Low-cost dimensional measurement using an Arduino embedded system with real-time logging via Microsoft Excel Data Streamer

Main Article Content

Worapong Phongphattarawut
Surachai Nampromma
Jittiwat Nithikarnjanatharn

Abstract

This research aimed to develop a low-cost and user-friendly dimensional measurement method using an Arduino-based embedded system integrated with Microsoft Excel Data Streamer for real-time data logging. The system was designed to address the limited accessibility to high-precision measuring instruments due to their high cost. The prototype consisted of an Arduino board, a rotary encoder, an LCD-I²C display, and a signal conditioning circuit, with data transmitted to Excel in real time. Calibration was conducted using a Dial Test Indicator, and measurements were performed on 30 sample workpieces, with results compared against a standard measuring instrument. Statistical analysis (t-test, p>0.05) indicated no significant difference between the embedded measurement system and the standard instrument, demonstrating that the developed system achieved satisfactory accuracy and reliability. The system effectively minimized manual recording errors, enhanced data accessibility for general users, and supported applications aligned with the principles of Industry 4.0.

Article Details

How to Cite
Phongphattarawut, W., Nampromma, S., & Nithikarnjanatharn, J. (2025). Low-cost dimensional measurement using an Arduino embedded system with real-time logging via Microsoft Excel Data Streamer. RMUTSB ACADEMIC JOURNAL, 14(1), 268561. https://doi.org/10.64989/rmutsbj.2026.268561
Section
Research Article

References

Akhtar, M. U., & Iqbal, M. T. (2024). Development and evaluation of an Arduino-based data logging system integrated with Microsoft Excel for monitoring on-grid photovoltaic systems. European Journal of Electrical Engineering and Computer Science, 8(3), 29-37. https://doi.org/10.24018/ejece.2024.8.3.622

Al Mamun, M. R., Ahmed, A. K., Upoma, S. M., Haque, M. M., & Ashik E Rabbani, M. (2025). IoT enabled solar powered smart irrigation for precision agriculture. Smart Agricultural Technology, 10, 100773. https://doi.org/10.1016/j.atech.2025.100773

Demetillo, A. T., Japitana, M. V., & Taboada, E. B. (2019). A system for monitoring water quality in a large aquatic area using wireless sensor network technology. Sustainable Environment Research, 29(1), 12. https://doi.org/10.1186/s42834-019-0009-4

Egho-Promise, E., Sitti, M., Hutchful, N., & Agangiba, W. A. (2024). IoT-enhanced weather monitoring system: Affordable hardware solution for real-time data collection storage and predictive analysis. European Journal of Computer Science and Information Technology, 12(1), 43-56. https://doi.org/10.37745/ejcsit2013/vol12n14356

Geck, C. C., Alsaad, H., Voelker, C., & Smarsly, K. (2024). Personalized low-cost thermal comfort monitoring using IoT technologies. Indoor Environments, 1(4), 100048. https://doi.org/10.1016/j.indenv.2024.100048

Gómez-Gijón, S., Salmerón, J. F., Falco, A., Loghin, F. C., Lugli, P., Morales, D. P., Rodriguez, N., & Rivadeneyra, A. (2025). Printed RFID sensing system: The cost-effective way to IoT smart agriculture. Computers and Electronics in Agriculture, 232, 110116. https://doi.org/10.1016/j.compag.2025.110116

Kittidecha, C., Saramath, S., & Narapinij, P. (2025). Plant layout improvement of the stainless-steel cookware manufacturing using ALDEP. RMUTSB Academic Journal, 13(1), 57-70. https://doi.org/10.64989/rmutsbj.2025.265274 (in Thai)

Koomngern, A., & Chaiyabut, N. (2025). Development of an automated system for beverage preparation to assist bartenders. RMUTSB Academic Journal, 13(2), 237-252. https://doi.org/10.64989/rmutsbj.2025.268136 (in Thai)

Murugesan, L. J., & Chettiar, S. R. S. (2021). Design and implementation of intelligent classroom framework through light-weight neural networks based on multimodal sensor data fusion approach. Revue d'Intelligence Artificielle, 35(4), 291-300. https://doi.org/10.18280/ria.350403

Parkavi, V., K. J., & Veluswamy, P. (2024). Enhancing photovoltaic systems with integrated thermoelectric generators: Real-time optimization through arduino implementation. Materials Circular Economy, 6(1), 61. https://doi.org/10.1007/s42824-024-00141-w

Rose, T., Ali, N., & Dong, Y. (2025). Design and development of an IoT-based dendrometer system for real-time trunk diameter monitoring of Christmas trees. Smart Agricultural Technology, 10, 100765. https://doi.org/10.1016/j.atech.2024.100765

Saputra, A. D. S., Hindarto, D., & Haryono, H. (2023). Supervised learning from data mining on process data loggers on micro-controllers. Sinkron: Jurnal dan Penelitian Teknik Informatika, 7(1), 157-165. https://doi.org/10.33395/sinkron.v8i1.11942

Somogyi, A., Kelemen, A., Mellár, J., & Mingesz, R. (2024). Event-driven kinematic measurements using BBC micro: Bits programmed in C++. Central-European Journal of New Technologies in Research, Education and Practice, 6(1), 35-58. https://doi.org/10.36427/CEJNTREP.6.1.7135

Xiong, X., Liu, Z., Kan, K., Zhu, Y., Zhang, W., & Fang, X. (2025). Design and implementation of a digital calibration certificate web service system based on microservice architecture. Measurement: Sensors, 38(S), 101487. https://doi.org/10.1016/j.measen.2024.101487