Real-Time Accident Detection Using KNN Algorithm to Support IoT-based Smart City
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Abstract
Surabaya is a city with an area of 326.81 km2 and is the center of land transportation in the eastern part of Java Island. The construction of digital infrastructure in the Surabaya area will make it easier for the City Government to make efficient services. Traffic accidents that occurred in Surabaya until 2017 recorded 1,365 incidents. EVAN (Emergency Vehicle Automatic Notification) is a research topic that focuses on the field of transportation, especially in real-time traffic accidents which can be integrated with city information centers and hospitals for primary assistance in accidents. The purpose of this research is to make it easier for the Surabaya city government to provide first aid in the event of an accident. The design of the device on the user side is made using the Arduino, the accelerometer sensor and the gyroscope in the form of the MPU6050 sensor and the u-blox gps module. Crash detection on the system using the k-Nearest neighbors algorithm (KNN). On the operator side, the design is done on a web basis by utilizing the ReactJs framework which is integrated with the Google Maps APIs. The results of the accuracy of the accident detection system reached 97% and the detection of accident locations and the nearest hospital from the location reached 100%. Thus, real-time accident detection can be implemented in Surabaya city to support the smart city.
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A. Karakteristik et al., “Knowledge Discovery in Database Analysis of Traffic Accident Characteristic on Ahmad Yani Road Surabaya through Knowledge Discovery in Database Approach,” 2018.
M. T. A. Amir and Y. Y. Kerlooza, “Sistem Pendeteksi Kecelakaan Kendaraan Bermotor Menggunakan Arduino Dan Smartphone Android,” Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan, vol. 8, no. 2, pp. 105–112, Apr. 2021, doi: 10.34010/telekontran.v8i2.4570.
Machine Intelligence Research Labs, Research Groups in Intelligent Machines, IEEE-Tunisia Section, M. IEEE Systems, M. IEEE Systems, and Institute of Electrical and Electronics Engineers, 6th International Conference on Soft Computing and Pattern Recognition : SoCPaR 2014 : August 11-14, 2014 : Ramada Plaza hotel, Tunis - Tunisia : Conference Booklet.
Y. W. Liyanage, D.-S. Zois, and C. Chelmis, “Near Real-Time Freeway Accident Detection,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 2, pp. 1467–1478, Oct. 2020, doi: 10.1109/tits.2020.3027494.
A. Khan, F. Bibi, M. Dilshad, S. Ahmed, Z. Ullah, and H. Ali, “Accident Detection and Smart Rescue System using Android Smartphone with Real-Time Location Tracking,” 2018. [Online]. Available: www.ijacsa.thesai.org
2020 IEEE PES/IAS PowerAfrica. IEEE, 2020.
D. S. Wisdayani, I. Manfaati Nur, and R. Wasono, “Penerapan Algoritma K-Nearest Neighbor dalam Klasifikasi Tingkat Keparahan Korban Kecelakaan Lalu Lintas di Kabupaten Jawa Tengah Application of K-Nearest Neihbor Algorithm in the Classification of Severity of Traffic Victims in Pati, Central Java.” [Online]. Available: http://prosiding.unimus.ac.id
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“Position Tracking during Human Motions using an Integrated Wearable Sensing System 2016 Giulio Zizzo.”
A. Mahfuzhon and G. Edhi Setyawan, “Rancang Bangun Alat Pendeteksi Kecelakaan Mobil Menggunakan Sensor Akselerometer dan Sensor 801s Vibration,” 2018. [Online]. Available: http://j-ptiik.ub.ac.id
D. Abdulahad Aziz, “Webserver Based Smart Monitoring System Using ESP8266 Node MCU Module,” International Journal of Scientific & Engineering Research, vol. 9, no. 6, 2018, [Online]. Available: http://www.ijser.org
N. Ferdiansyah Kusna, S. Rizqika Akbar, and D. Syauqy, “Rancang Bangun Pengenalan Modul Sensor Dengan Konfigurasi Otomatis Berbasis Komunikasi I2C,” 2018. [Online]. Available: http://j-ptiik.ub.ac.id
M. Rivki and A. M. Bachtiar, “IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR DALAM PENGKLASIFIKASIAN FOLLOWER TWITTER YANG MENGGUNAKAN BAHASA INDONESIA,” Jurnal Sistem Informasi, vol. 13, no. 1, p. 31, May 2017, doi: 10.21609/jsi.v13i1.500.
J. Teknik Elektro, P. Negeri Padang Jurusan Teknik Elektro Politeknik Negeri Padang, J. Limau, and K. Kunci, “Komparasi Akurasi Global Posistion System (GPS) Receiver U-blox Neo-6M dan U-blox Neo-M8N pada Navigasi Quadcopter,” Elektron Jurnal Ilmiah, vol. 12, 2020.
M. Wali and L. Ahmad, “Perancangan Access Open Journal System (AOJS) dengan menggunakan Framework Codeigniter dan ReactJs,” Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), vol. 2, no. 1, p. 48, Oct. 2018, doi: 10.35870/jtik.v2i1.53.
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Published
Mar 29, 2022
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How to Cite
Amiroh, K., Seno Aji, B. A., & Rahmanti, F. Z. (2022). Real-Time Accident Detection Using KNN Algorithm to Support IoT-based Smart City. Jurnal Nasional Teknik Elektro, 11(1), 65–70. https://doi.org/10.25077/jnte.v11n1.999.2022
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