Open-air Off-street Vehicle Parking Management System Using Deep Neural Networks: A Case Study

Kumar, K Naveen and Pawar, Digvijay S and Mohan, C. K. (2022) Open-air Off-street Vehicle Parking Management System Using Deep Neural Networks: A Case Study. In: 14th International Conference on COMmunication Systems and NETworkS, COMSNETS 2022, 4 January 2022 through 8 January 2022, Bangalore.

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Smart parking solution aims to output real-time parking occupancy information. It helps to reduce parking bay search time, traffic, fuel consumption, and thereby vehicular emissions with increased road safety. A computer vision-based solution using camera video data is most reliable and rational since it allows monitoring the entire open-air parking area at once. A real-time parking solution (cloud-based, server processing, or onboard processing) helps bring the occupancy information to the end-user. It comes with many challenges such as viewing angles, lighting conditions, model optimization, reducing inference time, and many more real-world challenges. Hence, this paper presents a case study on real-time open-air off-street intelligent parking management using a deep neural network. Also, most of the earlier research works focus on day-time data and do not discuss the night data. So, in this work, we perform experiments on realtime 24-hour data from an input camera video source mounted to monitor parking at IIT Hyderabad (IITH) parking lot. Our experiments demonstrate the real-world challenges and can help improve parking performance, deployment at IITH, and relevant parking systems in general. © 2022 IEEE.

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IITH Creators:
IITH CreatorsORCiD
Pawar, Digvijay SUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Additional Information: This work has been conducted as part of the SATREPS project entitled “Smart Cities for Emerging Countries by Multimodal Transport System based on Sensing, Network and Big Data Analysis of Regional Transportation” (JPMJSA1606) funded by JST and JICA.
Uncontrolled Keywords: convolution neural network; off-street parking; Open-air parking; real-time deployment; vehicle parking
Subjects: Computer science
Divisions: Department of Computer Science & Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 25 Jul 2022 04:35
Last Modified: 25 Jul 2022 04:35
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