Design and Performance Evaluation of an ESP32-Based IoT Trainer Kit with Telegram Integration for Vocational Learning

Widya Juliani Putri(1), Ryan Fikri(2), Zulwisli Zulwisli(3), Sartika Anori(4),
(1) Universitas Negeri Padang  Indonesia
(2) Universitas Negeri Padang  Indonesia
(3) Universitas Negeri Padang  Indonesia
(4) Universitas Negeri Padang  Indonesia

Corresponding Author


DOI : https://doi.org/10.24036/voteteknika.v14i2.138186

Full Text:    Language : en

Abstract


The rapid development of Internet of Things (IoT) technology requires practical learning media that can help vocational students understand the integration of sensors, actuators, microcontrollers, and remote communication systems. This study aims to design and evaluate an ESP32-based IoT trainer kit integrated with Telegram as a remote monitoring and control platform for microcontroller and IoT learning. The development process followed a waterfall model consisting of requirement analysis, system design, implementation, and functional testing. The trainer kit uses an ESP32 microcontroller as the central controller and integrates several input modules, including an HC-SR04 ultrasonic sensor, DHT22 temperature and humidity sensor, passive infrared sensor, light-dependent resistor, MQ-2 gas sensor, and RC522 RFID module. The output modules consist of a 16x2 LCD, LED indicators, buzzer, servo motor, relay, and solenoid door lock. Functional testing showed that all modules operated according to the designed logic. The RFID module successfully read cards at a distance of 0–3 cm, the ultrasonic sensor triggered servo movement when the object distance was less than 6 cm, the passive infrared sensor produced an output change from approximately 0 V to 3.1 V when motion was detected, and the MQ-2 sensor activated the buzzer when the gas reading exceeded the threshold value of 800. The system also displayed sensor data on the LCD and delivered event notifications through Telegram. These results indicate that the proposed trainer kit is feasible as an interactive learning medium for ESP32-based IoT practice.

Keywords - ESP32, Internet of Things, Telegram, Trainer Kit, Vocational Learning.


References


P. Jacko, M. Bereš, I. Kováčová, J. Molnár, T. Vince, J. Dziak, B. Fecko, Š. Gans, and D. Kováč, “Remote IoT education laboratory for microcontrollers based on the STM32 chips,” Sensors, vol. 22, no. 4, Art. no. 1440, 2022, doi: https://doi.org/10.3390/s22041440

A. Awouda, E. Traini, M. Asranov, and P. Chiabert, “Bloom’s IoT taxonomy towards an effective Industry 4.0 education: Case study on open-source IoT laboratory,” Education and Information Technologies, vol. 29, pp. 15043–15065, 2024, doi: https://doi.org/10.1007/s10639-024-12468-7

D. Sidik, A. Risal, and A. Hudiah, “IoT-based microcontroller trainer media: Innovation for vocational education essential programs,” International Journal of Latest Technology in Engineering, Management & Applied Science, vol. 13, no. 11, 2024, doi: https://doi.org/10.51583/ijltemas.2024.131102

A. Mahmood, K. Ahmed, and H. Mahmood, “Design and implementation of a microcontroller training kit for blend learning,” Computer Applications in Engineering Education, vol. 30, no. 4, pp. 1236–1247, 2022, doi: https://doi.org/10.1002/cae.22517

M. Sukardjo, V. Oktaviani, S. Tawari, I. Alfajar, and I. Ichsan, “Design of control system trainer based on IoT as electronic learning media for natural science course,” Jurnal Penelitian Pendidikan IPA, vol. 9, no. 2, 2023, doi: https://doi.org/10.29303/jppipa.v9i2.3097

L. McLauchlan, D. Hicks, M. Mehrubeoglu, and H. Bhimavarapu, “Enabling remote student learning of IoT technologies,” in Proc. 2023 ASEE Annual Conference & Exposition, Baltimore, MD, USA, 2023, doi: https://doi.org/10.18260/1-2--43273

A. Saxena, A. Agarwal, B. Nagrath, C. Jayavanth, S. Thulasidoss, S. Maheswari, and P. Sasikumar, “Deep learning-driven IoT solution for smart tomato farming,” Scientific Reports, vol. 15, 2025, doi: https://doi.org/10.1038/s41598-025-15615-3

J. Joko, A. Putra, and B. Isnawan, “Implementation of IoT-based human machine interface-learning media and problem-based learning to increase students’ abilities, skills, and innovative behaviors of Industry 4.0 and Society 5.0,” TEM Journal, vol. 12, no. 1, 2023, doi: https://doi.org/10.18421/TEM121-26

D. Hercog, T. Lerher, M. Truntič, and O. Težak, “Design and implementation of ESP32-based IoT devices,” Sensors, vol. 23, no. 15, Art. no. 6739, 2023, doi: https://doi.org/10.3390/s23156739

A. Pradeep, “Enabling IoTs with ESP32 for affordable education,” in Proc. 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 2023, pp. 1368–1373, doi: https://doi.org/10.1109/ICIRCA57980.2023.10220594

M. Ficco, A. Guerriero, E. Milite, F. Palmieri, R. Pietrantuono, and S. Russo, “Federated learning for IoT devices: Enhancing TinyML with on-board training,” Information Fusion, vol. 104, Art. no. 102189, 2023, doi: https://doi.org/10.1016/j.inffus.2023.102189

J. Capcha-Ochoa, J. Chahua-Benito, M. Serafin-Cayllahua, S. Mamani-Martinez, J. Mendivil-Imbertis, J. Mendoza-Fernandez, R. Casas-Miranda, M. Cabana-Cáceres, and C. Castro-Vargas, “Smart irrigation system with IoT, machine learning, and solar power for efficient plant care,” Emerging Science Journal, 2025, doi: https://doi.org/10.28991/esj-2025-09-03-012

M. Yusro, M. Ma’sum, M. Muhamad, and A. Jaenul, “Pengembangan trainer aplikasi multi-sensors (TAMS) berbasis Arduino dan Raspberry Pi,” Risenologi, vol. 6, no. 1, pp. 77–85, 2021, doi: https://doi.org/10.47028/j.risenologi.2021.61.150

H.-Y. Lee, P. Zhou, A. Duan, J. Wang, V. Wu, and D. Navarro-Alarcon, “A multisensor interface to improve the learning experience in arc welding training tasks,” IEEE Transactions on Human-Machine Systems, vol. 53, pp. 619–628, 2023, doi: https://doi.org/10.1109/THMS.2023.3251955

A. Almufarreh and M. Arshad, “Promising emerging technologies for teaching and learning: Recent developments and future challenges,” Sustainability, vol. 15, no. 8, Art. no. 6917, 2023, doi: https://doi.org/10.3390/su15086917

M. Fikri, A. Rossydi, A. Risal, P. Makassar, and U. Makassar, “Design of a security cameras for smart rooms based on Internet of Things (IoT) as an automation learning media at Makassar Aviation Polytechnic,” Airman: Jurnal Teknik dan Keselamatan Transportasi, vol. 7, no. 2, 2024, doi: https://doi.org/10.46509/ajtk.v7i2.510

M. W. Habibi and I. G. P. A. Buditjahjanto, “Impact of training kit-based Internet of Things to learn microcontroller viewed in cognitive domain,” TEM Journal, vol. 13, no. 2, 2024, doi: https://doi.org/10.18421/TEM132-30

F. Oliveira, D. Costa, F. Assis, and I. Silva, “Internet of Intelligent Things: A convergence of embedded systems, edge computing and machine learning,” Internet of Things, vol. 26, Art. no. 101153, 2024, doi: https://doi.org/10.1016/j.iot.2024.101153

O. Khattach, O. Moussaoui, and M. Hassine, “End-to-end architecture for real-time IoT analytics and predictive maintenance using stream processing and ML pipelines,” Sensors, vol. 25, no. 9, Art. no. 2945, 2025, doi: https://doi.org/10.3390/s25092945

A. Pradeep, “Developing an IoT enabled smart classroom S3TH system,” in Proc. 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 2023, pp. 1374–1379, doi: https://doi.org/10.1109/ICIRCA57980.2023.10220862

K. Umam, A. F. Ibadillah, A. Ubaidillah, H. Sukri, D. Rahmawati, and R. Alfita, “Pengembangan trainer Internet of Things (IoT) sebagai media pembelajaran dengan menggunakan NodeMCU ESP32CAM,” Energy: Jurnal Ilmiah Ilmu-Ilmu Teknik, vol. 14, no. 1, 2024, doi: https://doi.org/10.51747/energy.v14i1.1937

R. Fikri, A. D. Samala, D. Faiza, and Almasri, “Performance analysis of an ESP32-based integrated smart home access system: A laboratory scale study,” Jurnal Vocational Teknik Elektronika dan Informatika, vol. 13, no. 4, 2025, https://doi.org/10.24036/voteteknika.v13i4.136492

K. Okafor and O. Longe, “Smart deployment of IoT-TelosB service care StreamRobot using software-defined reliability optimisation design,” Heliyon, vol. 8, Art. no. e09634, 2022, doi: https://doi.org/10.1016/j.heliyon.2022.e09634

A. Apriliana, A. Pradana, and D. Hartanti, “Comparison of the use of Telegram and Blynk platforms in IoT-based gas leak detection,” Jurnal Riset Informatika, vol. 7, no. 3, 2025, doi: https://doi.org/10.34288/jri.v7i3.381

D. Bestari and A. Wibowo, “IoT based real-time weather monitoring system using Telegram bot and ThingsBoard platform,” International Journal of Interactive Mobile Technologies, vol. 17, no. 6, pp. 4–19, 2023, doi: https://doi.org/10.3991/ijim.v17i06.34129

G. Pereira, M. Chaari, and F. Daroge, “IoT-enabled smart drip irrigation system using ESP32,” IoT, vol. 4, no. 3, pp. 221–243, 2023, doi: https://doi.org/10.3390/iot4030012

S. Chakraborty and P. S. Aithal, “Let us create multiple IoT device controller using AWS, ESP32 and C#,” International Journal of Applied Engineering and Management Letters, vol. 7, no. 3, 2023, doi: https://doi.org/10.47992/ijaeml.2581.7000.0172

A. Borkowski, J. Brożyna, and J. Lesiuk, “Implementation of the telemetric integration of the BIM-RFID in context of access control,” Buildings, vol. 14, no. 11, Art. no. 3356, 2024, doi: https://doi.org/10.3390/buildings14113356

N. Hu and Y. Zhang, “Dynamic data management in industry university integration platform: An embedded decision framework,” Journal of Computational Methods in Sciences and Engineering, 2025, doi: https://doi.org/10.1177/14727978251374329

F. Puspasari, T. P. Satya, U. Oktiawati, I. Fahrurrozi, and H. Prisyanti, “Analisis akurasi sistem sensor DHT22 berbasis Arduino terhadap thermohygrometer standar,” Jurnal Fisika dan Aplikasinya, vol. 16, no. 1, pp. 40–45, 2020, doi: https://doi.org/10.12962/j24604682.v16i1.5776

D. Suthar and M. Patel, “IoT-based home security system using Telegram,” in Proc. 2025 12th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2025, pp. 1–9, doi: https://doi.org/10.23919/INDIACom66777.2025.11115737

G. Kilari, R. Mohammed, and R. Jayaraman, “Automatic light intensity control using Arduino UNO and LDR,” in Proc. 2020 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2020, pp. 862–866, doi: https://doi.org/10.1109/ICCSP48568.2020.9182238

M. Prananda, S. Syahputra, and M. Syari, “Design of an LPG leak detection system using IoT based MQ-2 sensor,” Journal of Artificial Intelligence and Engineering Applications, vol. 3, no. 1, 2023, doi: https://doi.org/10.59934/jaiea.v3i1.337

B. Pratama, Z. Z., A. Hadi, and L. Mursyida, “Development of network infrastructure monitoring system at vocational high school using MikroTik and Telegram integration,” Journal of Hypermedia & Technology-Enhanced Learning, vol. 2, no. 3, 2024, doi: https://doi.org/10.58536/j-hytel.v2i3.133

M. Gerten, S. Frei, M. Kiffmeier, and O. Bettgens, “Voltage stability of automotive power supplies during tripping events of melting and electronic fuses,” in Proc. 2022 IEEE 95th Vehicular Technology Conference (VTC2022-Spring), Helsinki, Finland, 2022, pp. 1–6, doi: https://doi.org/10.1109/VTC2022-Spring54318.2022.9860939


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