Development of digital viscometer based on Arduino to determine the viscosity of liquid

Suwardi, Suwardi; Haidul,; Ayatullah, Erik

doi:10.1063/5.0037489

Cited by 3 publications

(3 citation statements)

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“…Free fall is a type of straight motion occurring in an object under the influence of Earth's gravitational acceleration (Haidul et al, 2021). Equation 1 and 2 gives the position equation for a vertically falling object.…”

Section: Literature Review Free Fall Motionmentioning

confidence: 99%

“…Free fall is an object's motion phenomenon affected only by the earth's gravitational force (Schlegel et al, 2019). Free fall measurements include time to fall, distance to fall, velocity of the target, and gravitational acceleration (Haidul et al, 2021). These measurements must provide accurate data to support a more reliable decision-making process.…”

Section: Introductionmentioning

confidence: 99%

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YOLOv3 Algorithm to Measure Free Fall Time and Gravity Acceleration

Harlastputra,

Nasbey,

Suhendar

2023

Curr. STEAM Educ. Res.

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Computer vision methods as an alternative to sensors in modern measurements are feasible in physics experiments due to their speed, accuracy, and low cost. The You Only Look Once (YOLO) algorithm is widely used in computer vision because it detects object positions quickly and accurately. This research uses YOLO version 3 (YOLOv3) to compute an object’s falling time and gravitational acceleration. Two steps are performed in this study: first, the detection of predefined objects using YOLOv3, and second, the use of trained YOLOv3 to track the object's coordinate. According to the object tracking results, the object's falling time can be measured based on the object tracking results. The gravitational acceleration is calculated using the time data after the fall time of the object is measured. The measurement result of the fall time of the object will be compared with the data from the sensor. The result of the gravitational acceleration calculation is measured for its relative error against the value of 9.78150 m/s2, which is the value of gravitational acceleration in Jakarta city. The results show that YOLOv3 can accurately detect objects and measure free-fall motion, with a time measurement error of only 1.1 milliseconds compared to sensor measurements. The error obtained from the measurement of the Earth's gravity is 0.634%.

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Section: Literature Review Free Fall Motionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

YOLOv3 Algorithm to Measure Free Fall Time and Gravity Acceleration

Harlastputra,

Nasbey,

Suhendar

2023

Curr. STEAM Educ. Res.

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“…Understanding fluid behavior, improving process parameters, and ensuring product quality all rely on accurate viscosity measurement [3]. Traditional viscometers, on the other hand, frequently need manual operation and lack real-time data monitoring capabilities, which might limit their efficiency and comfort in a laboratory setting [4], [5]. To address these constraints, the integration of internet of things (IoT) technologies with viscosity measuring devices has received considerable interest.…”

Section: Introductionmentioning

confidence: 99%

IoT-based viscometer fabrication using the falling ball method for laboratory applications

Nofriandi,

Yulkifli,

Asrizal

et al. 2024

IJEECS

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This study outlines the production procedure of internet of things (IoT)- enabled viscometers designed for laboratory use. These viscometers utilize photodiode sensors, lasers, and falling ball techniques. The system is equipped with a temperature sensor that is utilized to quantify the impact of temperature on viscosity. The temperature sensor’s characterization yielded a R-square value of 0.999. The photodiode and laser sensors are utilized to operate a timer within the system, ensuring precise time measurement. The R-square value for the sensor characterization is 0.996. A viscometer equipped with an integrated IoT module for seamless wireless transmission of data. The photodiode timer sensor has an accuracy of 95.76% and a precision of 99.96%, while the temperature sensor has an accuracy of 99.43% and a precision of 99.93%. The viscometer transmits the measured viscosity data to the server using wireless technology. This IoT viscometer has the potential to enhance the efficiency and precision of liquid viscosity measurement in laboratory settings. Additionally, it enables real-time monitoring and data collection for subsequent analysis and research purposes.

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