Bridging theory and practice in motion detection: A reflective evaluation of PIR sensing systems by engineering students

Authors

  • Nazhif Kulliyyah of Engineering, International Islamic University Malaysia Author
  • M. Danish P. Zaharudin Kulliyyah of Engineering, International Islamic University Malaysia Author
  • M. Iman A. Hamidun Kulliyyah of Engineering, International Islamic University Malaysia Author
  • Z. Nazhan Zulazwer Kulliyyah of Engineering, International Islamic University Malaysia Author
  • M. Naufal Mohtar Kulliyyah of Engineering, International Islamic University Malaysia Author
  • Luhur Bayuaji Faculty of Data Science and Information Technology, INTI International University Author
  • Hazlina Md. Yusof Kulliyyah of Engineering, International Islamic University Malaysia Author
  • Dwi Pebrianti Kulliyyah of Engineering, International Islamic University Malaysia Author

DOI:

https://doi.org/10.15282/isse.1.1.2026.13880

Keywords:

Passive Infrared (PIR) Sensors, Data Acquisition (DAQ), Real-Time Visualization, Project-Based Learning (PBL), Instrumentation and Measurement, Signal Conditioning

Abstract

This paper presents the experience of students' understanding in subject Instrumentation and Measurements. The approach of the study is to explore the real devices which is Passive Infrared or Pyroelectric Infrared to measure motion, by conducting a set of steps. Students need to do the calibration, design a system to capture motions and develop a real time monitoring using Graphical User Interface based on Python programming. This concept is different from the traditional method, which students just sit in the class and listen to the lecture. Through the experiment, the student team characterized the system's dynamic response and quantified random errors within a controlled environment. The result shows 93.72% of reliability and measured False Positive Rate of 153.09 triggers per hour. This finding leads to the students’ satisfaction which are 80% in understanding the Data Acquisition pipeline, 80% in understanding the effectiveness of real-time visualization and 70% in understanding the analysis of uncertainty and false trigger. This project provides evidence on the effectiveness in Instrumentation and Measurement education by implementing problem-based learning which can improve the students’ understanding in the foundational sensor physics in the modern IoT landscape.

Downloads

Download data is not yet available.

Author Biography

  • Dwi Pebrianti, Kulliyyah of Engineering, International Islamic University Malaysia

    Dwi Pebrianti is an Assistant Professor at the Department of Mechanical and Aerospace Engineering, International Islamic University Malaysia (IIUM) since 2022. Previously, she was a senior lecturer at Universiti Malaysia Pahang, Malaysia in the field of Electrical and Electronics Engineering since 2013 until 2022. Post-Doctoral researcher in Graduate School of Engineering, Chiba University, Japan since 2011 until 2012. Additionally, she was an Indonesian language lecturer in Keiai University, Japan since 2007 until 2012. Currently, she is a Senior Member of The Institution of Electrical & Electronics Engineers (SMIEEE) under the Control And Systems Society (CAS) and Industry Application Society (IAS). She is acknowledged as Executive Professional Engineer from The Institution of Engineers Indonesia (PII).

     

    She received Philosophy Doctor in Artificial System Science from Chiba University, JAPAN in 2011, Master of Engineering in Precision Engineering from The University of Tokyo, JAPAN in 2006 under the MEXT Scholarship from Japanese Ministry of Education, Culture, Sports, Science and Technology. And Bachelor of Engineering in Control Engineering from Universitas Indonesia, INDONESIA in 2001. 

     

    During her study in Japan, Dwi Pebrianti was one of the recipients of College Women Association in Japan Scholarship, prestigious scholarship for only 3 foreign women conducting research in Japan, NEC C&C Research grant and also Iwatani Foundation Research Grant. She was also graduated from Multi-Career PhD program in Chiba University, Japan under the sponsorship of Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT). Her research work during PhD was awarded as the “BEST RESEARCH WORK”, cluster engineering in Chiba University, Japan. 

     

    Her main interests are including Nonlinear control & robotics, Unmanned Aerial Vehicle, underactuated mobile robot, Vision based robot navigation, Motion & dynamics control, Swarm robot control, Optimization technique, Machine Learning and Artificial Intelligence. She was the Principal Investigator of 9 research grants including Exploratory Research Grant Scheme (ERGS) in 2013, Fundamental Research Grant Scheme (FRGS) in 2014 and Sustainable Research Collaboration Grant UMP-UiTM-IIUM in 2020. Additionally, she is the Co-Researcher for 17 research grants.

References

[1] S. Rapuano, "Education in I&M: Instrumentation and Measurement Education Around the World and the Instrumentation and Measurement Society Educational Offerings," in IEEE Instrum. Meas. Mag., vol. 26, no. 1, pp. 29-34, February 2023.

[2] S. Grassini and L. Lombardo, "New Insights in Remote Teaching and Learning of Instrumentation and Measurement: The iHomeX Remote Lab Project," IEEE Instrum. Meas. Mag., vol. 27, no. 1, pp. 26-30, February 2024.

[3] M. Hu and Y. Wang, "Experiment Teaching Reform of Electronic Measurement and Intelligent Instrument Based on Emerging Engineering Education," SHS Web Conf., vol. 162, p. 01010, 2023.

[4] S. A. Dyer, J. L. Schmalzel, R. R. Krchnavek, and S. A. Mandayam, "Macro-I: instrumentation education with projects," in Proc. 2001 Frontiers in Education Conf. (FIE), 2001, vol. 3, pp. S1C-7-S1C-12.

[5] A. V. Szarka, "Engineering is Fun' - in the instrumentation Laboratory," J. Phys.: Conf. Ser., vol. 238, p. 012008, Jul. 2010.

[6] M. Bertocco et al., "E-learning in instrumentation and measurement courses," in Proc. 21st IEEE Instrum. and Meas. Technol. Conf., Como, Italy, 2004, pp. 1146–1150.

[7] M. A. A. Jarwi and A. Doyan, "Project Based Learning (PjBL) Based on Science Practice Tools on Measuring Instrument Material," J. Phys. Conf. Ser., vol. 1, no. 1, 2023.

[8] M.-M. Li and C.-C. Tu, "Developing a Project-Based Learning Course Model Combined with the Think-Pair-Share Strategy to Enhance Creative Thinking Skills in Education Students," Educ. Sci., vol. 14, no. 3, p. 233, Feb. 2024.

[9] D. P. Morales, E. Castillo, L. Parrilla, A. Garcia, and A. Otin, "Towards Project-Based Learning applied to the Electronic Engineering studies," in 2015 Conf. Design of Circuits and Integrated Systems (DCIS), Estoril, Portugal, Nov. 2015, pp. 1-5.

[10] J. L. Schmalzel and S. A. Dyer, "Macro-I: a gateway to instrumentation education," IEEE Instrum. Meas. Mag., vol. 1, pp. 467-468, 2000.

[11] M. Soheilian, G. Fischl, and M. Aries, "Smart Lighting Application for Energy Saving and User Well-Being in the Residential Environment," Sustainability, vol. 13, no. 11, p. 6198, May 2021.

[12] N. H. Baharudin, T. M. N. T. Mansur, R. Ali, and N. F. A. Sobri, "Smart lighting system control strategies for commercial buildings: a review," IJATEE, vol. 8, no. 74, pp. 45-53, Jan. 2021.

[13] J. Yun and M.-H. Song, "Detecting Direction of Movement Using Pyroelectric Infrared Sensors," IEEE Sensors J., vol. 14, no. 5, pp. 1482-1489, 2014.

[14] X. Luo et al., "Human Daily Activity Recognition Using Ceiling Mounted PIR Sensors," in Proc. 2nd Int. Conf. Adv. Mech. Eng. and Industrial Informatics (AMEII 2016), Hangzhou, China, 2016.

[15] A. Kraśniewski, “Integrating Project-Based Learning into Innovative Studies in IoT Engineering," Int. J. Electron. Telecommun., pp. 161-169, Apr. 2025.

[16] C. Perra et al., "Monitoring Indoor People Presence in Buildings Using Low-Cost Infrared Sensor Array in Doorways," Sensors, vol. 21, no. 12, p. 4062, Jun. 2021.

[17] S. O. Al-Jazzar, S. A. Aldalahmeh, D. McLernon, and S. A. R. Zaidi, "Intruder Localization and Tracking Using Two Pyroelectric Infrared Sensors," IEEE Sensors J., vol. 20, no. 11, pp. 6075-6082, Jun. 2020.

[18] A. Shokrollahi et al., "Passive Infrared Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches," Sensors, vol. 24, no. 5, p. 1533, Feb. 2024.

[19] J.-M. Guerrero-Rodriguez, M.-A. Cifredo-Chacon, C. Cobos Sánchez, and F. Perez-Peña, "Exploiting the PIR Sensor Analog Behavior as Thermoreceptor: Movement Direction Classification Based on Spiking Neurons," Sensors, vol. 23, no. 13, p. 5816, Jun. 2023.

[20] M. R. H. Sarker et al., "Characterization of the pyroelectric coefficient of a high-temperature sensor," J. Intell. Mater. Syst. Struct., vol. 29, no. 5, pp. 938-943, Mar. 2018.

Downloads

Published

2026-03-04

Issue

Vol. 1 No. 1 (2026): January

Section

Articles

License

Copyright (c) 2025 The Author(s)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

Bridging theory and practice in motion detection: A reflective evaluation of PIR sensing systems by engineering students. (2026). Intelligent Systems and Sustainable Energy, 1(1), 11-20. https://doi.org/10.15282/isse.1.1.2026.13880

Similar Articles

You may also start an advanced similarity search for this article.