Abstract

Water is the most significant sources for human life, but, it is in serious threat of contamination by life itself. The protection and availability of drinking-water are major worries throughout the globe. In this work,anIOT based solution isintroduced to check and predict the water quality and alert the user before the water gets polluted. The proposed system uses IoT and optimized neural network for prediction. It consists of various embedded sensors like conductivity, pH, turbidity and color. The measured sensor values are stored in the database and further directed for prediction analysis. The Cat swarm optimization (CSO) based neural network algorithm is used for forecasting thequality result. The proposed system alerts the user when any of themeasured parameters are lesser than the fixed thresholds. This technique can also be implemented in water plants, rivers and industries.

Highlights

  • Water quality has become more severe threats

  • The Cat swarm optimization (CSO) based neural network algorithm is used for forecasting thequality result

  • The Back Propagation Neural Network has been regularly applied as a pragmatic nonlinear incredible framework anticipating and showing mechanical get together, regardless, there are a couple of distortions

Read more

Summary

Introduction

Water quality has become more severe threats. The quality expectation of water, as a basic part of the water environment controlling, is to find the consistency for the determined file with the time utilizing certain guaging approaches, and to understanding the development style of the water quality dependent on the past information. Neural networksare generally founded on the development of neurons They include various layers with interrelated hubs. The info layer receipts in the anticipating boundaries and the yield layer show the expectation dependent on the information. They repeat over each preparation information point and disentangle the model by giving and refreshing the weight on every hub of each layer. An IOT based system is proposed to check and predict the water quality and alert the user earlierto avoid water contamination. The proposed system uses IoT and optimized neural network for prediction. It consists of various embedded sensors like conductivity, pH, turbidity and color. The cat swarm optimized neural network algorithm is used for forecasting the quality result

Preliminaries
Related work
Proposed system
Hardware design
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.