Intelligent Transportation System based on the Whale Algorithm in Internet of Things

Abdollahi, M.; Boujarnezhad, Z.

doi:10.22061/jecei.2022.8184.494

تعداد نشریات	11
تعداد شماره‌ها	237
تعداد مقالات	2,398
تعداد مشاهده مقاله	3,830,611
تعداد دریافت فایل اصل مقاله	2,775,223

	Intelligent Transportation System based on the Whale Algorithm in Internet of Things
Journal of Electrical and Computer Engineering Innovations (JECEI)
مقاله 8، دوره 10، شماره 2، مهر 2022، صفحه 351-362 اصل مقاله (1.05 M)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22061/jecei.2022.8184.494
نویسندگان
M. Abdollahi^* ¹؛ Z. Boujarnezhad²
¹School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran.
²Department of Computer Engineering, Pooyesh Institute of Higher Education, Qom, Iran.
تاریخ دریافت: 16 آبان 1400، تاریخ بازنگری: 10 بهمن 1400، تاریخ پذیرش: 16 بهمن 1400
چکیده
Background and Objectives: As cities are developing and the population increases significantly, one of the most important challenges for city managers is the urban transportation system. An Intelligent Transportation System (ITS) uses information, communication, and control techniques to assist the transportation system. The ITS includes a large number of traffic sensors that collect high volumes of data to provide information to support and improve traffic management operations. Due to the high traffic volume, the classic methods of traffic control are unable to satisfy the requirements of the variable, and the dynamic nature of traffic. Accordingly, Artificial Intelligence and the Internet of Things meet this demand as a decentralized solution. Methods: This paper presents an optimal method to find the best route and compare it with the previous methods. The proposed method has three phases. First, the area should be clustered under servicing and, second, the requests will be predicted using the time series neural network. then, the Whale Optimization Algorithm (WOA) will be run to select the best route. Results: To evaluate the parameters, different scenarios were designed and implemented. The simulation results show that the service time parameter of the proposed method is improved by about 18% and 40% in comparison with the Grey Wolf Optimizer (GWO) and Random Movement methods. Also, the difference between this parameter in the two methods of Harris Hawks Optimizer (HHO) and WOA is about 5% and the HHO has performed better. Conclusion: The interaction of AI and IoT can lead to solutions to improve ITS and to increase client satisfaction. We use WOA to improve time servicing and throughput. The Simulation results show that this method can be increase satisfaction for clients.
کلیدواژه‌ها
Grey Wolf Optimization؛ Whale Optimization Algorithm؛ Internet of Things؛ Intelligent Transportation System

مراجع
[1] K. Iqbal, M.A. Khan, S. Abbas, Z. Hasan, A. Fatima, “Intelligent transportation system (ITS) for smart-cities using Mamdani Fuzzy Inference System,” Int. J. Adv. Comput. Sci. Appl., 9(2): 94–105, 2018. [2] A. Boukerche, Y. Tao, P. Sun, “Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems,” Comput. Networks, 182: 107484, 2020. [3] R.M. Cardoso, N. Mastelari, M.F. Bassora, “Internet of things architecture in the context of intelligent transportation systems—a case study towards a web-based application deployment,” in Proc. 22nd International Congress of Mechanical Engineering (COBEM 2013): 7751–7760, 2013. [4] C. Chen, H. Liu, Z. Wang, “Analysis and design of urban traffic congestion in urban intelligent transportation system based on big data and internet of Things,” in Proc. 2019 International Conference on Artificial Intelligence and Computer Science: 659–665, 2019. [5] Z. Deng, T. Zhang, D. Liu, X. Jing, Z. Li, “A high-precision collaborative control algorithm for multi-agent system based on enhanced depth image fusion positioning,” IEEE Access, 8: 34842–34853, 2020. [6] A.A. Brincat, F. Pacifici, S. Martinaglia, F. Mazzola, “The internet of things for intelligent transportation systems in real smart cities scenarios,” in Proc. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT): 128–132, 2019. [7] A. Ghosh, D. Chakraborty, A. Law, “Artificial intelligence in Internet of Things,” CAAI Trans. Intell. Technol., 3(4): 208–218, 2018. [8] J. Guerrero-Ibáñez, S. Zeadally, J. Contreras-Castillo, “Sensor technologies for intelligent transportation systems,” Sensors, 18(4): 1212, 2018. [9] K. Nellore, G.P. Hancke, “A survey on urban traffic management system using wireless sensor networks,” Sensors, 16(2): 157, 2016. [10] Z. Boujarnezhad, M. Abdollahi, “Optimization of roadside assistance transportation based on the gray wolf algorithm in the internet of Things (in Persian),” in Proc. 28th Iran. Conf. Electr. Eng. (ICEE 2020): 683–689, 2020. [11] S. Mirjalili, S.M. Mirjalili, A. Lewis, “Grey wolf optimizer,” Adv. Eng. Softw., 69: 46–61, 2014. [12] A.A. Heidari, S. Mirjalili, H. Faris, I. Aljarah, M. Mafarja, H. Chen, “Harris hawks optimization: Algorithm and applications,” Futur. Gener. Comput. Syst., 97: 849–872, 2019. [13] P. Kuppusamy, R. Kalpana, P.V. Venkateswara Rao, “Optimized traffic control and data processing using IoT,” Cluster Comput., 22: 2169–2178, 2019. [14] A. Dubey, M. Lakhani, S. Dave, J.J. Patoliya, “Internet of Things based adaptive traffic management system as a part of Intelligent Transportation System (ITS),” in Oroc. 2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp): 1–6, 2017. [15] S. Javaid, A. Sufian, S. Pervaiz, M. Tanveer, “Smart traffic management system using Internet of Things,” in Proc. 2018 20th International Conference on Advanced Communication Technology (ICACT): 393–398, 2018. [16] P. Pyykönen, J. Laitinen, J. Viitanen, P. Eloranta, T. Korhonen, “IoT for intelligent traffic system,” in Proc. 2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP): 175–179, 2013. [17] T. Bojan, U. Kumar, V. Bojan, “An internet of things based intelligent transportation system,” in Proc. 2014 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2014): 174–179, 2014. [18] S. Geetha, D. Cicilia, “IoT enabled intelligent bus transportation system,” in 2017 2nd International Conference on Communication and Electronics Systems (ICCES): 7–11, 2017. [19] S.H. Sutar, R. Koul, R. Suryavanshi, “Integration of smart phone and IOT for development of smart public transportation system,” in Proc. 2016 International Conference on Internet of Things and Applications (IOTA): 73–78, 2016. [20] S.K. Datta, R.P.F. Da Costa, J. Harri, C. Bonnet, “Integrating connected vehicles in Internet of Things ecosystems: Challenges and solutions,” in Proc. 17th Int. Symp. a World Wireless, Mob. Multimed. Networks (WoWMoM 2016), 2016. [21] M. Desai, A. Phadke, “Internet of Things based vehicle monitoring system,” IFIP Int. Conf. Wirel. Opt. Commun. Networks (WOCN): 1–3, 2017. [22] A. Al-Dweik, R. Muresan, M. Mayhew, M. Lieberman, “IoT-based multifunctional scalable real-time enhanced road side unit for intelligent transportation systems,” in Proc. 2017 IEEE 30th Canadian conference on electrical and computer engineering (CCECE): pp. 1–6, 2017. [23] J. Jalaney, R.S. Ganesh, “Review on IoT based architecture for smart public transport system,” Int. J. Appl. Eng. Res., 14(2): 466–471, 2019. [24] F. Zhu, Y. Lv, Y. Chen, X. Wang, G. Xiong, F.-Y. Wang, “Parallel transportation systems: toward IoT-enabled smart urban traffic control and management,” IEEE Trans. Intell. Transp. Syst., 2019. [25] K.N. Qureshi, A.H. Abdullah, “A survey on intelligent transportation systems,” Middle East J. Sci. Res., 15(5): 629–642, 2013. [26] D.F. Murad, B.S. Abbas, A. Trisetyarso, W. Suparta, C.H. Kang, “Development of smart public transportation system in Jakarta city based on integrated IoT platform,” in Proc. 2018 Int. Conf. Inf. Commun. Technol. (ICOIACT 2018): 872–877, 2018. [27] A. Thakur, R. Malekian, D.C. Bogatinoska, “Internet of Things based solutions for road safety and traffic management in intelligent transportation systems,” Commun. Comput. Inf. Sci., 778: 47–56, 2017. [28] A.H. Sodhro et al., “Quality of service optimization in an iot-driven intelligent transportation system,” IEEE Wirel. Commun., 26(6): 10–17, 2019. [29] A.H. Sodhro, J.J.P.C. Rodrigues, S. Pirbhulal, N. Zahid, A.R.L. de Macedo, V.H.C. de Albuquerque, “Link optimization in software defined IoV driven autonomous transportation system,” IEEE Trans. Intell. Transp. Syst., 22(6): 3511-3520, 2020. [30] A.H. Sodhro et al., “Towards 5G-Enabled self adaptive green and reliable communication in intelligent transportation system,” IEEE Trans. Intell. Transp. Syst., 99: 1–9, 2020. [31] S.M. Odeh, “Management of an intelligent traffic light system by using genetic algorithm,” J. Image Graph., 1(2): 90–93, 2013. [32] Z. Li, M. Shahidehpour, S. Bahramirad, A. Khodaei, “Optimizing traffic signal settings in smart cities,” IEEE Trans. Smart Grid, 8(5): 2382–2393, 2016. [33] P. Zhou, Z. Fang, H. Dong, J. Liu, S. Pan, “Data analysis with multi-objective optimization algorithm: A study in smart traffic signal system,” in 2017 IEEE 15th International Conference on Software Engineering Research, Management and Applications (SERA), 307–310, 2017. [34] A.A. Osuwa, E.B. Ekhoragbon, L.T. Fat, “Application of artificial intelligence in Internet of Things,” in Proc. 2017 9th International Conference on Computational Intelligence and Communication Networks (CICN): 169–173, 2017. [35] R. Hamidouche, Z. Aliouat, A.A.A. Ari, M. Gueroui, “An efficient clustering strategy avoiding buffer overflow in IoT sensors: a bio-inspired based approach,” IEEE Access, 7: 156733–156751, 2019. [36] R.K. Yadav, R. Jain, S. Yadav, S. Bansal, “Dynamic traffic management system using neural network based iot system,” in Proc. the International Conference on Intelligent Computing and Control Systems (ICICCS 2020): 521–526, 2020. [37] Z. Liu, C. Wang, “Design of traffic emergency response system based on Internet of Things and data mining in emergencies,” IEEE Access, 7: 113950–113962, 2019. [38] M. Elhenawy, A.A. Elbery, A.A. Hassan, H.A. Rakha, “An intersection game-theory-based traffic control algorithm in a connected vehicle environment,” in Proc. IEEE Conf. Intell. Transp. Syst. (ITSC): 343–347, 2015. [39] X. Wang, Y. Wang, L. Wang, “Improving fuzzy c-means clustering based on feature-weight learning,” Pattern Recognit. Lett., 25(10): 1123–1132, 2004. [40] P. Arora, S. Varshney, et al., “Analysis of k-means and k-medoids algorithm for big data,” Procedia Comput. Sci., 78: 507–512, 2016. [41] M. Rocha, P. Cortez, J. Neves, “Evolution of neural networks for classification and regression,” Neurocomputing, 70,(16–18): 2809–2816, 2007. [42] F. Raue, W. Byeon, T.M. Breuel, M. Liwicki, “Parallel sequence classification using recurrent neural networks and alignment,” in Proc. Int. Conf. Doc. Anal. Recognition (ICDAR): 581–585, 2015. [43] S. Mirjalili, A. Lewis, “The whale optimization algorithm,” Adv. Eng. Software, 95: 51–67, 2016. [44] I.N. Trivedi, J. Pradeep, J. Narottam, K. Arvind, L. Dilip, “Novel adaptive whale optimization algorithm for global optimization,” Indian J. Sci. Technol., 9(38): 319–326, 2016. [45] I. Aljarah, H. Faris, S. Mirjalili, “Optimizing connection weights in neural networks using the whale optimization algorithm,” Soft Comput., 22(1): 1–15, 2018.
آمار تعداد مشاهده مقاله: 1,020 تعداد دریافت فایل اصل مقاله: 575

سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب

پیوندهای مفید

آمار

Intelligent Transportation System based on the Whale Algorithm in Internet of Things