Drinking Water Monitoring in Mosul City Using IoT

Al-Khashab, Yaareb; Daoud, Raid W.; Majeed, Mahmood Sh.; Yasen, Mohammed Hammed

doi:10.1109/iccista.2019.8830662

Cited by 14 publications

(9 citation statements)

References 2 publications

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“…Al-Khashab et al proposed a monitoring system of drinking water in Mosul City through the IoT using physiochemical sensors and Arduino UNO as the microcontroller. (4) They compared the results obtained using the proposed system and in the laboratory and found this system to be very efficient and useful in practice as the water could be tested instantly.…”

Section: Related Workmentioning

confidence: 99%

IoT-based Water Quality Monitoring

Sung¹,

Fadillah²,

Hsiao³

2021

Sensors and Materials

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Water pollution has become a major issue over the last few years. Constant water monitoring will be important in dealing with this issue since water is essential to human beings. The purpose of this research is to develop an effective IoT system for monitoring the quality of water in real time using physiochemical sensors. The system is implemented using Arduino as the microcontroller and turbidity, temperature, pH, conductivity, and total dissolved solid (TDS) sensors. The information from each sensor is sent over the internet. Experiments are performed on water quality data acquisition, online data transfer, monitoring, recording, and analysis. The results of the experiments show that the water sources in this study satisfy the parameters of good water quality. In addition, our team proposed a water quality model for running water based on diversion-method-related experiments.

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Section: Related Workmentioning

confidence: 99%

IoT-based Water Quality Monitoring

Sung¹,

Fadillah²,

Hsiao³

2021

Sensors and Materials

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“…Researchers use parameters such as DO, pH, temperature, EC, and turbidity for water quality monitoring. Researchers use a minimum of two (2) sensors for the corresponding elements in the water monitoring systems including pH sensors and TDS sensors or water temperature sensors [ 6 , 7 , 8 , 9 , 10 , 11 ]. Ultrasonic sensors can detect water quality parameters, integrating it with the WeMos D1 mini through its built-in Wi-Fi capabilities [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…An Arduino platform has an integrated development environment which makes it easy for users to develop their projects. Thanks to its simplicity and accessibility, most researchers have combined it with the sensors [ 6 , 8 , 9 , 10 ]. Moreover, utilizing the ThingSpeak IoT platform can also enhance the monitoring system’s features [ 7 , 9 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…Thanks to its simplicity and accessibility, most researchers have combined it with the sensors [ 6 , 8 , 9 , 10 ]. Moreover, utilizing the ThingSpeak IoT platform can also enhance the monitoring system’s features [ 7 , 9 , 12 ]. The monitoring system’s complexity can be extended to prediction systems that employ the collected data.…”

Section: Introductionmentioning

confidence: 99%

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An IoT Real-Time Potable Water Quality Monitoring and Prediction Model Based on Cloud Computing Architecture

Wiryasaputra,

Huang,

Lin

et al. 2024

Sensors

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In order to achieve the Sustainable Development Goals (SDG), it is imperative to ensure the safety of drinking water. The characteristics of each drinkable water, encompassing taste, aroma, and appearance, are unique. Inadequate water infrastructure and treatment can affect these features and may also threaten public health. This study utilizes the Internet of Things (IoT) in developing a monitoring system, particularly for water quality, to reduce the risk of contracting diseases. Water quality components data, such as water temperature, alkalinity or acidity, and contaminants, were obtained through a series of linked sensors. An Arduino microcontroller board acquired all the data and the Narrow Band-IoT (NB-IoT) transmitted them to the web server. Due to limited human resources to observe the water quality physically, the monitoring was complemented by real-time notifications alerts via a telephone text messaging application. The water quality data were monitored using Grafana in web mode, and the binary classifiers of machine learning techniques were applied to predict whether the water was drinkable or not based on the data collected, which were stored in a database. The non-decision tree, as well as the decision tree, were evaluated based on the improvements of the artificial intelligence framework. With a ratio of 60% for data training: at 20% for data validation, and 10% for data testing, the performance of the decision tree (DT) model was more prominent in comparison with the Gradient Boosting (GB), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) modeling approaches. Through the monitoring and prediction of results, the authorities can sample the water sources every two weeks.

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“…Since the values of the parameters were above the recommended range, it was determined that Balad city tap water is unsafe. Al-Khashab et al 16 measured the pH, TDS, and EC and discovered that they were 7.7-8.7, 226-302 mg/L, and 330-405 μs/cm, respectively, and that all the values are within the recommended ranges. Salman et al 17 were able to carry out a comprehensive radioactivity of 232 Th, 238 U, and 40 k. The NaI(Tl) detector was used to ascertain this.…”

Section: Introductionmentioning

confidence: 99%

Heat Production Rate and Radiation Hazard Indices from Radioactive Elements in Different Types of Natural Water in Nineveh Governorate, Iraq.

Al-sofy

Al-jomaily

2023

Baghdad Sci.J

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The current study sheds light on the measurement and estimation of the radioactivity of radionuclides (238U, 226Ra, 232Th, and 40k) in natural waters of different regions of Nineveh Governorate in Iraq.15 samples were collected from different sources of natural waters, where gamma-ray spectroscopy was used using NaI)TI) sodium iodide detector to determine the concentration of radioactivity in the samples. According to the results, the radioactivity concentration in the tested water sample were ranged from 0.36 ± 0.04-1.57 ± 0.09with an average value of 0.69 ± 0.06 Bq/l for 238U, and 2.9 ± 0.02-0.88 ± 0.03 with an average value of 0.65 ± 0.03 Bq/l for 226Ra Bq/l, and 0.48 ± 0.04-1.36 ± 0.06 with an average value of 0.88 ± 0.05 Bq/l for 232Th, while for 40K 13.00 ± 0.69-36.89 ± 1.12 with an average value of 25.1 ± 0.95 Bq/l, respectively. The results obtained from the water samples are below the safe and standard limits established by UNSCEAR. In addition to calculating the radiological hazard indicators that included Radium equivalent (Raeq), air absorbed dose rate (Dγ), effective annual equivalent dose rate (AEDE), indoor and outdoor radiation hazard (H) indices, lifetime cancer risk (ELCR), gonadotropin equivalent dose (AGDE), and ideal level index of gamma rays (Iγ) has been calculated. To verify its deleterious character. On the other hand, the results showed that the rate of heat production values ranged between 0.006-0.0015 µW/m3, which indicates a low rate of heat production and does not affect the temperature of the Earth's crust. Finally, In addition to physicochemical parameters such as PH, dissolved solids TDS, and electrical conductivity Ec. All tested data are within the permissible limit of WHO standards. The results of the current study can be used to provide essential baseline data for future epidemiological investigations and surveillance programs in the areas under study.

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Drinking Water Monitoring in Mosul City Using IoT

Cited by 14 publications

References 2 publications

IoT-based Water Quality Monitoring

IoT-based Water Quality Monitoring

An IoT Real-Time Potable Water Quality Monitoring and Prediction Model Based on Cloud Computing Architecture

Heat Production Rate and Radiation Hazard Indices from Radioactive Elements in Different Types of Natural Water in Nineveh Governorate, Iraq.

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