Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration
Nighttime driving is difficult owing to low visibility and lights. Nighttime accidents are more dangerous due to reduced obstacle detection, poor vision, and trouble evaluating distances. Knowing the causes and dynamics of nighttime accidents is essential for improving road safety and preventing col...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Penerbit Universiti Malaysia Pahang
2025
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| Online Access: | https://umpir.ump.edu.my/id/eprint/45391/ |
| _version_ | 1848827405138919424 |
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| author | Beg, Mohammad Sojon Muhammad Yusri, Ismail Najmi Haziq, Badrulhisam Ibnu Siswanto, . Gunadi, . |
| author_facet | Beg, Mohammad Sojon Muhammad Yusri, Ismail Najmi Haziq, Badrulhisam Ibnu Siswanto, . Gunadi, . |
| author_sort | Beg, Mohammad Sojon |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Nighttime driving is difficult owing to low visibility and lights. Nighttime accidents are more dangerous due to reduced obstacle detection, poor vision, and trouble evaluating distances. Knowing the causes and dynamics of nighttime accidents is essential for improving road safety and preventing collisions when natural light is limited. This study proposes using an infrared thermal sensor to assist drivers in mitigating the issue of inadequate light at night, with the ultimate goal of preventing crashes under such circumstances. The investigation compared the infrared thermal camera sensor with the normal camera visual to evaluate how well it worked at night. The testing has been done on the road in Pekan, Pahang. Yolov8 deep learning has been integrated with both cameras to detect items like cars, motorcycles, and traffic lights. The test findings demonstrated how temperature variations can be utilized to precisely detect items on different types of roadways. The study showed that infrared thermal sensors are impressive at detecting traffic lamps, motorcycles, and vehicles. The infrared camera's actual detection on confusion matrices was 0.98 for traffic lamps and 0.87 for motorcycles and vehicles. This shows how well the infrared thermal camera works in dark conditions, with a faster frame rate of 64.94 fps than regular cameras at 55.25 fps. The results of this study demonstrate that using infrared technology can enhance object detection capabilities and, hence, enhance nighttime road safety. |
| first_indexed | 2025-11-15T04:00:11Z |
| format | Article |
| id | ump-45391 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T04:00:11Z |
| publishDate | 2025 |
| publisher | Penerbit Universiti Malaysia Pahang |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-453912025-08-14T07:31:33Z https://umpir.ump.edu.my/id/eprint/45391/ Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration Beg, Mohammad Sojon Muhammad Yusri, Ismail Najmi Haziq, Badrulhisam Ibnu Siswanto, . Gunadi, . TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering Nighttime driving is difficult owing to low visibility and lights. Nighttime accidents are more dangerous due to reduced obstacle detection, poor vision, and trouble evaluating distances. Knowing the causes and dynamics of nighttime accidents is essential for improving road safety and preventing collisions when natural light is limited. This study proposes using an infrared thermal sensor to assist drivers in mitigating the issue of inadequate light at night, with the ultimate goal of preventing crashes under such circumstances. The investigation compared the infrared thermal camera sensor with the normal camera visual to evaluate how well it worked at night. The testing has been done on the road in Pekan, Pahang. Yolov8 deep learning has been integrated with both cameras to detect items like cars, motorcycles, and traffic lights. The test findings demonstrated how temperature variations can be utilized to precisely detect items on different types of roadways. The study showed that infrared thermal sensors are impressive at detecting traffic lamps, motorcycles, and vehicles. The infrared camera's actual detection on confusion matrices was 0.98 for traffic lamps and 0.87 for motorcycles and vehicles. This shows how well the infrared thermal camera works in dark conditions, with a faster frame rate of 64.94 fps than regular cameras at 55.25 fps. The results of this study demonstrate that using infrared technology can enhance object detection capabilities and, hence, enhance nighttime road safety. Penerbit Universiti Malaysia Pahang 2025-03-19 Article PeerReviewed pdf en cc_by_nc_4 https://umpir.ump.edu.my/id/eprint/45391/1/Improving%20Vehicle%20Assistance%20Systems_Evaluation%20of%20Augmented%20Capabilities.pdf Beg, Mohammad Sojon and Muhammad Yusri, Ismail and Najmi Haziq, Badrulhisam and Ibnu Siswanto, . and Gunadi, . (2025) Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration. International Journal of Automotive and Mechanical Engineering (IJAME), 22 (1). pp. 12236-12252. ISSN 2180-1606. (Published) https://doi.org/10.15282/ijame.22.1.2025.20.0937 https://doi.org/10.15282/ijame.22.1.2025.20.0937 https://doi.org/10.15282/ijame.22.1.2025.20.0937 |
| spellingShingle | TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering Beg, Mohammad Sojon Muhammad Yusri, Ismail Najmi Haziq, Badrulhisam Ibnu Siswanto, . Gunadi, . Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration |
| title | Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration |
| title_full | Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration |
| title_fullStr | Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration |
| title_full_unstemmed | Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration |
| title_short | Improving vehicle assistance systems: Evaluation of augmented capabilities through infrared thermal camera integration |
| title_sort | improving vehicle assistance systems: evaluation of augmented capabilities through infrared thermal camera integration |
| topic | TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering |
| url | https://umpir.ump.edu.my/id/eprint/45391/ https://umpir.ump.edu.my/id/eprint/45391/ https://umpir.ump.edu.my/id/eprint/45391/ |