International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 13, No. 3, 8 Jun. 2021
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IoT Bus Navigation System with Optimized Routing using Machine Learning
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Author(s)
Index Terms
RFID, System-on-Chip, Machine learning, Cloud computing
Abstract
As the population in Egypt is ever expanding, it is reflected in the increase of the number of vehicles on the road. Public transportation is the solution and the number of available buses can cover a significant amount of the population demand. However, the outdated state of the transportation infrastructure, the static nature of the lines and indistinct schedules create a confounding and unappealing user experience which prompts the users to stray to cars for their needs. So, an Intelligent Urban Transportation System (IUTS) is a must. IUTS is a multi-layered system which provides the solution for most of these problems. It operates on different layers starting from a real time vehicle tracking for transparent and efficient management of assets, cash-less ticketing done through RFID cards, vehicle health and diagnostic data for creation of automated maintenance schedules and a friendly interactive driver interface. In this paper an approach based on combining all these technologies is discussed where the hardware component is implemented based on System-on-Chip technology with custom hardware to interface with the vehicle. The data collected from the on-board unit is sent to the cloud, and with the help of machine learning algorithms the dynamic responsiveness of the system is guaranteed. The proposed system outperforms other existing ones through the dynamic and optimized routing feature for the bus navigation to optimize the operating cost but still satisfy the passengers' demand.
Cite This Paper
Samer I. Mohamed, Muhamed Abdelhadi, "IoT Bus Navigation System with Optimized Routing using Machine Learning", International Journal of Information Technology and Computer Science(IJITCS), Vol.13, No.3, pp.1-15, 2021. DOI:10.5815/ijitcs.2021.03.01
Reference
[1]Central Agency for Public Mobilization and Statistics,” Egypt In Figures”, 2015.
[2]SWVL,” Egyptian start-up Swvl raises USD 8 million in series A funding round”, 2018.
[3]K. Ltd,” KPIT — On-Bus Intelligent Transport System”, KPIT Technologies Ltd, 2018. Available at: https://www.kpit.com/what-wedo/products/on-bus-its.
[4]B. Hamilton, History of intelligent transportation systems, U.S. Department of Transportation, 2016.
[5]T. Matters, Facts & figures”, Transport for London, 2018. Available at: https://tfl.gov.uk/corporate/about-tfl/what-we-do/londonunderground/
[6]Seoul Transport Operation & Information Service, Topis.seoul.go.kr, 2018. Available at: http://topis.seoul.go.kr/eng/page/transInfo 1 1.jsp.
[7]Angelakis, V., Tragos, E., Pohls, H., Kapovits, A. and Bassi, A. Designing, developing, and facilitating smart cities, 2017.
[8]Bhusiri, N., Qureshi, A.G. and Taniguchi, E, The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem, Transportation Research Part E, 62, 1 -22, 2017
[9]V. Bogdanov, How To Choose The Right Tech Stack For Your Software Development Project, Welcome to Intersog Your App Development Partner in Chicago, 2018. Available at: https://intersog.com/blog/tech-tips/how-to-choose-the-right-tech- stackfor- your-software-development-project/.
[10]C. Pirson, Optimization of a demand-responsive transit system, Master Thesis, University of Lige, 2017.
[11]Czarnowski, I., Caballero, A., Howlett, R. and Jain, L. “Intelligent Decision Technologies”, 2017
[12]H. Yahyaoui, I. Kaabachi, S. Krichen and A. Dekdouk, Two metaheuristic approaches for solving the multi-compartment vehicle routing problem, Operational Research, 2018.
[13]N. Landwehr, M. Hall and E. Frank, Logistic Model Trees, Machine Learning, vol. 59, no. 1-2, pp. 161-205, 2005.
[14]C. Pornsing, A practice swarm optimization for the vehicle routing, Ph.D, University of Rhode island, 2014.
[15]P. Samaras, A. Fachantidis, G. Tsoumakas and I. Vlahavas, A prediction model of passenger demand using AVL and APC data from a bus fleet, Proceedings of the 19th Panhellenic Conference on Informatics – PCI ’15, 2015.
[16]B. Rohrer, Brandon Rohrer - Instructor - End-to-End Machine Learning, Brohrer.github.io, 2017. Available at: https://brohrer.github.io/blog.html.
[17]V. Kachitvichyanukul, P. Sombuntham and S. Kunnapapdeelert, Two solution representations for solving multi-depot vehicle routing problem with multiple pickup and delivery requests via PSO, Computers & Industrial Engineering, vol. 89, pp. 125-136, 2015.
[18]W. Fan and R. Machemehl, using a Simulated Annealing Algorithm to Solve the Transit Route Network Design Problem, Journal of Transportation Engineering, vol. 132, no. 2, pp. 122-132, 2006.
[19]A. Karpathy, The Unreasonable Effectiveness of Recurrent Neural Networks, 2015. Available at: https://karpathy.github.io/2015/05/21/rnn-effectiveness/.
[20]P. Umrao, Intelligent Transportation System, Institute of Engineering & Technology, Lucknow, 2015.
[21]Q. Yang, L. Wang, W. Xia, Y. Wu and L. Shen, Development of on-board unit in vehicular adhoc network for highways, International Conference on Connected Vehicles and Expo (ICCVE), Vienna, pp. 457-462, 2014.
[22]Petracca, Matteo & Pagano, P & Pelliccia, Riccardo & Ghibaudi, Marco & Salvadori, Claudio & Nastasi, C. On-Board Unit hardware and software design for Vehicular Ad-hoc Networks. Roadside Networks for Vehicular Communications: Architectures, Applications, and Test Fields. 10.4018/978-1-4666-2223-4.ch002, 2012
[23]Bello, Irwan, Pham, Hieu, Le, Quoc V, Norouzi, Mohammad, and Bengio, Samy. Neural combinatorial optimization with reinforcement learning, 2016.
[24]Cho, Kyunghyun, Van Merri¨enboer, Bart, Gulcehre, Caglar, Bahdanau, Dzmitry, Bougares, Fethi, Schwenk, Holger, and Bengio, Yoshua. Learning phrase representations using rnn encoder-decoder for statistical machine translation, Conference on Empirical Methods in Natural Language Processing, 2014.
[25]Clarke, Geoff and Wright, John W. Scheduling of vehicles from a central depot to a number of delivery points. Operations research, 12(4):568–581, 1964.
[26]Dai, Hanjun, Dai, Bo, and Song, Le. Discriminative embeddings of latent variable models for structured data, In International Conference on Machine Learning, pp. 2702–2711, 2016.
[27]Dai, Hanjun, Khalil, Elias B, Zhang, Yuyu, Dilkina, Bistra, and Song, Le. Learning combinatorial optimization algorithms over graphs, Advances in Neural Information Processing Systems, 2017.
[28]T. X. Brown, Low power wireless communication via reinforcement learning, In Advances in Neural Information Processing Systems, volume 12, pages 893–899, 1999.
[29]T. X. Brown, H. Tong, and S. P. Singh, optimizing admission control while ensuring quality of service in multimedia networks via reinforcement learning, In Advances in Neural Information Processing Systems, volume 12, pages 982–988, 1999.
[30]J. Carlstrom, Reinforcement Learning for Admission Control and Routing, PhD thesis, Uppsala University, Uppsala, Sweden, May 2000.
[31]E. Dijkstra, A note on two problems in connection with graphs, Numerical Mathematics, 1:269–271, 1959.
[32]L. P. Kaelbling, M. L. Littman, and A. W. Moore. Reinforcement learning: A survey, Journal of AI Research, 4:237–277, 1996.
[33]P. Marbach, O. Mihatsch, M. Schulte, and J. N. Tsitsiklis Reinforcement learning for call admission control and routing in integrated service networks, In Advances in Neural Information Processing Systems, volume 11, 1998.
[34]https://www.uber.com/en-EG/blog/introducing-uber-bus-a-new-way-to-commute/ (accessed Nov 1 2020)
[35]https://swvl.com/eg-en (Accessed Oct 1 2020)
[36] Active Selection Constraints for Semi-supervised Clustering Algorithms", International Journal of Information Technology and Computer Science, Vol.12, No.6, pp.23-30, 2020.
[37] Iram Mehmood, Sidra Anwar, AneezaDilawar, IsmaZulfiqar, Raja Manzar Abbas, "Managing Data Diversity on the Internet of Medical Things (IoMT)", International Journal of Information Technology and Computer Science, Vol.12, No.6, pp.49-56, 2020.
[38] Nur Kumala Dewi, " Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept ", International Journal of Engineering and Manufacturing, Vol.11, No.1, pp. 29-36, 2021.
[39] Anna Merine George, S.Y Kulkarni, Vice Chancellor,"Cluster based Routing Protocols for IOT Application", International Journal of Computer Network and Information Security, Vol.11, No.5, pp.43- 49, 2019.
[40] Nur Kumala Dewi, " Review of Vehicle Surveillance Using Iot in the Smart Transportation Concept ", International Journal of Engineering and Manufacturing, Vol.11, No.1, pp. 29-36, 2021.