Everything and everyone is growing smarter day-by-day, from a small kid to an entire nation. The current research incorporates a thorough study on intelligent transportation, keeping the former view in mind. It briefly highlights the need for an eficient transport system in India and analyses what factors lead to the need for more eficient transport systems in the making of a smart city. With the current tech-savvy society, it has become necessary to propose such a system that can not only benefit society but also the environment, as the current emission of harmful gases has been outnumbered by excessive trafic more than any other source. Next, the research proposes a novel framework that links three diferent subsystems, each with its own functionality, for a new and eficient method of transport. While describing the proposed approach, the paper discusses the need for society and the government to be a pivotal factor in supporting and maintaining such frameworks to increase the safety, security, and wellbeing of every vehicle driver.
A ’Smart City’, as the name suggests, uses technology to provide intelligent and quickly
responsive support to the needs of the city, further contributing to the growth of a nation and
the development of the country as a whole [
The remaining article is as follows: Section 2 provides insights into current works existing in developing smart transportation systems. Section 3 briefly discusses the role of transportation in smart cities. The proposed framework with subsystems is discussed in Section 4. Next, Section 5 discusses the opportunities and challenges in the implementation of intelligent transportation while Section 6 concludes the paper.
Several papers [
Research in [11] proposes another framework that coordinates the Internet of Things with the proposed advanced transportation framework in order to provide better transportation, but excellent wireless connectivity [12] is required for the same. The framework in [13], [14] utilises the sensors to screen the climate, which is then utilised by the observing framework to illuminate the drivers in regards to the situating of the gadget and subtleties relating to it.
Accordingly, this data can be productively used to control vehicle trafic but requires high performance computing [15], [16]. All signs from advanced camcorders are sent to focal frameworks that break down trafic streams. As of now, the measurable in-line information is gathered in the genuine working items where camcorders with programming support are linked so they can perceive vehicles and their permit figures. At the point when this data is gathered, it is feasible to assess the efectiveness of the data gathering subsystem exhaustively [ 17]. Overall, every research [17], [18], [19] [20], [21], [22], [23][24] in one way or the other suggests that the development in technology aids in demonstrating frameworks with high adaptability.
In India, the Smart Cities Mission represents a pioneering initiative that will spur economic development and improve people’s quality of life by stimulating local development and leveraging technology as a means to create smart outcomes for citizens, including better public transport services, one of the key infrastructure elements of smart cities. Smart transport is a pivotal factor in establishing the concept of a smart city. To further improve the well-being of the people and the environment, society can act as an impactful factor in present-day transport systems by proactively maintaining legislation. Lastly, the word "smart" itself shows the significance of technology, the role it plays, and its relationship to smart transportation.
The proposed framework is a part of existing subsystems, making use of diferent concepts, technologies, and subsystems as discussed in the following subsections:
Figure 2 depicts Subsystem 1.The actor is an individual who wishes to drive the vehicle and has all the necessary information in the form of a card or other means. Now these details will be passed onto an authenticator, who checks whether the details of the actor are valid for travel or not. The Details DB will carry all the information about the trip with input from the authenticated actor of the destination. The Authenticator will be an IoT device [25, 26] that can fetch and match the details provided by the actor with the true details in the Transport Department.
Subsystem 2 depicted in Figure 3 is a regulation and monitoring subsystem. First, it will focus on the regulatory measures depending on the vehicle details, primarily the type of vehicle, being input from the Details DB. These regulatory measures are those which are set by the respective Transport Department of the city, and will include things such as the speed limit of 45kmph for two-wheelers and 60kmph for four-wheelers in Chandigarh, India. Based on the actor’s response to these regulatory details during the trip, it will send the response as after ride details to the monitoring system. The monitoring system will now check for the defaulters of regulatory measures, attaching a tag of defaulter or non-defaulter to it with the after-ride details and, in return, sending it as a report to the Details DB.
The subsystem 3 depicted in Figure 4 is responsible for end-user benefit and conveyance. It fetches the report from the Details DB, which is passed on to the actor as a response to having the details of the last travel with every fault and warning. On the other hand, the report is also provided to the data-analysis mechanism, which will be required to access the defaulters and non-defaulters. Based on the data analysis performed by this subsystem, potential candidates for incentives can be found, which can be awarded through the incentive mechanism by the respective transport department after a travel of a certain number of kilometres or so.
The subsystems shown in the previous system are an abstract representation of what the complete system will look like. For diferent phases of evaluation, these subsystems will arouse further opportunities in the domains of artificial intelligence, data engineering, IoT, etc. It is true that eficient trafic and transport systems have been the need of the hour for smart cities for a long time now. This implies that if a proposed system like the one suggested in the paper, with a non-abstract design, is implemented, it could lead to the world’s finest transport system. Indeed, the obstacles are high – whether it is the infrastructure, the number of vehicles, or the growing population – but it is in our hands to propose such changes to the existing system and in the hands of the government to implement them, so that there is a reduction in not only trafic but also other environmental efects with a regular check on the vehicles via smart cards with IoT features.The same, if utilised to the benefit of the general public, can help improvise the concept of a smart city and thereby build a smart nation afterward.
The market for transportation systems is profoundly encouraging for society [27]. As the transportation frameworks for brilliant urban communities are being used all throughout the planet, people can start to procure the numerous security, efectiveness, and money-saving advantages that accompany the present-day public vehicle. It is energising to ponder how society may associate their urban communities with the most recent innovations that are opening up today. The future work of this research will focus on the details and less abstraction of the proposed subsystems of the stated framework and is in continuation of the stated work. Truly, a high-performance computing back-end infrastructure is required to implement the proposed autonomous system with an end-to-end flow of development for millions of vehicles, but it is perfectly possible to be implemented with available and in-hand resources. analysis, in: P. Verma, C. Charan, X. Fernando, S. Ganesan (Eds.), Advances in Data Computing, Communication and Security, Springer Singapore, Singapore, 2022, p. in press.
URL: https://link.springer.com/book/9789811684029. [11] A. Amini, J. de la Garza, Computer simulations of the vehicle localization for intelligent transportation systems, in: International Conference on Computing in Civil and Building Engineering 2014, 2014, pp. 1118–1125. doi:10.1061/9780784413616.139. [12] S. Kr, A. Kumar, M. Rachna, S. Gupta, R. Madan, Architectural performance of wimax over wifi with reliable qos over wireless communication, International Journal of Advanced Networking and Applications 03 (2011). [13] K. Ashokkumar, B. Sam, R. Arshadprabhu, Britto, Cloud based intelligent transport system, Procedia Computer Science 50 (2015) 58–63. URL: https://doi.org/10.1016/j.procs.2015.04. 061. doi:10.1016/j.procs.2015.04.061. [14] T. M. Bojan, U. R. Kumar, V. M. Bojan, An internet of things based intelligent transportation system, in: 2014 IEEE International Conference on Vehicular Electronics and Safety, IEEE, 2014, pp. 174 – 179. URL: https://doi.org/10.1109/icves.2014.7063743. doi:10.1109/icves. 2014.7063743. [15] S. Singh, Performance evaluation of hybrid reconfigurable computing architecture over symmetrical fpga, International Journal of Embedded Systems and Applications 2 (2012) 107–116. doi:10.5121/ijesa.2012.2312. [16] S. Singh, K. Kaur, A. Aggarwal, D. Verma, Achieving high performance distributed system: Using grid, cluster and cloud computing, Int. Journal of Engineering Research and Application ,ISSN : 2248-9622 5 (2015) 59–67. [17] A. Jarašu¯nienė, RESEARCH INTO INTELLIGENT TRANSPORT SYSTEMS (ITS) TECHNOLOGIES AND EFFICIENCY, TRANSPORT 22 (2007) 61–67. URL: https://doi.org/10. 3846/16484142.2007.9638100. doi:10.3846/16484142.2007.9638100. [18] M. Chopra, S. K. Singh, K. Aggarwal, A. Gupta, Predicting catastrophic events using machine learning models for natural language processing, in: Data Mining Approaches for Big Data and Sentiment Analysis in Social Media, IGI Global, 2022, pp. 223–243. URL: https://doi.org/10.4018/978-1-7998-8413-2.ch010. doi:10.4018/978-1-7998-8413-2. ch010. [19] A. Gupta, A. Bansal, K. Mamgain, A. Gupta, An exploratory analysis on the unfold of fake news during covid-19 pandemic, in: A. K. Somani, A. Mundra, R. Doss, S. Bhattacharya (Eds.), Smart Systems: Innovations in Computing, Springer Singapore, Singapore, 2022, pp. 259–272. [20] E. Costa, J. Seixas, Contribution of electric cars to the mitigation of co2 emissions in the city of sao paulo, 2014 IEEE Vehicle Power and Propulsion Conference (VPPC) (2014) 1–5. [21] G. Grob, Future transportation with smart grids & sustainable energy, in: 2009 6th International Multi-Conference on Systems, Signals and Devices, volume 13, 2009, pp. 1 – 5. doi:10.1109/SSD.2009.4956791. [22] S. Mehar, S. Zeadally, G. Remy, S. M. Senouci, Sustainable transportation management system for a fleet of electric vehicles, IEEE Transactions on Intelligent Transportation Systems 16 (2015) 1401–1414. URL: https://doi.org/10.1109/tits.2014.2367099. doi:10.1109/ tits.2014.2367099. [23] S. Kumar, Artificial intelligence and machine learning for smart and secure healthcare system, Insights2Techinfo (2021) 1–1. [24] Mamta, Quick medical data access using edge computing, Insights2Techinfo (2021) 1–1. [25] C. L. Stergiou, K. E. Psannis, B. B. Gupta, Iot-based big data secure management in the fog over a 6g wireless network, IEEE Internet of Things Journal 8 (2020) 5164–5171. [26] C. Wang, J. Shen, P. Vijayakumar, B. B. Gupta, Attribute-based secure data aggregation for isolated iot-enabled maritime transportation systems, IEEE Transactions on Intelligent Transportation Systems (2021). [27] J. Zhang, Z. Wang, D. Wang, X. Zhang, B. Gupta, X. Liu, J. Ma, A secure decentralized spatial crowdsourcing scheme for 6g-enabled network in box, IEEE Transactions on Industrial Informatics (2021).