Arduino based Automated Viscometer for Oil Health Monitoring

Srinivasan, Aparajith; Sharavanee, D P; Shwetha, M P; Surendran, Subu; Suryaprakash, S.; W, Jino Hans

doi:10.1109/i-smac49090.2020.9243310

Cited by 4 publications

(1 citation statement)

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“…Previous studies have focused on manufacturing a fluid viscosity measuring instrument using an Arduino microcontroller with a photodiode sensor, but the data analysis and reading still relied on a serial monitor or LCD. Furthermore, a viscometer system based on a hall effect magnetic sensor was also made, but data readings still used a serial monitor or LCD [9]- [11]. The system is also equipped with a temperature sensor to see the fluid's viscosity behavior which is affected by temperature.…”

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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Section: Introductionmentioning

confidence: 99%