COMPARISON OF VARIOUS TYPES OF PIR MOTION SENSORS FOR NODEMCU ESP32 CAM IMAGE CAPTURING DEVICES
DOI:
https://doi.org/10.36595/jire.v7i2.1344Keywords:
ESP32 CAM, PIR Motion, Image CaptureAbstract
Abstract:Videos and images can be used as observations or evidence of a crime. The most widely used device for recording video in an office or home is CCTV (Closed Circuit Television). The cost of installing the cheapest CCTV in Indonesia is 1,300,000 thousand Rupiah.The development of the microcontroller has been equipped with a camera module. Lilygo TTGO, NodeMCU ESP 32 CAM, Raspberry Pi, are the choices of microcontrollers with camera extensions. Using the ESP32 CAM Node MCU to record images is a cheaper option compared to using CCTV (Closed Circuit Television). The input data for the ESP32 CAM NodeMCU to detect human movement is the PIR Motion sensor module.In searches on various marketplaces, there are around 20 types of PIR Motion. Each type has a different range and delay time specifications. In this study, 6 PIR Motion sensors available on the Indonesian marketplace were tested with the types HC-SR505, HC-SR501, SR602, AM312, D203s, PIR 507. The test was carried out by assembling six PIR Motions on one PCB (Printed Circuit Board) to get data at the same time. The testing tool uses Arduino Uno by utilizing the Serial Monitor service on the Arduino IDE application. The results of the PIR sensor range test show that the HC-SR501 type has the farthest range while the HC-SR505 successfully captures images.
References
Ai-thinker, “ESP32-CAM camera development board,” vol. 1, pp. 0–4, 1375.
P. Kantha & Priyanka, “Realization of an IoT System to Ensure Doorway Security by Integrating ESP32-CAM with Cloud Server,” pp. 1235–1238, 2020.
D. Noviani and S. Riyanto, “Aplikasi Sistem Keamanan Rumah Berbasis Internet of Things Menggunakan Blynk,” Pros. Semin. Nas. Teknol. Inf. dan Komun., vol. 4, no. 1, pp. 2–3, 2021, [Online]. Available: http://prosiding.unipma.ac.id/index.php/SENATIK/article/view/1946
G. Priyandoko, “Rancang Bangun Sistem Portable Monitoring Infus Berbasis Internet of Things,” Jambura J. Electr. Electron. Eng., vol. 3, no. 2, pp. 56–61, 2021, doi: 10.37905/jjeee.v3i2.10508.
M. Ismail, R. K. Abdullah, and S. Abdussamad, “Tempat Sampah Pintar Berbasis Internet of Things (IoT) Dengan Sistem Teknologi Informasi,” Jambura J. Electr. Electron. Eng., vol. 3, no. 1, pp. 7–12, 2021, doi: 10.37905/jjeee.v3i1.8099.
N. Jaini, E. Asri, and F. Nova, “Sistem Manajemen Kehadiran Menggunakan Metode Face Recognition Berbasis Web,” JITSI J. Ilm. Teknol. Sist. Inf., vol. 2, no. 2, pp. 48–55, Jun. 2021, doi: 10.30630/jitsi.2.2.39.
M. F. Wicaksono and M. D. Rahmatya, “Implementasi Arduino dan ESP32 CAM untuk Smart Home,” J. Teknol. dan Inf., vol. 10, no. 1, pp. 40–51, 2020, doi: 10.34010/jati.v10i1.2836.
H. G. GHIFARI, D. DARLIS, and A. HARTAMAN, “Pendeteksi Golongan Darah Manusia Berbasis Tensorflow menggunakan ESP32-CAM,” ELKOMIKA J. Tek. Energi Elektr. Tek. Telekomun. Tek. Elektron., vol. 9, no. 2, p. 359, 2021, doi: 10.26760/elkomika.v9i2.359.
A. Rifaini, S. Sintaro, and A. Surahman, “ALAT PERANGKAP DAN KAMERA PENGAWAS DENGAN MENGGUNAKAN ESP32-CAM SEBAGAI,” vol. 2, pp. 53–63, 2021.
H. Fitri and D. Ivan Finiel Hotmartua Bagariang, “Pemanfaatan Esp32-Cam Untuk Mengukur Ketinggian Air Menggunakan Metode Image Processing,” Semin. Nas. Terap. Ris. Inov. Ke-6 ISAS Publ. Ser. Eng. Sci., vol. 6, no. 1, pp. 762–769, 2020.
P. Rai and M. Rehman, “ESP32 Based Smart Surveillance System,” in 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), Jan. 2019, pp. 1–3. doi: 10.1109/ICOMET.2019.8673463.
blynk, “A fully integrated suite of IoT software,” 1375. https://blynk-io.translate.goog/?_x_tr_sl=en&_x_tr_tl=id&_x_tr_hl=id&_x_tr_pto=op,sc
A. Jeklin, “Arduino Telegram,” 2016. http://www.arduino.web.id/2021/03/bot-telegram-untuk-project-iot.html
H. Andrianto, D. P. Sutanto, and Y. A. Prasetyo, “A low-cost IoT-based auscultation training device,” Indones. J. Electr. Eng. Comput. Sci., vol. 21, no. 3, pp. 1356–1363, 2021, doi: 10.11591/ijeecs.v21.i3.pp1356-1363.
N. A. Hussein and M. I. Shujaa, “Secure vehicle to vehicle voice chat based MQTT and coap internet of things protocol,” Indones. J. Electr. Eng. Comput. Sci., vol. 19, no. 1, pp. 526–534, 2020, doi: 10.11591/ijeecs.v19.i1.pp526-534.
“MQTT: The Standard for IoT Messaging.” https://mqtt.org
Z. B. Abilovani, W. Yahya, and F. A. Bakhtiar, “Implementasi Protokol MQTT Untuk Sistem Monitoring Perangkat IoT,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 12, pp. 7521–7527, 2018, [Online]. Available: http://j-ptiik.ub.ac.id
I. G. M. Ngurah Desnanjaya and I. N. A. Arsana, “Home security monitoring system with IoT-based Raspberry Pi,” Indones. J. Electr. Eng. Comput. Sci., vol. 22, no. 3, pp. 1295–1302, 2021, doi: 10.11591/ijeecs.v22.i3.pp1295-1302.
B. Alathari, M. F. Kadhim, S. Al-Khammasi, and N. S. Ali, “A framework implementation of surveillance tracking system based on pir motion sensors,” Indones. J. Electr. Eng. Comput. Sci., vol. 13, no. 1, pp. 235–242, 2019, doi: 10.11591/ijeecs.v13.i1.pp235-242.
A. H. Maray, S. Q. Hasan, and N. L. Mohammed, “Design and implementation of low-cost vein-viewer detection using near infrared imaging,” vol. 29, no. 2, 2023, doi: 10.11591/ijeecs.v29.i2.pp1039-1064.
A. Setiawan and A. Irma Purnamasari, “Pengembangan Passive Infrared Sensor (PIR) HC-SR501 dengan Microcontrollers ESP32-CAM Berbasiskan Internet of Things (IoT) dan Smart Home sebagai Deteksi Gerak untuk Keamanan Perumahan,” Prosisiding Semin. Nas. SISFOTEK (Sistem Inf. dan Teknol. Informasi), vol. 3, no. 1, pp. 148–154, 2019, [Online]. Available: http://seminar.iaii.or.id/index.php/SISFOTEK/article/view/118
A. A. Ashar and D. H. R. Saputra, “Design and Build a Safe Security System Using RFID With e-KTP as a Tag and Monitoring With IoT-Based Esp32-Cam With Telegram Notifications,” Indones. J. Innov. Stud., vol. 15, pp. 1–13, 2021, doi: 10.21070/ijins.v13i.527.
M. Z. H. Zim, “TinyML: Analysis of Xtensa LX6 microprocessor for Neural Network Applications by ESP32 SoC,” Cornel University, 2021. doi: 10.13140/RG.2.2.28602.11204.
K. Dokic, “Microcontrollers on the edge – is esp32 with camera ready for machine learning?,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, vol. 12119 LNCS, pp. 213–220. doi: 10.1007/978-3-030-51935-3_23.
B. H. Sirenden, A. Manao, and N. Mn, “JoTP Development of Camera-Based Rainfall Intensity,” vol. 3, no. 2, pp. 89–100, 2021, doi: https://doi.org/10.32734/jotp.v3i2.5407.
A. Putra, M. Susilo, D. Darlis, and D. A. Nurmantris, “PENGENALAN WAJAH BERBASIS ESP32-CAM UNTUK SISTEM KUNCI SEPEDA MOTOR ESP32-CAM-BASED FACE RECOGNITION FOR MOTORCYCLE,” vol. 8, no. 2, pp. 1091–1103, 2021, doi: https://doi.org/10.25124/jett.v8i2.4199.
Y. Rahmawati, I. Uli, V. Simanjutak, and R. B. Simorangkir, “Rancang Bangun Purwarupa Sistem Peringatan Pengendara Pelanggar Zebra Cross Berbasis Mikrokontroler ESP-32 CAM,” Jambura J. Electr. Electron. Eng., vol. 4, no. 2, pp. 191–192, 2022.
N. G. Lam and J. Matila, “Vehicle Speed Measurement Using Doppler Effect,” UNIVERSITY OF APPLIED SCIENCES, 2021. [Online]. Available: https://www.theseus.fi/bitstream/handle/10024/496044/Thesis.pdf?sequence=2
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