Automatic fare collection system for public transport with high level security

Dhamodhiran, Rathika Pacharpalayam; Saravanan, Kishore; Rangasamy, Pragatheesh Jagadeesan; Kannappan, Vimal Venkatachalam; Dhandapani, Subash

doi:10.1063/5.0194815

Cited by 1 publication

(1 citation statement)

References 2 publications

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“…Smart Fare Collection: AI-powered fare collection systems are enhancing the efficiency and security of public transport payment processes. Through technologies like computer vision and ML, public transport operators can automate fare validation, detect fare evasion, and personalize fare options for passengers, leading to improved revenue management and passenger satisfaction [19]. Smart cards, which is an AI-powered fare collection system can streamline payment processes by enabling passengers to use smart cards for contactless payments.…”

Section: Public Transportmentioning

confidence: 99%

A Review of the Advances in Artificial Intelligence in Transportation System Development

Mirindi

2024

JCCEE

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In modern times, the rapid expansion of urban populations has intensified the urgency to optimize transportation systems, which has become an alarming issue in the face of urbanization and traffic congestion. This paper reviews the latest applications of Artificial Intelligence (AI) in the transport sector. It explores various AI methodologies, including Artificial Neural Networks (ANN), Genetic Algorithms (GA), Simulated Annealing (SA), Ant Colony Optimizer (ACO), Bee Colony Optimization (BCO), disruptive urban mobility, Fuzzy Logic Models (FLM), automated incident detection systems, and drones, which improve dynamic traffic management and route optimization. The study reveals that integrating these AI techniques with real-time data analytics improves traffic flow, automated incident management, and overall transportation efficiency. The results demonstrate that AI-driven systems, such as drones equipped with advanced sensors and AI algorithms, are increasingly capable of autonomous navigation, real-time monitoring, and predictive traffic management. These advancements in technologies, such as electric Vertical Take-off and Landing (eVTOL) aircraft, Hyperloop Transportation Technologies (HTT), Mobility-as-a-Service (MaaS) and autonomous delivery robots, contribute to smarter urban mobility solutions. However, it is important to focus on refining AI models for better performance, addressing challenges such as computational complexity and privacy concerns, and continuing to innovate in AI to improve the economic efficiency and reliability of transportation systems. Furthermore, to promote sustainability development in this sector, ethical considerations such as the protection of user information and the integration of the concepts of informed consent and human autonomy with community engagement programs should also be considered.

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Section: Public Transportmentioning

confidence: 99%

A Review of the Advances in Artificial Intelligence in Transportation System Development

Mirindi

2024

JCCEE

View full text Add to dashboard Cite

show abstract

Automatic fare collection system for public transport with high level security

Cited by 1 publication

References 2 publications

A Review of the Advances in Artificial Intelligence in Transportation System Development

A Review of the Advances in Artificial Intelligence in Transportation System Development

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