Application of AI-IoT Technologies to Develop the Smart LED Display Management and Monitoring System for the Laboratory
DOI:
https://doi.org/10.12928/biste.v8i1.15263Keywords:
LED Display Management, Jetson Nano-ESP32 Kit, Internet of Things (IoT), Artificial Intelligence (AI), Deep Learning (DL), Computer Vision (CV), MQTT Protocol, YOLO-Based Object DetectionAbstract
Smart LED display systems are widely used to provide useful information to users, ranging from simple LED screens to complex screens management and monitoring systems involving a large number of diverse devices, capable of integrating modern technologies. This research focuses on developing a smart LED display management and monitoring system for a laboratory using AI-IoT technologies, which combines deep learning, computer vision, edge computing, embedded system, IoT Communication (MQTT), and web-based management. The goal is to provide convenience, efficiency, and flexibility for users and managers, enabling easy remote information updates and real-time display on LED screens, while simultaneously automatically monitoring and accurately counting the number of people entering and leaving the laboratory. The development of the system includes designing an ESP32-based central LED control board, selecting the P2.5 LED modules, the jetson nano, the Logitech C505e camera, suitable for low-cost educational research. Subsequently, the article introduces the image processing algorithm for counting people based on YOLOv7 TensorRT inference and develops the web management interface based on the Next.js platform, combined with data communication via MQTT protocol. This research was then experimentally implemented at the Mitsubishi FA Laboratory at the university of transport and communications (UTC). The experimental results showed that the Web interface features a grid layout divided into three functional groups, allowing for display content configuration, graphical visualization, clear status display. It provides networked link-tags for updating date/time, temperature/humidity, and In/Out people counts in real-time on both the Web and the LED screen via MQTT/ WebSocket protocols. The experimental results also indicated that the proposed algorithm for counting people In/Out the laboratory achieves high accuracy, over 90%, under normal, stable lighting conditions. This confirms that the proposed smart LED display system operates efficiently, stably, and reliably, and suitable for promoting the digital management of laboratories at a low investment cost.
References
A. S. Uyi, A. E. Airoboman, R. Ogu and C. Okwuokenye, "Development of a GSM Enabled Real-Time Electronic Display Board," 2024 IEEE PES/IAS PowerAfrica, pp. 01-05, 2024, https://doi.org/10.1109/PowerAfrica61624.2024.10759372.
Z. Chen, C. B. Sivaparthipan, and B. Muthu, “IoT based smart and intelligent smart city energy optimization,” Sustainable Energy Technologies and Assessments, vol. 49, p. 101724, 2022, https://doi.org/10.1016/j.seta.2021.101724.
J. Li et al., "Long-Distance, Real-Time LED Display-Camera Communication System Based on LED Point Clustering and Lightweight Image Processing", Photonics 9, no.10, p. 721, 2022, https://doi.org/10.3390/photonics9100721.
A. Torralba, J. P. García-Martín, J. M. González-Romo, M. García-Castellano, J. Peral-López and V. Pérez-Mira, "An Autonomous, Intelligent Sign Control System Using Wireless Communication and LED Signs for Rural and Suburban Roads," in IEEE Intelligent Transportation Systems Magazine, vol. 14, no. 2, pp. 115-128, March-April 2022, https://doi.org/10.1109/MITS.2021.3049375.
A. C.Caliwag, H. M. Canilang, M. A. Kamali, E. M. Caliwag, and W. Lim, “Design and Implementation of an IoT-Based Door Signage Control System,” Journal of the Korean Institute of Communications and Information Sciences, vol. 46, no. 4, pp. 696-705, 2021, https://doi.org/10.7840/kics.2021.46.4.696.
S. Chen et al., “Passive matrix Micro-LED display driven by STM32 microcontroller using a two-wire serial transmission method,” In Journal of Physics: Conference Series, vol. 2524, no. 1, p. 012004, 2023, https://doi.org/10.1088/1742-6596/2524/1/012004.
Z. Zou et al., "FPGA-based LED Display Technology," 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), pp. 2460-2463, 2019, https://doi.org/10.1109/IAEAC47372.2019.8997982.
T. Facchinetti, A. Bonandin, G. Benetti and D. D. Martini, "Distributed architecture for a smart LEDs display system based on MQTT," 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), pp. 1243-1246, 2020, https://doi.org/10.1109/ETFA46521.2020.9212084.
B. Jyothi, D. Geethika, A. R. Khan, B. M. Prudhvi, M. A. S. V. Ratnakar and M. V. Vardhan, "Smart Illuminated Display Board," 2024 10th International Conference on Electrical Energy Systems (ICEES), pp. 1-7, 2024, https://doi.org/10.1109/ICEES61253.2024.10776858.
P. Anuradha and K. S. Theja, "IoT Based Real Time LED Display Board," 2022 International Conference on Recent Trends in Microelectronics, Automation, Computing and Communications Systems (ICMACC), pp. 1-4, 2022, https://doi.org/10.1109/ICMACC54824.2022.10093434.
H. Jiang, J. Xu and K. Wang, "Software and hardware design and implementation of LED display system of stadium big screen," 2011 International Conference on Multimedia Technology, pp. 3663-3666, 2011, https://doi.org/10.1109/ICMT.2011.6002193.
I. Surya and J. Kustija, “Dashboard for Industrial Load Control and Remote Power Factor Correction Based on Adafruit’s MQTT”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 5, no. 1, pp. 76–85, 2023, https://doi.org/10.12928/biste.v5i1.7494.
M. A. Hailan, N. M. Ghazaly, and B. M. Albaker, “ESPNow Protocol-Based IIoT System for Remotely Monitoring and Controlling Industrial Systems,” Journal of Robotics and Control (JRC), vol. 5, no. 6, pp. 1924-1942, 2024, https://doi.org/10.18196/jrc.v5i6.21925.
M. Ţălu, “Exploring IoT Applications for Transforming University Education: Smart Classrooms, Student Engagement, and Innovations in Teacher and Student-focused Technologies”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 7, no. 1, pp. 9–29, 2025, https://doi.org/10.12928/biste.v7i1.12361.
M. Mustofa and A. . Fadlil, “Design an Internet of Things-Based LPG Gas Leak Detection System”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 4, no. 3, pp. 122–131, 2023, https://doi.org/10.12928/biste.v4i3.5572.
Y. Munsadwala, P. Joshi, P. Patel and K. Rana, "Identification and Visualization of Hazardous Gases Using IoT," 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), Ghaziabad, India, 2019, pp. 1-6, 2019, https://doi.org/10.1109/IoT-SIU.2019.8777481.
S. Sharma, S. Das, J. Virmani, M. Sharma, S. Singh and A. Das, "IoT Based Dipstick Type Engine Oil Level and Impurities Monitoring System: A Portable Online Spectrophotometer," 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), pp. 1-4, 2019, https://doi.org/10.1109/IoT-SIU.2019.8777703.
V. Puranik, Sharmila, A. Ranjan and A. Kumari, "Automation in Agriculture and IoT," 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), pp. 1-6, 2019, https://doi.org/10.1109/IoT-SIU.2019.8777619.
D. Mishra, A. Khan, R. Tiwari and S. Upadhay, "Automated Irrigation System-IoT Based Approach," 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU), pp. 1-4, 2018, https://doi.org/10.1109/IoT-SIU.2018.8519886.
R. A. Kjellby, L. R. Cenkeramaddi, A. Frøytlog, B. B. Lozano, J. Soumya and M. Bhange, "Long-range & Self-powered IoT Devices for Agriculture & Aquaponics Based on Multi-hop Topology," 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), pp. 545-549, 2019, https://doi.org/10.1109/WF-IoT.2019.8767196.
I. Miladinovic and S. Schefer-Wenzl, "NFV enabled IoT architecture for an operating room environment," 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), pp. 98-102, 2018, https://doi.org/10.1109/WF-IoT.2018.8355128.
W. Eka Sari, E. Junirianto, and G. Fatur Perdana, “System of Measuring PH, Humidity, and Temperature Based on Internet of Things (IoT)”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 3, no. 1, pp. 72–81, 2021, https://doi.org/10.12928/biste.v3i1.3214.
D. D. Sanjaya and A. Fadlil, “Monitoring Temperature and Humidity of Boiler Chicken Cages Based on Internet of Things (IoT)”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 5, no. 2, pp. 180–189, 2023, https://doi.org/10.12928/biste.v5i2.4897.
D. T. Ma’arij and A. Yudhana, “Temperature and Humidity Monitoring System in Internet of Things-based Solar Dryer Dome”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 5, no. 3, pp. 323–335, 2023, https://doi.org/10.12928/biste.v5i3.8633.
S. M. Khan, M. T. Mahi and M. Rasheduzzaman, "Design and Implementation of a Low-Cost Weather Monitoring System using ESP-NOW," 2024 13th International Conference on Electrical and Computer Engineering (ICECE), pp. 437-442, 2024, https://doi.org/10.1109/ICECE64886.2024.11024940.
J. Park, J. Bae, J. Lim, B. Kim and J. Jeong, "LED-Display Defect Detection Based on YOLOv5 and Transformer," in IEEE Access, vol. 11, pp. 124660-124675, 2023, https://doi.org/10.1109/ACCESS.2023.3325487.
M. I. M. Ameerdin, M. H. Jamaluddin, A. Z. Shukor, and S. Mohamad, “A review of deep learning-based defect detection and panel localization for photovoltaic panel surveillance system,” International Journal of Robotics and Control Systems, vol. 4, no. 4, pp. 1746-1771, 2024, https://doi.org/10.31763/ijrcs.v4i4.1579.
T. L. Mien, N. D. Tu, and N. Van Lam, “Deploying YOLOv8 for Real-Time Road Crack Detection on Smart Road Length Measurement Devices,” Journal of Future Artificial Intelligence and Technologies, vol. 2, no. 1, pp. 135-144, 2025, https://doi.org/10.62411/faith.3048-3719-102.
H. I. K. Fathurrahman and C. Li-Yi, “Character Translation on Plate Recognition with Intelligence Approaches”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 4, no. 3, pp. 105–110, 2023, https://doi.org/10.12928/biste.v4i3.7161.
A. R. Zulkifli, K. Ali, and Z. Abd Rahman, “Raspberry Pi Based Intelligent Traffic Signal Control at Intersections,” In Control, Instrumentation and Mechatronics: Theory and Practice (pp. 391-405, 2022, https://doi.org/10.1007/978-981-19-3923-5_34.
T. Luong Mien and V. Van Duy, "Development of the System of Monitoring Traffic Vehicle Volume and Density on the Vietnam’s Street," 2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS), Hanoi, Vietnam, 2022, pp. 292-297, 2022, https://doi.org/10.1109/ICCAIS56082.2022.9990367.
T. L. Mien and V. V. Duy, “Research on Building the System of the Identification and Detection Traffic Violations Vehicles at Vietnamese Intersections,” In International Conference on Engineering Research and Applications, pp. 831-838, 2022, https://doi.org/10.1007/978-3-031-22200-9_87.
N. Bachir and Q. A. Memon, “Benchmarking YOLOv5 models for improved human detection in search and rescue missions,” Journal of Electronic Science and Technology, vol. 22, no. 1, p. 100243, 2024, https://doi.org/10.1016/j.jnlest.2024.100243.
A. D. Baharuddin and M. A. M. Basri, “A YOLO-Based Target Detection Algorithm for DJI Tello Drone,” International Journal of Robotics and Control Systems, vol. 5, no. 3, pp. 1608-1624, 2025, https://doi.org/10.31763/ijrcs.v5i3.1898.
T. A. R. Shyaa and A. A. Hashim, “Enhancing real human detection and people counting using YOLOv8,” In BIO Web of Conferences, vol. 97, p. 00061, 2024, https://doi.org/10.1051/bioconf/20249700061.
N. Chandra and S. P. Panda, "A Human Intruder Detection System for Restricted Sensitive Areas," 2021 2nd International Conference on Range Technology (ICORT), pp. 1-4, 2021, https://doi.org/10.1109/ICORT52730.2021.9582099.
N. M. Muriyah, J. H. Sim, and A. Yulianto, “Evaluating YOLOv5 and YOLOv8: advancements in human detection,” Journal of Information Systems and Informatics, vol. 6, no. 4, pp. 2999-3015, https://doi.org/10.51519/journalisi.v6i4.944.
T. A. R. Shyaa and A. A. Hashim, “Enhancing real human detection and people counting using YOLOv8,” In BIO Web of Conferences, vol. 97, p. 00061, 2024, https://doi.org/10.1051/bioconf/20249700061.
Y. Xiao, Z. Tian, J. Yu, Y. Zhang, S. Liu, S. Du, and X. Lan, “A review of object detection based on deep learning,” Multimedia Tools and Applications, vol. 79, no. 33, pp. 23729-23791, 2020, https://doi.org/10.1007/s11042-020-08976-6.
T. L. Mien, V. Van An, and T. T. Huong, “Research and development of the pupil identification and warning system using AI-IoT,” Journal of Robotics and Control (JRC), vol. 3, no. 4, pp. 528-534, 2022, https://doi.org/10.18196/jrc.v3i4.14978.
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