Publication: Social Distancing Monitoring By Detection Of Traffic Near Miss And Accidents In Penang
| dc.contributor.author | Lim, Lek Ming | |
| dc.date.accessioned | 2023-10-26T02:46:24Z | |
| dc.date.available | 2023-10-26T02:46:24Z | |
| dc.date.issued | 2022-12 | |
| dc.description.abstract | In terms of fatalities, Malaysia ranks third among ASEAN countries. Every year, there is an increase in the number of accidents and fatalities. The state of the road is one of the factors that contribute to Near Misses. A Near Miss is an almost-caused accident, which is an unplanned situation that could result in injury or accidents. The Majlis Bandar Pulau Pinang (MBPP) has installed 1841 closed-circuit television (CCTV) cameras around Penang to monitor traffic and track Near Miss incidents. When installing CCTVs, the utilization of video allows resources to be used and optimized in situations when maintaining video memories is difficult and costly. Highways, industrial regions, and city roads are the most typical places where accidents occur. Accidents occurred at a rate of 200 per year on average in Penang from 2015 to 2017. Near Misses are what create accidents. One of the most essential factors in vehicle detection is the “Near Miss.” In this study, You Only Look Once version 3 (YOLOv3) and Faster Region-based Convolutional Neural Network (Faster RCNN) are used to solve transportation issues. Faster RCNN was only used in vehicle detection. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/17737 | |
| dc.subject | Social Distancing Monitoring | |
| dc.subject | Detection Of Traffic Near Miss And Accidents In Penang | |
| dc.title | Social Distancing Monitoring By Detection Of Traffic Near Miss And Accidents In Penang | |
| dc.type | Resource Types::text::thesis::master thesis | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |