Simulation of Smart Water Quality Monitoring Device
Nidhi Mishra1, Sanjay Mohite2
1Nidhi Mishra*, Research Scholar, Shri JJT University Vidyanagari, Jhunjhunu (Rajasthan), India.
2Prof. Sanjay Mohite, Professor, Department of Power Electronics, Jayawantraao Sawant College of Engineering, Pune (Maharashtra), India.
Manuscript received on February 12, 2022. | Revised Manuscript received on February 22, 2022. | Manuscript published on April 30, 2022. | PP: 21-23 | Volume-11 Issue-4, April 2022. | Retrieval Number: 100.1/ijeat.D34140411422 | DOI: 10.35940/ijeat.D3414.0411422
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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 contamination is one of the primary concerns for green globalization. Environmental monitoring is a fascinating system that has become increasingly important in 21st-century human life. To ensure a safe supply of drinking water and other water-related activities, water quality must be monitored in real time. This paper depicts a stage progression and plan for a small amount of effort. This research makes use of the Arduino Uno microcontroller, as well as a variety of sensors connected to the platform. The device, which is made up of a number of sensors, is used to determine the physical and chemical properties of water in various locations. Water quality factors such as pH, temperature, and Chlorine can be calculated. When estimated values were compared to W.H.O. standards, it was discovered that a cost-effective device for water quality management was required. In this paper we are trying to measure pH value for drinking water, temperature and chlorine content with the help of ORP sensor through simulation and then compared to standard value given by WHO. In this research paper our aim is to develop a system to evaluate the water quality based on simulation. Using a sensor we can collect data on various water quality parameters with minor variations. Following that, we can perform the necessary qualitative comparisons. It has also proven to be an effective tool for determining the impact of contaminated water. It is a effective tool for comparing data. Here we have used only three sensors pH , Temperature sensor and ORP sensor.
Keywords: IoT, Water Quality, Sensors, Cloud Computing, Machine Learning
Scope of the Article: Machine Learning