Measurement of Physical Parameters of Water Quality in Real-Time Based on Arduino

Junaidi, Junaidi; Putra, T M; Surtono, Arif; Puazi, G A; Suciyati, Sri Wahyu; Firdaus, Iqbal; Rumiyanti, Leni

doi:10.1088/1742-6596/1751/1/012067

Cited by 9 publications

(7 citation statements)

References 2 publications

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“…III, the level of error and accuracy of DS18B20 sensor measurements reached an error value of 5.26%, with an accuracy of 94.734%. In another study [58] reported an error of 0.29%; [59] achieved a 5% error; [60] reported a 0.2% error; [61] error is 0.829%; [62] had a 3.00% error with accuracy below 85%. In the study [63], the sensor accuracy ranged from 95% to 99%.…”

Section: Testing the Error And Accuracy Of Ds18b20 Sensor Measurementsmentioning

confidence: 99%

IoAT: Internet of Aquaculture Things for Monitoring Water Temperature in Tiger Shrimp Ponds with DS18B20 Sensors and WeMos D1 R2

Satra,

Hadi,

Sujito

et al. 2024

Journal of Robotics and Control

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Cultivation of tiger prawns stands as a crucial sector in Indonesia's fisheries industry, significantly contributing to the country's foreign exchange. However, challenges persist in the cultivation process, particularly concerning suboptimal harvest outcomes. A critical factor in tiger prawn cultivation is the water temperature within shrimp ponds, a parameter directly influencing shrimp growth. The recommended normal temperature range is 28-31°C. Deviations from this range can adversely impact the shrimp's metabolic system and appetite, resulting in stress and potential mortality. Temperature fluctuations can lead to severe issues such as hindered growth, reduced productivity, and increased shrimp mortality. Real-time monitoring of air temperature emerges as a pivotal element in ensuring the success of shrimp farming. This research aims to provide a practical solution for shrimp cultivation by presenting a system that enables farmers to adjust air temperature in ponds in real-time through a user-friendly website application. The ability to promptly respond to abnormal temperature fluctuations empowers farmers to optimize cultivation conditions, thereby reducing shrimp mortality rates. The research focuses on creating a water temperature monitoring system for tiger prawn ponds using cloud storage through the Firebase platform. By implementing real-time temperature monitoring, financial risks for shrimp farmers can be mitigated, preventing losses attributed to temperature-induced shrimp mortality. The research utilizes the DS18B20 temperature sensor and WeMos D1 R2 as the control center. The website displays air temperature measurements, showcasing a high accuracy of 99% with a minimal error of 1.2%. This underscores the system's effectiveness in measuring air temperature both above and below the pond. The incorporation of IoT technology for monitoring water quality in ponds offers a practical and innovative approach to tiger prawn cultivation, with the potential to enhance production outcomes in each harvest.

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Section: Testing the Error And Accuracy Of Ds18b20 Sensor Measurementsmentioning

confidence: 99%

IoAT: Internet of Aquaculture Things for Monitoring Water Temperature in Tiger Shrimp Ponds with DS18B20 Sensors and WeMos D1 R2

Satra,

Hadi,

Sujito

et al. 2024

Journal of Robotics and Control

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“…Teknologi informasi memberikan dampak yang baik bagi perkembangan teknologi yang semakin canggih. Salah satu contohnya adalah system komunikasi serat optik [1]- [3]. Serat optik adalah saluran transmisi cahaya yang terdiri dari jenis serat optik plastik dan kaca.…”

Section: Pendahuluanunclassified

U-bend Optical Fiber to Determine Characteristics of pH Sensor

Yunus

2023

JTAF

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Determination of the characteristics of the pH sensor using U-shaped optical fiber was carried out with various varieties, namely length without a coat, indentation diameter, and the number of imperfections. Optical fiber as a light transmission medium is used as a sensor to detect the pH level of the solution. The sensor output is read on the OPM in the form of output power. The best characteristic of the pH sensor was obtained in the number of imperfections, namely number of imperfections 3 with a value range of 32.0 µW, a sensitivity of 3.2 µW/pH, and a resolution of 0.3 x 10-3 pH. The greater the power losses in the optical fiber sensor, the better the sensor characteristics. Determination of the characteristics of the pH sensor is very suitable to be carried out using U-shaped optical fiber in simple measurements and easy fabrication

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“…e water is sucked from the water reservoir and is fed into the process level tank with the use of a pump and transmitted to the pipeline system. Different setups for level recording, flow recording, and pressure recording are made to record the real-time data from the water distribution system [35,36] as shown in Figures 3, 4, and 5. e water distribution system is pilot scaled and used for real-time data monitoring based on pressure and flow sensors' feedback.…”

Section: Experimental Hardware For Water Distribution Systemmentioning

confidence: 99%

Prediction of Fault Occurrences in Smart City Water Distribution System Using Time-Series Forecasting Algorithm

Chenniappan

Gnanavel

Gunasekaran

et al. 2022

Mathematical Problems in Engineering

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The proposed research work is focused on forecasting the future requirements of water supply based on the current requirement of water and also identifying the possibility of occurrences of cracks and leaks using the ARIMA (autoregressive integrated moving average) model. The experiments were conducted using real-time experimental hardware. The pressure data obtained and their p -value is less than 0.05, which represents the stability of the data in the ARIMA model. The forecasted pressure data range between 0.451379 N/m2 and 2.022273 N/m2. The frequency of the forecasted pressure ranges between 1.706869 N/m2 and 3.065836 N/m2 (maximum peak) and −0.81046 N/m2 and 1.042164 N/m2 (minimum peak). Forecasted data of pressure at damaged condition lie between 2.880788 N/m2 and 3.29797 N/m2 and frequency ranges between 4.866227 N/m2 and 5.664348 N/m2. Similarly, future forecasted data of water requirement for the next 1 year range between 614.6292 (liters/week) and 620.0099 (liters/week), the frequency of the forecast value with maximum ranging from 617.0086 (liters/week) to 628.5465 (liters/week), and the minimum peaks ranging from 611.0967 (liters/week) to 612.2914 (liters/week). The above data are for a single water distribution pipeline.

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Measurement of Physical Parameters of Water Quality in Real-Time Based on Arduino

Cited by 9 publications

References 2 publications

IoAT: Internet of Aquaculture Things for Monitoring Water Temperature in Tiger Shrimp Ponds with DS18B20 Sensors and WeMos D1 R2

IoAT: Internet of Aquaculture Things for Monitoring Water Temperature in Tiger Shrimp Ponds with DS18B20 Sensors and WeMos D1 R2

U-bend Optical Fiber to Determine Characteristics of pH Sensor

Prediction of Fault Occurrences in Smart City Water Distribution System Using Time-Series Forecasting Algorithm

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