| Author | Sai, Arepalli Rama Venkata Naga |
| Note | A thesis submitted in partial fulfillment of the requirements for the
degree of Master of Engineering in
Microelectronics and Embedded Systems |
| Publisher | Asian Institute of Technology |
| Abstract | The car parking occupancy detection is one of the most important systems that are needed at various parking lots. For this thesis, CNNs have been used because they achieve most promising results than compared to the other traditional parking detections. This thesis presents a robust technique for the car parking occupancy detection by going through the most of the parking issues such as parking displacements, non-unified car sizes and interobject occlusion. This thesis presents a real-time parking space detection based on the Convolutional Neural Networks (CNN). The aim of this thesis is to solve the issue of car parking for some extent which is done by taking videos from surveillance cameras and detecting the occupancy of the parking lot whether the parking space is Empty or Occupied. By using this technique, the main parking lot issue, that is availability of the parking spaces in the parking lot is solved, so that the drivers do not waste much time in searching for the parking space and do not leave in frustration of not able to find the exact Empty space. This thesis uses the YOLOv3 object detection algorithm which is implemented by deep neural network architecture. This is achieved by collecting the data from five parking lots at our institute and training them using YOLOv3 model. The detection is tested on both images and videos and the results indicate that this method is most efficient in detecting a car in parking lot |
| Year | 2019 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Microelectronics (ME) |
| Chairperson(s) | Mongkol Ekpanyapong ; |
| Examination Committee(s) | Dailey, Matthew N.;Manukid Parnichkun ; |
| Scholarship Donor(s) | AIT Fellowship; |
| Degree | Thesis (M. Eng.) -- Asian Institute of Technology, 2019 |