An Intelligent IoT based Wireless Sensor Network for Monitoring Water Quality by using RNN in Real-Time
Sana Afreen1, Shashank Singh2, Sarika Singh3, Archana Dwivedi4, Vipin Kumar Chaudhary5
1Sana Afreen, Department of Computer Science and Engineering, Integral University, Lucknow (U.P), India.
2Dr. Shashank Singh, Assistant Professor, Department of Computer Science and Engineering, Integral University, Lucknow (U.P), India.
3Sarika Singh, Department of Information Technology, Madan Mohan Malviya University of Technology, Gorakhpur (U.P), India.
4Archana Dwivedi, Department of Computer Science and Engineering, Bansal Institute of Engineering and Technology, Lucknow (U.P), India.
5Vipin Kumar Chaudhary, Department of Computer Science and Engineering, Madan Mohan Malviya University of Technology, Gorakhpur (U.P), India.
Manuscript received on 29 August 2022 | Revised Manuscript received on 05 September 2022 | Manuscript Accepted on 15 September 2022 | Manuscript published on 30 September 2022 | PP: 37-42 | Volume-11 Issue-10, September 2022 | Retrieval Number: 100.1/ijitee.K76630991120 | DOI: 10.35940/ijitee.K7663.09111022
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Water uses is increasing day by day. As development continues, the demand for water is increasing. Water is require for daily routine, for irrigation, for fish and wildlife and for industrial use, not only water but pure water is require. This is a helpful approach to make people or authorities aware and alert about water quality in real-time situation. In this paper, the proposed technology helps to monitor the water quality in real time situation or environment. The technology such as Internet of Things, Wireless Sensor Network and Cloud Computing are used in this approach for water quality parameters (pH, minerals and Temperature) measuring in real-time environment. For water quality prediction and analysis, a training data set has been prepared and these training data sets use for categorize utility of water in different field. The sensor sensed the water parameters and send this sensed value to the cloud server for processing. These data compared with training data set. In this paper monitor data classify by using Naive Bayes and the utility of water can be predicted by Recurrent Neural Network. The resultant of this proposed approach are: it gives high accuracy and the response time of this approach is very less comparatively.
Keywords: WQM system, IoT, WSN, Cloud Computing.
Scope of the Article: Cloud Computing