Energy Aware Parking Lot Detection Using YOLO on Jetson TX2

Anggawijaya, Yohan Marvel (2019) Energy Aware Parking Lot Detection Using YOLO on Jetson TX2. Other thesis, UNIKA SOEGIJAPRANATA SEMARANG.

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Abstract

Finding a parking space is a tedious and time-consuming task in a metropolitan city. Due to this problem, many researchers proposed an automatic parking lot occupancy detection system. using a camera with a deep learning method to provide useful in/ormation in the smart city system. Since object detection for the parking lot is performed in real-time by utilizing CPU and GPUs while parking defection is working 24 hours a day and 365 days a year, therefore power saving is important [0 reduce the cost. However, the energy-aware is not considered ill most related works. In this paper, we proposed an energy-saving algorithm for parking lot availability defection using YOLO running 012 the TX2 machine. We experiment using small parking lot prototype and remote control cars. In the experiment. we compare our algorithm with the direct application of original YOLO for parking lot detection. The results show that it reduces powerby 97 percent when there is no moving object in the parking lot area and 71 percent when there are moving objects in the parking lot area.

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works > 004 Data processing & computer science
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: mr AM. Pudja Adjie Sudoso
Date Deposited: 30 Mar 2020 03:07
Last Modified: 25 Sep 2020 04:48
URI: http://repository.unika.ac.id/id/eprint/21094

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