameter optimizer