Implementation And Design of Security System On Motorcycle Vehicles Using Raspberry Pi3-Based GPS Tracker And Facedetection
Keywords:Facedetection; GPS Tracker; Raspberry Pi3; and Security System.
One of the nations where land transportation is frequently employed is Indonesia, particularly on motorbikes or two-wheeled vehicles. Since there is not much economic growth to maintain the high level of sales, there are many people without jobs, which leads to criminality, particularly motorcycle theft. The rate of motorbike theft in society is currently rising. The researchers developed a security system using a GPS Tracker whose control was handled by a two-channel relay in response to the rise in motorbike theft. The webcam camera produces the greatest images when it is hidden by a tree. 100% of the time, Relay Components work to control the horn and electricity. Due to the short read-time of the location the first time, GPS has a high accuracy. The Raspberry Pi3 can send, receive, and process commands to the motorcycle security system. The motion sensors, vibration sensors, raspberry pi microcontrollers, relays, and servo motors make up the system architecture in general. This method operates when the motor produces a lot of vibration. The sensor will relay the vibration to the Raspberry Pi microcontroller's output and the microcontroller will then deliver a warning notification message. In the event of a theft, the motorcycle will be immediately within the owner's control. In addition, with security using facedetection, the public can detect the perpetrators of theft and it takes quite a long time to work on it. The security system on motorbikes using facedetection takes a long time to produce, but it can't be done optimally. The purpose of this creation is to improve the security system on motorcycles to make it more efficient and effective in identifying the perpetrators of theft. This system consists of a Raspberry Pi3 as the control center, a picamera as a face detector, and a buzzer as an alarm.
I.P. Sari, Al-Khowarizmi, and I.H. Batubara, “Optimization of the FP-Growth Algorithm in Data Mining Techniques to Get the Electric Power Theft Pattern for the Development of Smart City,” 4th International Conference of Computer and Informatics Engineering (IC2IE), 2021, pp. 293-298.
I.P. Sari, Al-Khowarizmi, and F. Ramadhani, “User Interface Prototype Using User Centered System Design Method in Motorvice Information System,” International Conference on Computer Science and Engineering (IC2SE), 2021, pp. 1-6.
F. Ramadhani, Al-Khowarizmi, and I.P. Sari, “Improving the Performance of Naïve Bayes Algorithm by Reducing the Attributes of Dataset Using Gain Ratio and Adaboost,” International Conference on Computer Science and Engineering (IC2SE), 2021, pp. 1-5.
M. E. Al Khowarizmi, Rahmad Syah, Mahyuddin K. M. Nasution, “Sensitivity of MAPE using detection rate for big data forecasting crude palm oil on k-nearest neighbor,” Int. J. Electr. Comput. Eng., vol. 11, no. 3, pp. 2697–2704, 2021, doi: 10.11591/ijece.v11i3.pp2697-2704.
I.H. Batubara, S. Saragih, E. Simamora, E.E. Napitupulu, Nuraini, D.N. Sari, Anim, I.P. Sari, E. Rahmadani, and E. Syafitri, “Improving student mathematics communication ability through problem based learning assisted by Augmented Reality based on culture,” AIP Conference Proceedings 2659, 110014 (2022), https://doi.org/10.1063/5.0113258.
I.H. Batubara, A. Famella, N.A. Yossa, M. Yamin, K. Ramadhani, and I.P. Sari, “The Influence Of Project-Based Learning Model On Student Learning Outcomes In Syllabus In Syllabus Development,” The 3th International Seminar on of Language, Art, and Literature Education, pp.429-434.
Al-Khowarizmi, I. R. Nasution, M. Lubis, and A. R. Lubis, “The effect of a secos in crude palm oil forecasting to improve business intelligence,” Bull. Electr. Eng. Informatics, vol. 9, no. 4, pp. 1604–1611, 2020, doi: 10.11591/eei.v9i4.2388.
W. D. Wicaksono, “The development of expert system software in the legal field is expected to make it easier for the public to know and understand the articles and penalties that are adapted to the elements of the articles and types of crimes based on the Criminal Code (KU.” President University, 2018.
M.-J. Lin, “Does democracy increase crime? The evidence from international data,” J. Comp. Econ., vol. 35, no. 3, pp. 467–483, 2007.
I.P. Sari, Al-Khowarizmi, and I.H. Batubara, “Analisa Sistem Kendali Pemanfaatan Raspberry Pi sebagai Server Web untuk Pengontrol Arus Listrik Jarak Jauh,” InfoTekJar: Jurnal Nasional Informatika dan Teknologi Jaringan, PP.99-103.
I.P. Sari, and I.H. Batubara, “Aplikasi Berbasis Teknologi Raspberry Pi Dalam Manajemen Kehadiran Siswa Berbasis Pengenalan Wajah”, JMP-DMT, pp.6.
S. Edy, W. Gunawan, and B. D. Wijanarko, “Analysing the trends of cyber attacks: Case study in Indonesia during period 2013-Early 2017,” in 2017 International Conference on Innovative and Creative Information Technology (ICITech), 2017, pp. 1–6.
P. E. P. Utomo, “Prediction the Crime Motorcycles of Theft using ARIMAX-TFM with Single Input,” in 2018 Third International Conference on Informatics and Computing (ICIC), 2018, pp. 1–7.
H. Chen, W. Chung, J. J. Xu, G. Wang, Y. Qin, and M. Chau, “Crime data mining: a general framework and some examples,” Computer (Long. Beach. Calif)., vol. 37, no. 4, pp. 50–56, 2004.
F. Feeney, “Robbers as decision-makers,” in The reasoning criminal, Routledge, 2017, pp. 53–71.
T. Ahmad, H. Chen, J. Wang, and Y. Guo, “Review of various modeling techniques for the detection of electricity theft in smart grid environment,” Renew. Sustain. Energy Rev., vol. 82, pp. 2916–2933, 2018.
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