Abstract
Environmentally friendly and intelligent transportation options have been developed to tackle pollution and fuel shortages during the past several years. Numerous standards organizations and transportation authorities have provided a range of alternative energy sources intending to create a more environmentally friendly and sustainable atmosphere. However, some obstacles remain to clear before the goal may be fulfilled in green transportation. The research examines and identifies transportation pollution and greenhouse gas emissions. An electric vehicle-centric approach to green mobility is taken, emphasizing electric vehicle architecture and current solutions initiatives, and essential for effectively done. Regarding an Electric Vehicle Charging Station (EVCS), location is key; according to the study, EVSC location selection may be improved using an Internet of Things (IoT) with a cloud computing (IoT-CC) approach. Carbon-producing vehicles such as trains and buses are being phased out globally for more eco-friendly transportation. Electrified vehicles are a significant step toward a more environmentally friendly mode of transportation. However, electric vehicles are becoming more common, and the infrastructure for charging must be expanded and seamless. Solar panels may be used to electric power vehicles and generate their energy by certain entities. There are plans to develop EVSC-IoT service architecture to minimize carbon dioxide emissions and fuel consumption in a smart transportation system. It gathers data from telematics, digital systems, and roadside camera to assist fuel consumption. Electric vehicle drivers may use electronic wallets to pay for their charging costs. The suggested EVSC-IoT model enhances the charging demand, charging time, time distribution, and traveling velocity compared to other existing methods.
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Aldeen, Y.A.A.S., Jaber, M.M., Ali, M.H. et al. Electric charging station management using IoT and cloud computing framework for sustainable green transportation. Multimed Tools Appl 83, 28705–28728 (2024). https://doi.org/10.1007/s11042-023-16630-0
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DOI: https://doi.org/10.1007/s11042-023-16630-0