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Timer-Based Capacitance-to-Voltage Converter
(2026-03-01)
Kaewpoonsuk, Anucha
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Tokampang, Sudarat
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Sisuk, Noppadon
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Rerkratn, Apinai
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Petchmaneelumka, Wandee
This article presents the design and analysis of a capacitance-to-voltage converter based on 555-timer Integrated Circuits (ICs) as the core design element. The circuit structure consists of two primary active components: two 555-timer ICs connected in conjunction with a low-pass filter circuit. The first 555-timer IC operates in astable mode to generate a signal that controls the timing of the second IC. The target capacitor or capacitive sensor to be measured is connected to the second 555-timer IC, which operates in monostable mode. The output signal from the second 555-timer IC is then converted into a DC voltage output using a low-pass filter circuit. The circuit was tested using laboratory capacitors in the range of 52.72 pF to 807.61 pF, and the data were analyzed using Microsoft Excel. The results showed excellent agreement with the measurements obtained from the GW INSTEK LCR-819. The maximum uncalibrated error was found to be −3.32% of full scale. After applying linear curve fitting in Excel, the maximum error was reduced to 0.92% of full scale, confirming the effectiveness of the calibration approach. Furthermore, the circuit was applied to measure the moisture content of paddy rice using a cylindrical capacitive sensor within the moisture range of 12.1% to 23.2%. The experimental data were fitted to a derived equation, which was then used to predict rice moisture content, producing results that corresponded closely with those obtained from the KETT PM-450 grain moisture meter.
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DEVELOPMENT OF AN EMBEDDED EXERCISE POSTURE PREDICTION SYSTEM FOR OFFICE SYNDROME USING MACHINE LEARNING
(2024-12-01)
Sisuk, Noppadon
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Onkhong, Tada
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Kaewpoonsuk, Anucha
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Wardkein, Paramote
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Prompak, Kriangsak
Office syndrome is a condition with a high prevalence among people of working age and an upward tendency. In this study, a wearable device implant based on machine learning will be created for exercise of office syndrome. Developing a machine learning model that can distinguish 3 exercise postures for implantable devices was the objective of the study. The Edge Impulse online software was used for data collecting, preprocessing, training, and testing. After that, the model was successfully installed and tested on an Arduino Nano 33 BLE microcontroller. In addition to designing embedded systems, this work also developed applications through the App Inventor program for exercising properly. From testing the system, the model showed an average classification accuracy of 97.6% of exercise postures. The results of testing the embedded system in conjunction with the presented application on 10 subjects showed that the system was able to provide predictive accuracy for wrist exercises, shoulder exercises and stretch exercises with 95%, 97%, and 93%, respectively.
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Resistive-Sensor Interfacing Circuit for Remote Measurement Using CFOA
(2024-01-01)
Petchmaneelumka, Wandee
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Rerkratn, Apinai
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Tammaruckwattana, Sirichai
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Kaewpoonsuk, Anucha
An alternative approach to implementing an interfacing circuit for resistive sensor-based remote measurement is presented. The proposed technique uses a Current Feedback Operational Amplifier (CFOA) as an active building block to produce an output voltage linearly related to the resistance of the sensor. Moreover, the accuracy of the output voltage is improved by the enhancement of CFOA. In addition, the proposed circuit provides compensation for the effects of lead-wire resistance. The performance of the proposed technique is discussed in detail and confirmed by PSPICE program simulation and experimental implementation. The resistance decade box is used in the experiment. The maximum error on the output voltage of the experimental results is about 0.4234 %. The experimental results show that the proposed technique provides good performance.
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Real-time seafood quality monitoring system using interdigital sensor
(2020-01-01)
Kaewpoonsuk, Anucha
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Luangpol, Amata
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Prasitmeeboon, Pitcha
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Rerkratn, Apinai
Many studies showed that seafood consumption contains many health benefits. However, the spoilage of such products causes the vast economic loss each year. An effective monitoring and inspection system for quality is required during the storage of these products. Most existing methods for such inspection require laboratory tests. In this study, the interdigital sensor was developed and applied to inspect the spoilage of seafood. The sensor was designed to monitor the change of impedance during spoilage progression of seafood. The result revealed that impedance of liquid decreased overtime. This coincides with the fact that spoilage of seafood generates ammonium ion which causes decrease in the impedance of the liquid. The designed sensor was then merged with the proposed system which consists of a sine wave circuit, a voltage control current source circuit, an interdigital sensor, an amplifier circuit, a rectifier circuit, a low-pass filter circuit, a comparator circuit and a display circuit. These circuits adjusted the signals received from the sensor to be proper to the application. The experiment was designed to have conditions similar to the real-world situation of how seafood is stored. The experimental results showed that the proposed system effectively indicated the change of seafood quality.

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