SMART ROBOT OBJECT DETECTION MENGGUNAKAN ESP-32 CAM
Abstract
Object detection is a method to recognize the class and location of objects in an image. The main challenge is integrating complex algorithms into lightweight and portable hardware, especially with expensive sensor and camera technologies. This research aims to develop an object detection system using the ESP-32 Cam for robotics monitoring and security. The focus is on utilizing the Yolov5 model transformed into TensorFlow Lite for integration with ESP32 AI CAMERA, expected to detect objects in real-time at a low cost. The methodology includes collecting 1710 datasets from 27 images, dividing the data into 70% training, 20% validation, and 10% testing, and labeling the dataset in Roboflow. The object detection model uses Yolov5, transformed into TensorFlow Lite, and implemented in ESP32 AI CAMERA with ESP-32 Cam as the microcontroller. Model evaluation shows high performance with mAP 95%, precision 97%, and recall 100%, indicating high accuracy. The research successfully develops an efficient and affordable object detection system with ESP-32 Cam and TensorFlow Lite from Yolov5. This integration enables the development of wheeled robots capable of real-time object detection, providing an effective solution for portable robotics monitoring and security.
References
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[2] D. Hariyanto, E. Setiawan, and D. Syauqy, “Kendali Posisi Robot Beroda Dengan Sistem Global Positioning System (GPS) Menggunakan Proportional, Integral dan Derivative (PID) Berbasis Arduino Mega 2560,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 1, pp. 233–241, 2021, [Online]. Available: http://j-ptiik.ub.ac.id
[3] T. A. Dompeipen, S. R. U. . Sompie, and M. E. . Najoan, “Computer Vision Implementation for Detection and Counting the Number of Humans,” J. Tek. Inform., vol. 16, no. 1, pp. 65–67, 2021.
[4] W. Supriyatin, “Analisis Perbandingan Pelacakan Objek Menggunakan Algoritma Horn-Schunck Dan Lucas-Kanade,” Komputasi J. Ilm. Ilmu Komput. dan Mat., vol. 17, no. 2, pp. 362–371, 2020, doi: 10.33751/komputasi.v17i2.2146.
[5] Y. Zhang, Z.; Li, Q.; Yu, W.; Zhang, “Object Detection for Indoor Environments Using RGB-D Cameras,” J. Robot. Auton. Syst., vol. 113, pp. 82–94, 2019, doi: 10.1016/j.robot.2019.01.005.
[6] K. Kim, H.; Lee, S.; Park, J.; Choi, “Enhanced Object Detection for Autonomous Indoor Navigation Using LiDAR and Stereo Cameras,” J. Adv. Robot. Intell. Syst., vol. 28, no. 4, pp. 456–470, 2020, doi: 10.1016/j.arob.2020.04.003.
[7] Espressif Systems, “ESP32-CAM: Wi-Fi + BT + BLE MCU Module with 2MP Camera,” 2019. [Online]. Available: https://www.espressif.com/sites/default/files/documentation/esp32-cam_datasheet_en.pdf
[8] J. S. Asri and G. Firmansyah, “Implementasi objek detection dan tracking menggunakan deep learning untuk pengolahan citra digital | Asri | Konferensi Nasional Sistem Informasi (KNSI) 2018,” pp. 8–9, 2018, [Online].Available: http://jurnal.atmaluhur.ac.id/index.php/knsi2018/article/view/439
[9] E. M. Pamungkas, B. A. A. Sumbodo, and I. Candradewi, “Sistem Pendeteksi dan Pelacakan Bola dengan Metode Hough Circle Transform, Blob Detection, dan Camshift Menggunakan AR.Drone,” IJEIS (Indonesian J. Electron. Instrum. Syst., vol. 7, no. 1, p. 1, 2017, doi: 10.22146/ijeis.15405.
[10] Y. D. Widiarto, M. E. I. Najoan, and M. D. Putro, “Sistem Penggerak Robot Beroda Vacuum Cleaner Berbasis Mini Computer Raspberry pi,” J. Tek.Elektro dan Komput., vol. 7, no. 1, pp. 25–32, 2018.
[11] D. Ferdiansyah and A. Susanto, “Rancang Bangun Prototype Kursi Roda Menggunakan Arduino R3 Berbasis Android,” GATOTKACA J. (Teknik Sipil, Inform. Mesin dan Arsitektur), vol. 1, no. 2, pp. 140–149, 2020, doi: 10.37638/gatotkaca.v1i2.86.
[12] M. Otomatis and B. Arduino, “1) , 2),” vol. 2, no. 2, pp. 233–241, 2019.
[13] A. Nur Alfan and V. Ramadhan, “Prototype Detektor Gas Dan Monitoring Suhu Berbasis Arduino Uno,” PROSISKO J. Pengemb. Ris. dan Obs. Sist. Komput., vol. 9, no. 2, pp. 61–69, 2022, doi: 10.30656/prosisko.v9i2.5380.
[14] A. Armanto, A. A. T. Susilo, H. O. L. Wijaya, and W. M. Sari, “Pengukuran Tingkat Kelembapan Tanah Dan Suhu Berbasis Arduino Uno pada Kelompok Tani Karya Maju II (Dua),” J. Sist. Komput. dan Inform., vol. 3, no. 4, p. 417, 2022, doi: 10.30865/json.v3i4.4197.
[15] A. Wahab, M. Rohman, A. Saepuddin, and M. Sulaiman, “Desain Dan Simulasi Uji Kekuatan Chassis Mobil Sem Jenis Prototype Menggunakan Material Aluminium Alloy 7075,” J. Tek. Mesin Indones., vol. 17, no. 1, pp. 78–85, 2022, doi: 10.36289/jtmi.v17i1.297.
[16] M. F. Setiawan, M. N. Witama, and R. Hikmah, “Perancangan Sistem Pengolahan Data Produksi Konveksi Berbasis Java Pada CV Nirwana Bunga Abadi,” J. Nas. Komputasi dan Teknol. Inf., vol. 3, no. 3, pp. 202–208, 2020, doi: 10.32672/jnkti.v3i3.2435.
[17] W. Supriyatin, “Analisis Perbandingan Pelacakan Objek Menggunakan Optical Flow Dan Background Estimation Pada Kamera Bergerak,” Ilk. J. Ilm., vol. 11, no. 3, pp. 191–199, 2019, doi: 10.33096/ilkom.v11i3.452.191-199.
[18] R. N. Alfi, K. Hijjayanti, N. Saptoaji, and A. Rizal, “Analisis Perbandingan Kecepatan Transfer Data Dengan Kabel USB Tipe A Dan USB Tipe C,” NJCA (Nusantara J. Comput. Its Appl., vol. 4, no. 2, p. 144, 2019, doi: 10.36564/njca.v4i2.156.
[19] N. Sari, W. A. Gunawan, P. K. Sari, I. Zikri, and A. Syahputra, “Analisis Algoritma Bubble Sort Secara Ascending Dan Descending Serta Implementasinya Dengan Menggunakan Bahasa Pemrograman Java,” ADI Bisnis Digit. Interdisiplin J., vol. 3, no. 1, pp. 16–23, 2022, doi: 10.34306/abdi.v3i1.625.
[20] M. S. Naufalimam, M. Zakiyullah Romdlony, and W. A. Cahyadi, “Penerapan Deteksi Dan Pelacakan Objek Pada Robot Otonom Pengumpul Bola Tenis Meja Menggunakan Pengolahan Citra Implementation of Object Detection and Tracking on Autonomous Table Tennis Ball Collector Robot Using Image Processing,” vol. 8, no. 5, pp. 4355–4361, 2021.
Published
2024-06-30
How to Cite
NURDIANSYAH, Deni; SATRIANANSYAH, Satrianansyah; SOBRI, Ahmad.
SMART ROBOT OBJECT DETECTION MENGGUNAKAN ESP-32 CAM.
Jurnal Tekinkom (Teknik Informasi dan Komputer), [S.l.], v. 7, n. 1, p. 272-280, june 2024.
ISSN 2621-3079.
Available at: <https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/1296>. Date accessed: 03 dec. 2024.
doi: https://doi.org/10.37600/tekinkom.v7i1.1296.
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