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Author: search.filters.author.Gupta, Karunesh KumarSubject: search.filters.subject.Water Quality

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    Water Quality Index Calculation: Switching from MATLAB Fuzzy Toolbox to Python for Real-Time Implementation
    (IEEE, 2020) Gupta, Raj Kumar; Gupta, Karunesh Kumar
    Water quality assessment has always been of primary importance before consumption as most of the available water is polluted, which could transmit several waterborne diseases. Water Quality Index (WQI) is a unique single value to determine overall water quality. WQI summarizes the water quality parameters in a single value. MATLAB fuzzy is the standard toolbox to implement the water quality index. The user has to determine only the inputs as different water quality parameters and the membership functions based on the complexity of the application. This approach is offline, as it cannot be implemented in real-time. An alternate method may be the WQI measurement in the Python framework for real-time implementation. In this paper, we are trying to find out that it is possible to switch from MATLAB fuzzy toolbox to the Python framework for real-time implementation. The WQI measurement is performed in both the fuzzy toolbox from MATLAB® and Python 3.4. Based on the results, a comparative study has been done, and the switching possibility is found out.
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    Real-time water quality monitoring for distribution networks in IoT environment
    (Inder Science, 2022-04) Gupta, Karunesh Kumar; Gupta, Raj Kumar
    Water quality has always been a significant concern worldwide as a large portion of accessible water is either contaminated or polluted, which can spread serious diseases like dysentery, diarrhoea and cholera. Before consumption, the water quality should be tested to reduce the risk of infection. In real-time applications, the traditional approach for water quality monitoring is not appropriate, as on-site water sample collection is often a cost-intensive and time-consuming process. This paper introduces a real-time assessment of water quality parameters in distribution systems employing Raspberry Pi and Arduino development boards. The parameters were chosen based on the different categories identified by the Central Pollution and Control Board, Government of India. An Arduino development board was used at the sensing node for water quality sensor interfacing, data acquisition, and transmission to the wireless sensor network via Zigbee. Raspberry Pi was used at the server to collect data and upload data on the cloud platform. The 'Thingspeak' cloud platform was used for IoT implementation. The results were validated with the reference instrument.