The Impact of Intelligent Parking Systems on Urban Mobility and the Role of Innovations in the Spectrum of Artificial Intelligence in the Electric Vehicle Industry

In this paper, we investigate the impact of Smart Parking Systems (SPS) on urban mobility and the incorporation of technological innovations within the electric vehicle (EV) industry, focusing on Petrosani, Romania. As urban areas grapple with the challenges of rapid development, such as traffic congestion and inefficient use of parking spaces, SPS emerge as a crucial solution. This research presents a comprehensive analysis of Petrosani's current traffic and parking conditions, leveraging public opinion surveys and traffic flow studies to propose an efficient integration of smart parking systems. The study reveals significant public support for SPS, highlighting a community eager to embrace solutions that enhance urban mobility, reduce environmental pollution, and improve the quality of urban life. Our findings suggest that adopting SPS in Petrosani could lead to more effective traffic management, better utilization of parking resources, and a shift towards sustainable urban development. The paper underscores the need for strategic planning and community involvement in transitioning towards smarter, more sustainable urban ecosystems, setting a precedent for similar initiatives in other cities. This work contributes to the discourse on sustainable urban planning, emphasizing the practical implications and benefits of intelligent parking solutions in enhancing urban mobility and environmental sustainability.

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Publication Details

Journal
Proceedings of the ENTRENOVA - Enterprise Research Innovation Conference
Published
2024-09-30
DOI
https://doi.org/10.54820/entrenova-2024-0041
Citations
4
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
3.09
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article

The Impact of Intelligent Parking Systems on Urban Mobility and the Role of Innovations in the Spectrum of Artificial Intelligence in the Electric Vehicle Industry

Cosmin Rus, Monica Leba, Marius Rîsteiu, Remus Sibisanu
4 citations
Proceedings of the ENTRENOVA - Enterprise Research Innovation Conference
Traffic Prediction and Management Techniques
3.09
article

The Impact of Intelligent Parking Systems on Urban Mobility and the Role of Innovations in the Spectrum of Artificial Intelligence in the Electric Vehicle Industry

Cosmin Rus, Monica Leba, Marius Rîsteiu, Remus Sibisanu
article en
4 citations

Abstract

In this paper, we investigate the impact of Smart Parking Systems (SPS) on urban mobility and the incorporation of technological innovations within the electric vehicle (EV) industry, focusing on Petrosani, Romania. As urban areas grapple with the challenges of rapid development, such as traffic congestion and inefficient use of parking spaces, SPS emerge as a crucial solution. This research presents a comprehensive analysis of Petrosani's current traffic and parking conditions, leveraging public opinion surveys and traffic flow studies to propose an efficient integration of smart parking systems. The study reveals significant public support for SPS, highlighting a community eager to embrace solutions that enhance urban mobility, reduce environmental pollution, and improve the quality of urban life. Our findings suggest that adopting SPS in Petrosani could lead to more effective traffic management, better utilization of parking resources, and a shift towards sustainable urban development. The paper underscores the need for strategic planning and community involvement in transitioning towards smarter, more sustainable urban ecosystems, setting a precedent for similar initiatives in other cities. This work contributes to the discourse on sustainable urban planning, emphasizing the practical implications and benefits of intelligent parking solutions in enhancing urban mobility and environmental sustainability.

Proceedings of the ENTRENOVA - Enterprise Research Innovation ConferenceVol. 10(1)
Universitatea Din Petrosani (RO)
Openalex Percentile: Top 6%
Traffic Prediction and Management Techniques
3.09
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