Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept

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Nur Kumala Dewi 1,*

1. STMIK Muhammadiyah Jakarta, Indonesia

* Corresponding author.


Received: 13 Jan. 2021 / Revised: 20 Jan. 2021 / Accepted: 28 Jan. 2021 / Published: 8 Feb. 2021

Index Terms

Vehicle, Internet of Think (IoT), Transportation, Violations


The background of this research raises the problem of the development of smart transportation in terms of monitoring and enforcement of traffic on the highway, with the proposed system that will help many parties such as the police and the government. The system that is running is to develop a system using CCTV that is placed on every corner of the capital city to replace the police in carrying out road surveillance and law enforcement against lawbreakers, especially in the traffic sector. The method used in this research is by using literature review of many previous research journals, by reading many journals will be able to add knowledge and can deepen ongoing research. The problem raised in this research is finding solutions to problems in the transportation sector, especially smart transportation, using smart transportation will be able to connect all systems that have been made. This research produces a system proposal that can be used in further research and can be applied in terms of the development of smart cities, especially smart transportation.

Cite This Paper

Nur Kumala Dewi, " Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept ", International Journal of Engineering and Manufacturing (IJEM), Vol.11, No.1, pp. 29-36, 2021. DOI: 10.5815/ijem.2021.01.04


[1] Y. Agarwal, K. Jain, and O. Karabasoglu, “Smart vehicle monitoring and assistance using cloud computing in vehicular Ad Hoc networks,” Int. J. Transp. Sci. Technol., vol. 7, no. 1, pp. 60–73, 2018, doi: 10.1016/j.ijtst.2017.12.001.

[2] M. Agbali, C. Trillo, T. Fernando, I. A. Ibrahim, and Y. Arayici, “Conceptual Smart City KPI Model: A System Dynamics Modelling Approach,” Proc. 2nd World Conf. Smart Trends Syst. Secur. Sustain. WorldS4 2018, pp. 158–162, 2019, doi: 10.1109/WorldS4.2018.8611565.

[3] S. H. Ahmed, M. A. Yaqub, S. H. Bouk, and D. Kim, “Towards content-centric traffic ticketing in VANETs: An application perspective,” Int. Conf. Ubiquitous Futur. Networks, ICUFN, vol. 2015-Augus, pp. 237–239, 2015, doi: 10.1109/ICUFN.2015.7182541.

[4] G. Aisyah and P. Bestari, “Implementation E-Tilang in Bandung to Increase Awareness of Cross as Moral Law Passed Citizenship (Civic Virtue),” vol. 251, no. 22, pp. 664–667, 2018, doi: 10.2991/acec-18.2018.148.

[5] Z. Al-Ars, S. van der Vlugt, P. Jääskeläinen, and F. van der Linden, “ALMARVI System Solution for Image and Video Processing in Healthcare, Surveillance and Mobile Applications,” J. Signal Process. Syst., vol. 91, no. 1, pp. 1–7, 2019, doi: 10.1007/s11265-018-1423-2.

[6] Z. Allam and P. Newman, “Redefining the Smart City: Culture, Metabolism and Governance,” Smart Cities, vol. 1, no. 1, pp. 4–25, 2018, doi: 10.3390/smartcities1010002.

[7] A. S. Putra and F. R. Radita, “Paradigma Belajar Mengaji Secara Online Pada Masa Pandemic Coronavirus Disease 2019 ( Covid-19 ) ى ْ أ ش ُ َ ف ه,” Mataazir J. Adm. dan Manaj. Pendidik., vol. 1, no. I, pp. 49–61, 2020.

[8] B. A. Alpatov, P. V. Babayan, and M. D. Ershov, “Vehicle detection and counting system for real-time traffic surveillance,” 2018 7th Mediterr. Conf. Embed. Comput. MECO 2018 - Incl. ECYPS 2018, Proc., no. June, pp. 1–4, 2018, doi: 10.1109/MECO.2018.8406017.

[9] A. A. Ambardekar and T. Advisor, “Efficient Vehicle Tracking and Classification for an Automated Traffic Surveillance System,” 2007.

[10] H. Lisnawati and A. Sinaga, “Data mining with associated methods to predict consumer purchasing patterns,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 5, pp. 16–28, 2020, doi: 10.5815/ijmecs.2020.05.02.

[11] M. Mitra and A. Chowdhury, “A modernized voting system using fuzzy logic and blockchain technology,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 3, pp. 17–25, 2020, doi: 10.5815/ijmecs.2020.03.03.

[12] Muhammad Syarif Hartawan, Arman Syah Putra, and Ayub Muktiono, “Smart City Concept for Integrated Citizen Information Smart Card or ICISC in DKI Jakarta,” Int. J. Sci. Technol. Manag., vol. 1, no. 4, pp. 364–370, 2020, doi: 10.46729/ijstm.v1i4.76.

[13] N. K. Dewi et al., “Konsep Aplikasi E-Dakwah Untuk Generasi Milenial Jakarta penting dalam menyiarkan agama Islam . Dengan media dakwah yang tepat maka akan bisa menyiarkan agama Islam dengan maksimal dengan media dakwah yang tepat suatu konsep dalam berdakwah dengan E-Dakwa,” vol. 5, no. 2, pp. 26–33, 2021.

[14] N. K. Dewi, I. Mulyana, A. S. Putra, and F. R. Radita, “Tampilan Konsep Robot Penjaga Toko Di Kombinasikan Dengan Pengendalian Virtual Reality (VR) Jarak Jauh,” J. IKRA-ITH Inform., vol. 5, no. 1, pp. 33–38, 2021, [Online]. Available:

[15] N. K. Dewi and A. S. Putra, “PENERIMAAN KARYAWAN BARU DENGAN,” vol. 6, no. 2, pp. 154–160, 2020.

[16] S. Sathasivam, S. A. Alzaeemi, and M. Velavan, “Mean-field theory in hopfield neural network for doing 2 satisfiability logic programming,” Int. J. Mod. Educ. Comput. Sci., vol. 12, no. 4, pp. 27–39, 2020, doi: 10.5815/ijmecs.2020.04.03.

[17] I. Ramadhan, A. Kurniawan, and A. S. Putra, “Penentuan Pola Penindakan Pelanggaran Lalu Lintas di DKI Jakarta Menggunakan Metode Analytic Network Process ( ANP ),” vol. 5, no. 1, pp. 51–57.

[18] P. Cardullo and R. Kitchin, “Being a ‘citizen’ in the smart city: up and down the scaffold of smart citizen participation in Dublin, Ireland,” GeoJournal, vol. 84, no. 1, 2019, doi: 10.1007/s10708-018-9845-8.

[19] J. Chang, L. Wang, G. Meng, S. Xiang, and C. Pan, “Vision-based occlusion handling and vehicle classification for traffic surveillance systems,” IEEE Intell. Transp. Syst. Mag., vol. 10, no. 2, pp. 80–92, 2018, doi: 10.1109/MITS.2018.2806619.

[20] S. Chaudhuri and U. Dayal, “An Overview of Data Warehousing and OLAP Technology,” SIGMOD Rec. (ACM Spec. Interes. Gr. Manag. Data), vol. 26, no. 1, pp. 65–74, 1997, doi: 10.1145/248603.248616.

[21] T. Regulations, P. P. Data, P. Examiner, and A. M. Au, “( 12 ) United States Patent,” vol. 2, no. 12, 2003.

[22] A. Pongpunwattana and R. Rysdyk, “Real-time planning for multiple autonomous vehicles in dynamic uncertain environments,” J. Aerosp. Comput. Inf. Commun., vol. 1, no. DEC., pp. 580–604, 2004, doi: 10.2514/1.12919.

[23] P. Polack, F. Altche, B. DAndrea-Novel, and A. De La Fortelle, “The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?,” IEEE Intell. Veh. Symp. Proc., no. Iv, pp. 812–818, 2017, doi: 10.1109/IVS.2017.7995816.

[24] S. Chaudhuri and U. Dayal, “Data warehousing and OLAP for decision support,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 1341, pp. 33–34, 1997, doi: 10.1007/3-540-63792-3_6.

[25] J. W. Choi, R. Curry, and G. Elkaim, “Path planning based on bézier curve for autonomous ground vehicles,” Proc. - Adv. Electr. Electron. Eng. - IAENG Spec. Ed. World Congr. Eng. Comput. Sci. 2008, WCECS 2008, no. 2, pp. 158–166, 2008, doi: 10.1109/WCECS.2008.27.

[26] G. Corraro, F. Corraro, E. De Lellis, and L. Garbarino, “Flight tests of ADS-B traffic advisory system (ATAS) and performance comparison with other surveillance systems,” AIAA Aerosp. Sci. Meet. 2018, no. 210059, 2018, doi: 10.2514/6.2018-0286.

[27] R. Cowley, S. Joss, and Y. Dayot, “The smart city and its publics: insights from across six UK cities,” Urban Res. Pract., vol. 11, no. 1, pp. 53–77, 2018, doi: 10.1080/17535069.2017.1293150.

[28] M. Desai and A. Phadke, “Internet of Things based vehicle monitoring system,” IFIP Int. Conf. Wirel. Opt. Commun. Networks, WOCN, pp. 1–3, 2017, doi: 10.1109/WOCN.2017.8065840.

[29] M. A. Elliott, C. J. Baughan, and B. F. Sexton, “Errors and violations in relation to motorcyclists’ crash risk,” Accid. Anal. Prev., vol. 39, no. 3, pp. 491–499, 2007, doi: 10.1016/j.aap.2006.08.012.

[30] J. Gao and H. Tembine, “Distributed Mean-Field-Type Filters for Traffic Networks,” IEEE Trans. Intell. Transp. Syst., vol. 20, no. 2, pp. 507–521, 2019, doi: 10.1109/TITS.2018.2816811.

[31] B. Garau, A. Alvarez, and G. Oliver, “Path planning of autonomous underwater vehicles in current fields with complex spatial variability: An A* approach,” Proc. - IEEE Int. Conf. Robot. Autom., vol. 2005, no. April, pp. 194–198, 2005, doi: 10.1109/ROBOT.2005.1570118.

[32] K. Garg, N. Ramakrishnan, A. Prakash, and T. Srikanthan, “Rapid and Robust Background Modeling Technique for Low-Cost Road Traffic Surveillance Systems,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 5, pp. 2204–2215, 2020, doi: 10.1109/TITS.2019.2917560.

[33] R. B. Pendor and P. P. Tasgaonkar, “An IoT framework for intelligent vehicle monitoring system,” Int. Conf. Commun. Signal Process. ICCSP 2016, pp. 1694–1696, 2016, doi: 10.1109/ICCSP.2016.7754454.

[34] P. Giannakeris, V. Kaltsa, K. Avgerinakis, A. Briassouli, S. Vrochidis, and I. Kompatsiaris, “Speed estimation and abnormality detection from surveillance cameras,” IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Work., vol. 2018-June, pp. 93–99, 2018, doi: 10.1109/CVPRW.2018.00020.

[35] S. Pohlmann and U. Traenkle, “Orientation in road traffic. Age-related differences using an in-vehicle navigation system and a conventional map,” Accid. Anal. Prev., vol. 26, no. 6, pp. 689–702, 1994, doi: 10.1016/0001-4575(94)90048-5.

[36] M. G. Gnoni, A. Rollo, and P. Tundo, “A smart model for urban ticketing based on RFID applications,” IEEM 2009 - IEEE Int. Conf. Ind. Eng. Eng. Manag., pp. 2353–2357, 2009, doi: 10.1109/IEEM.2009.5373004.

[37] R. J. Reisman, “Air traffic management blockchain infrastructure for security, authentication, and privacy,” AIAA Scitech 2019 Forum, pp. 1–14, 2019, doi: 10.2514/6.2019-2203.

[38] E. Guerra, “Planning for Cars That Drive Themselves: Metropolitan Planning Organizations, Regional Transportation Plans, and Autonomous Vehicles,” J. Plan. Educ. Res., vol. 36, no. 2, pp. 210–224, 2016, doi: 10.1177/0739456X15613591.

[39] G. Guido, V. Gallelli, D. Rogano, and A. Vitale, “Evaluating the accuracy of vehicle tracking data obtained from Unmanned Aerial Vehicles,” Int. J. Transp. Sci. Technol., vol. 5, no. 3, pp. 136–151, 2016, doi: 10.1016/j.ijtst.2016.12.001.

[40] G. Guido, A. Vitale, F. F. Saccomanno, V. Astarita, and V. Giofrè, “Vehicle Tracking System based on Videotaping Data,” Procedia - Soc. Behav. Sci., vol. 111, pp. 1123–1132, 2014, doi: 10.1016/j.sbspro.2014.01.147.

[41] S. Parekh, N. Dhami, S. Patel, and J. Undavia, “Traffic signal automation through iot by sensing and detecting traffic intensity through ir sensors,” Smart Innov. Syst. Technol., vol. 106, pp. 53–65, 2019, doi: 10.1007/978-981-13-1742-2_6

[42] H. Gunawan and Lynawati, “Analisis Penerimaan Teknologi ‘Smart City’ Kota Purwokerto Dengan Model Technology Acceptance Model (TAM),” Konf. Nas. Sist. Inf., pp. 129–134, 2018, [Online]. Available:

[43] D. Parker, J. T. Reason, A. S. R. Manstead, and S. G. Stradling, “Driving errors, driving violations and accident involvement,” Ergonomics, vol. 38, no. 5, pp. 1036–1048, 1995, doi: 10.1080/00140139508925170.

[44] C. El Hatri and J. Boumhidi, “Fuzzy deep learning based urban traffic incident detection,” 2017 Intell. Syst. Comput. Vision, ISCV 2017, 2017, doi: 10.1109/ISACV.2017.8054903.

[45] S. D. Pendleton et al., “Perception, planning, control, and coordination for autonomous vehicles,” Machines, vol. 5, no. 1, pp. 1–54, 2017, doi: 10.3390/machines5010006.

[46] J. Z. Hernández, S. Ossowski, and A. García-Serrano, “Multiagent architectures for intelligent traffic management systems,” Transp. Res. Part C Emerg. Technol., vol. 10, no. 5–6, pp. 473–506, 2002, doi: 10.1016/S0968-090X(02)00032-3.

[47] J. I. Hernández-Vega, E. R. Varela, N. H. Romero, C. Hernández-Santos, J. L. S. Cuevas, and D. G. P. Gorham, Internet of things (IoT) for monitoring air pollutants with an unmanned aerial vehicle (UAV) in a smart city, vol. 213. Springer International Publishing, 2018.

[48] G. T. S. Ho, Y. P. Tsang, C. H. Wu, W. H. Wong, and K. L. Choy, “A computer vision-based roadside occupation surveillance system for intelligent transport in smart cities,” Sensors (Switzerland), vol. 19, no. 8, 2019, doi: 10.3390/s19081796.

[49] Y. Huang, Z. Liu, M. Jiang, X. Yu, and X. Ding, “Cost-Effective Vehicle Type Recognition in Surveillance Images with Deep Active Learning and Web Data,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 1, pp. 79–86, 2020, doi: 10.1109/TITS.2018.2888698.

[50] N. K. Jain, R. K. Saini, and P. Mittal, A review on traffic monitoring system techniques, vol. 742. Springer Singapore, 2019.

[51] José Miguel Cisneros Herreros and Germán Peñalva Moreno, “Article in Press Article in Press,” GEF Bull. Biosci., vol. 1, no. 1, pp. 1–6, 2010, doi: 10.1016/j.jinf.2020.02.020.

[52] R. Kala and K. Warwick, “Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes,” Eng. Appl. Artif. Intell., vol. 26, no. 5–6, pp. 1588–1601, 2013, doi: 10.1016/j.engappai.2013.02.001.

[53] Kenny, “United States Patent (19) 11 Patent Number: 5,348,136,” no. 19, pp. 1992–1995, 1993.

[54] B. Nemade, “Automatic Traffic Surveillance Using Video Tracking,” Procedia Comput. Sci., vol. 79, pp. 402–409, 2016, doi: 10.1016/j.procs.2016.03.052.

[55] H. J. Kim, “Vehicle detection and speed estimation for automated traffic surveillance systems at nighttime,” Teh. Vjesn., vol. 26, no. 1, pp. 87–94, 2019, doi: 10.17559/TV-20170827091448.

[56] K. J. Kim, P. K. Kim, Y. S. Chung, and D. H. Choi, “Multi-Scale Detector for Accurate Vehicle Detection in Traffic Surveillance Data,” IEEE Access, vol. 7, pp. 78311–78319, 2019, doi: 10.1109/ACCESS.2019.2922479.

[57] S. W. Kim, W. Liu, M. H. Ang, E. Frazzoli, and D. Rus, “The Impact of Cooperative Perception on Decision Making and Planning of Autonomous Vehicles,” IEEE Intell. Transp. Syst. Mag., vol. 7, no. 3, pp. 39–50, 2015, doi: 10.1109/MITS.2015.2409883.

[58] T. Kumar and D. S. Kushwaha, “An intelligent surveillance system based on IoT for internal security of a nation,” Int. J. Inf. Secur. Priv., vol. 13, no. 3, pp. 1–30, 2019, doi: 10.4018/IJISP.201907010101.

[59] X. Li, J. Niu, S. Kumari, F. Wu, and K. K. R. Choo, “A robust biometrics based three-factor authentication scheme for Global Mobility Networks in smart city,” Futur. Gener. Comput. Syst., vol. 83, pp. 607–618, 2018, doi: 10.1016/j.future.2017.04.012.

[60] M. Likhachev and D. Ferguson, “Planning long dynamically-feasible maneuvers for autonomous vehicles,” Robot. Sci. Syst., vol. 4, pp. 214–221, 2009, doi: 10.15607/rss.2008.iv.028.

[61] V. Murugan, V. R. Vijaykumar, and A. Nidhila, “A deep learning RcNn approach for vehicle recognition in traffic surveillance system,” Proc. 2019 IEEE Int. Conf. Commun. Signal Process. ICCSP 2019, pp. 157–160, 2019, doi: 10.1109/ICCSP.2019.8698018.

[62] M. Lu et al., “Cooperative and connected intelligent transport systems for sustainable European road transport Citation for published version (APA): Cooperative and Connected Intelligent Transport Systems for Sustainable European Road Transport,” no. 2018, 2018, [Online]. Available:

[63] P. G. V. Naranjo, Z. Pooranian, M. Shojafar, M. Conti, and R. Buyya, “FOCAN: A Fog-supported smart city network architecture for management of applications in the Internet of Everything environments,” J. Parallel Distrib. Comput., vol. 132, pp. 274–283, 2019, doi: 10.1016/j.jpdc.2018.07.003.

[64] Z. Lv, X. Li, W. Wang, B. Zhang, J. Hu, and S. Feng, “Government affairs service platform for smart city,” Futur. Gener. Comput. Syst., vol. 81, pp. 443–451, 2018, doi: 10.1016/j.future.2017.08.047.

[65] K. Nellore and G. P. Hancke, “A survey on urban traffic management system using wireless sensor networks,” Sensors (Switzerland), vol. 16, no. 2, 2016, doi: 10.3390/s16020157.

[66] S. Lyu et al., “UA-DETRAC 2018: Report of AVSS2018 IWT4S Challenge on Advanced Traffic Monitoring,” Proc. AVSS 2018 - 2018 15th IEEE Int. Conf. Adv. Video Signal-Based Surveill., pp. 1–7, 2019, doi: 10.1109/AVSS.2018.8639089.

[67] V. C. Maha Vishnu, M. Rajalakshmi, and R. Nedunchezhian, “Intelligent traffic video surveillance and accident detection system with dynamic traffic signal control,” Cluster Comput., vol. 21, no. 1, pp. 135–147, 2018, doi: 10.1007/s10586-017-0974-5.

[68] V. A. Memos, K. E. Psannis, Y. Ishibashi, B. G. Kim, and B. B. Gupta, “An Efficient Algorithm for Media-based Surveillance System (EAMSuS) in IoT Smart City Framework,” Futur. Gener. Comput. Syst., vol. 83, no. 2018, pp. 619–628, 2018, doi: 10.1016/j.future.2017.04.039.

[69] A. Mhalla, T. Chateau, S. Gazzah, and N. E. Ben Amara, “An Embedded Computer-Vision System for Multi-Object Detection in Traffic Surveillance,” IEEE Trans. Intell. Transp. Syst., vol. 20, no. 11, pp. 4006–4018, 2019, doi: 10.1109/TITS.2018.2876614.

[70] J. S. B. Mitchell, D. W. Payton, and D. M. Keirsey, “Planning and reasoning for autonomous vehicle control,” Int. J. Intell. Syst., vol. 2, no. 2, pp. 129–198, 1987, doi: 10.1002/int.4550020204.

[71] A. Murtaza, S. J. Hussain Pirzada, L. Jianwei, and T. Xu, “Air traffic surveillance using IP-Based space information network,” 2019 28th Wirel. Opt. Commun. Conf. WOCC 2019 - Proc., no. May, 2019, doi: 10.1109/WOCC.2019.8770697.