Abstract
This chapter presents the fruit of our research by merging smart transportation and smart health to provide IoT transportation solutions based on green smart city intelligence and safety to fight against the COVID-19 pandemic. For this, we have realized a model that allows transporting citizens via a means of transportation based on electric mobility to reduce energy consumption, reduce CO\(_2\) emission and cost by searching the optimal path that this vehicle will be used. And to transport people, we need a system that allows us to check the health situation of citizens to avoid and prevent the spread of the COVID-19 pandemic. In order to find solutions to this work, we have proposed approaches to calculate the most optimal path that meets our needs, as well as to propose scenarios that allow checking the situation of the citizens. And to complete this work with minimum consumption of memory and time, we made a comparative study on the nodes used for the different IoT network topologies to choose the best one for our platform. Concerning the communication, we chose to use the CoAP protocol to ensure the communication between the nodes, and we used the AES-SHA256 encryption algorithm to compare it with RSA-SHA256 to ensure the elements of security and protection the data from any intrusion.
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Oussous, S.A., Hamza, F.Z., Beloualid, S., Allali, A.E., Bajit, A., Tamtaoui, A. (2022). Green Smart City Intelligent and Cyber-Security-Based IoT Transportation Solutions for Combating the Pandemic COVID-19. In: Lahby, M., Al-Fuqaha, A., Maleh, Y. (eds) Computational Intelligence Techniques for Green Smart Cities. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-96429-0_6
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