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Item Real-time water quality monitoring for distribution networks in IoT environment(Inder Science, 2022) Gupta, Raj Kumar; Gupta, Karunesh KumarWater 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.Item Smart Water Quality Monitoring System for Distribution Networks(SSRN, 2019-06) Gupta, Raj Kumar; Gupta, Karunesh KumarDrinking water quality monitoring is essential these days as the available water is polluted and can cause several diseases like cholera, diarrhea, dysentery, etc. This paper presents a low-cost wireless water quality monitoring system based on Arduino and Zigbee Module. Water quality parameters for monitoring is decided by the Central Pollution and Control Board, New Delhi, India. The water quality sensors are interfaced with the Arduino board through signal conditioning circuit. Acquired data is sent to the server over the wireless network through the Zigbee module. At the server, Raspberry Pi is used for data receiving and results have been shown on the graphical display.Item Raspberry Pi-based smart sensing platform for drinking-water quality monitoring system: a Python framework approach(Copernicus Publication, 2019) Gupta, Raj Kumar; Gupta, Karunesh KumarThis paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters was made based on guidelines of the Central Pollution and Control Board (CPCB), New Delhi, India. A graphical user interface (GUI) was developed for providing an interactive human machine interface to the end user for ease of operation. The Python programming language was used for GUI development, data acquisition, and data analysis. Fuzzy computing techniques were employed for decision-making to categorize the water quality in different classes like “bad”, “poor”, “satisfactory”, “good”, and “excellent”. The system has been tested for various water samples from eight different locations, and the water quality was observed as being good, satisfactory, and poor for the measured water samples. Finally, the obtained results were compared with the benchmark for authentication.Item Water Quality Index Calculation: Switching from MATLAB Fuzzy Toolbox to Python for Real-Time Implementation(IEEE, 2020) Gupta, Raj Kumar; Gupta, Karunesh KumarWater 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.Item Development of Cyber-Physical Systems for Water Quality Monitoring in Smart Water Grid(Springer, 2022-05) Gupta, Raj Kumar; Gupta, Karunesh KumarThere are many challenges while developing a smart city, such as air/water quality monitoring, water resource management, power grid implementation, and transport management. Water quality monitoring is one of them in which many researchers and scientists showed interest. The current water distribution systems always face leakage, failure, and maintenance delays due to the unavailability of real-time monitoring in distribution systems, which results in a high amount of water wastage. This can be solved by implementing a smart water grid. This paper proposes a solution for water quality monitoring for distribution systems in a real-time environment based on low-cost commercial off-the-shelf modules. Various water quality parameters were monitored from the developed setup. The proposed architecture can log, analyze data, make decisions, and remotely represent the data. The data obtained from various sensing nodes were uploaded to the cloud, a service provided by Amazon Web Services (AWSs). Experimental results show that the proposed low-cost sensing network can be an ideal early warning system in smart cities.Item Raspberry Pi-based smart sensing platform for drinking-water quality monitoring system: a Python framework approach(DWES, 2019) Gupta, Raj Kumar; Gupta, Karunesh KumarThis paper proposes the development of a Raspberry Pi-based hardware platform for drinking-water quality monitoring. The selection of water quality parameters was made based on guidelines of the Central Pollution and Control Board (CPCB), New Delhi, India. A graphical user interface (GUI) was developed for providing an interactive human machine interface to the end user for ease of operation. The Python programming language was used for GUI development, data acquisition, and data analysis. Fuzzy computing techniques were employed for decision-making to categorize the water quality in different classes like “bad”, “poor”, “satisfactory”, “good”, and “excellent”. The system has been tested for various water samples from eight different locations, and the water quality was observed as being good, satisfactory, and poor for the measured water samples. Finally, the obtained results were compared with the benchmark for authentication.Item Real-time water quality monitoring for distribution networks in IoT environment(Inder Science, 2022-04) Gupta, Karunesh Kumar; Gupta, Raj KumarWater 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.Item Development of Cyber-Physical System for Water Quality Monitoring in Smart Water Grid(Springer, 2022-05) Gupta, Karunesh Kumar; Gupta, Raj KumarThere are many challenges while developing a smart city, such as air/water quality monitoring, water resource management, power grid implementation, and transport management. Water quality monitoring is one of them in which many researchers and scientists showed interest. The current water distribution systems always face leakage, failure, and maintenance delays due to the unavailability of real-time monitoring in distribution systems, which results in a high amount of water wastage. This can be solved by implementing a smart water grid. This paper proposes a solution for water quality monitoring for distribution systems in a real-time environment based on low-cost commercial off-the-shelf modules. Various water quality parameters were monitored from the developed setup. The proposed architecture can log, analyze data, make decisions, and remotely represent the data. The data obtained from various sensing nodes were uploaded to the cloud, a service provided by Amazon Web Services (AWSs). Experimental results show that the proposed low-cost sensing network can be an ideal early warning system in smart cities.