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Trends in Transport Engineering and Applications Review Article

A Comprehensive Study of Sensor and Camera Fusion for Real-Time Parking Space Detection

  1. Ravikant Nanwatkar Department of Engineering Science, STES’s NBN Sinhgad Technical Institutes Campus, Ambegaon, SPPU, Pune
  2. Aayush Talware Department of Engineering Science, STES’s NBN Sinhgad Technical Institutes Campus, Ambegaon, SPPU, Pune
  3. Sujay Sonar Department of Engineering Science, STES’s NBN Sinhgad Technical Institutes Campus, Ambegaon, SPPU, Pune
  4. Atharva Joshi Department of Engineering Science, STES’s NBN Sinhgad Technical Institutes Campus, Ambegaon, SPPU, Pune
  5. Ayush Ahhiroa Department of Engineering Science, STES’s NBN Sinhgad Technical Institutes Campus, Ambegaon, SPPU, Pune

Abstract

Due to the rapid growth in urban vehicle density, there have been major problems in the effective management of parking space, which has caused congestion, more traveling time, wastage of fuel, and environmental pollution. Conventional parking systems are very ineffective, as they are based on manual surveillance and cannot provide drivers with much real-time information. To overcome these challenges, the present paper explores the design, development, and operation of a smart parking system, using current technologies like Internet of Things (IoT), sensor networks, cloud computing, and mobile applications. The system is a combination of intelligent sensors to capture the real-time occupancy of parking spaces that is processed and relayed to a central server. The system uses data analytics and mobile connectivity, providing information on the availability of the closest vacant spot and the best route to take in real-time to the driver, which saves time searching and reduces congestion in traffic. Also, the suggested system will have automated payment systems, user authentication, and reservations as an addition to the overall parking experience. A controlled test model was created and tested using a prototype model to measure the parameters of the test, including accuracy, latency, convenience to the user, and scalability. Findings reveal a high level of efficiency in parking and shortened time of vehicle idling as opposed to the traditional systems. The observations identify the potential of smart parking systems to add to the sustainable urban motion and intelligent transportation infrastructures. The future work will include the large-scale implementation, interdependence with smart city platforms, as well as the usage of machine learning for predictive parking analytics

Keywords

References (34)

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