IoT-Based Vision Techniques in Autonomous Driving
As more people drive vehicles, there is a corresponding increase in the number of deaths and injuries that happen due to road traffic accidents. Thus, various solutions have been proposed to reduce the impact of accidents. One of the most popular solutions is autonomous driving, which involves a ser...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Ediciones Universidad de Salamanca
2023-01-01
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| Series: | Advances in Distributed Computing and Artificial Intelligence Journal |
| Subjects: | |
| Online Access: | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/28821 |
| _version_ | 1797943620624449536 |
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| author | Mohammed Qader Kheder Mohammed Aree Ali |
| author_facet | Mohammed Qader Kheder Mohammed Aree Ali |
| author_sort | Mohammed Qader Kheder |
| collection | DOAJ |
| description | As more people drive vehicles, there is a corresponding increase in the number of deaths and injuries that happen due to road traffic accidents. Thus, various solutions have been proposed to reduce the impact of accidents. One of the most popular solutions is autonomous driving, which involves a series of embedded systems. These embedded systems assist drivers by providing crucial information on the traffic environment or by acting to protect the vehicle occupants in particular situations or to aid driving. Autonomous driving has the capacity to improve transportation services dramatically. Given the successful use of visual technologies and the implementation of driver assistance systems in recent decades, vehicles are prepared to eliminate accidents, congestion, collisions, and pollution. In addition, the IoT is a state-of-the-art invention that will usher in the new age of the Internet by allowing different physical objects to connect without the need for human interaction. The accuracy with which the vehicle's environment is detected from static images or videos, as well as the IoT connections and data management, is critical to the success of autonomous driving. The main aim of this review article is to encapsulate the latest advances in vision strategies and IoT technologies for autonomous driving by analysing numerous publications from well-known databases. |
| first_indexed | 2024-04-10T20:27:04Z |
| format | Article |
| id | doaj.art-0ddc105047eb452ab221e155c2ef2223 |
| institution | Directory Open Access Journal |
| issn | 2255-2863 |
| language | English |
| last_indexed | 2024-04-10T20:27:04Z |
| publishDate | 2023-01-01 |
| publisher | Ediciones Universidad de Salamanca |
| record_format | Article |
| series | Advances in Distributed Computing and Artificial Intelligence Journal |
| spelling | doaj.art-0ddc105047eb452ab221e155c2ef22232023-01-25T08:48:07ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632023-01-0111336739434282IoT-Based Vision Techniques in Autonomous DrivingMohammed Qader Kheder0Mohammed Aree Ali1University of SulaimaniUniversity of SulaimaniAs more people drive vehicles, there is a corresponding increase in the number of deaths and injuries that happen due to road traffic accidents. Thus, various solutions have been proposed to reduce the impact of accidents. One of the most popular solutions is autonomous driving, which involves a series of embedded systems. These embedded systems assist drivers by providing crucial information on the traffic environment or by acting to protect the vehicle occupants in particular situations or to aid driving. Autonomous driving has the capacity to improve transportation services dramatically. Given the successful use of visual technologies and the implementation of driver assistance systems in recent decades, vehicles are prepared to eliminate accidents, congestion, collisions, and pollution. In addition, the IoT is a state-of-the-art invention that will usher in the new age of the Internet by allowing different physical objects to connect without the need for human interaction. The accuracy with which the vehicle's environment is detected from static images or videos, as well as the IoT connections and data management, is critical to the success of autonomous driving. The main aim of this review article is to encapsulate the latest advances in vision strategies and IoT technologies for autonomous driving by analysing numerous publications from well-known databases.https://revistas.usal.es/cinco/index.php/2255-2863/article/view/28821avsavs’ sensorscomputer visioninternet of thing (iot)internet of vehicles (iov)autonomous drivingtrafficaccident prevention |
| spellingShingle | Mohammed Qader Kheder Mohammed Aree Ali IoT-Based Vision Techniques in Autonomous Driving Advances in Distributed Computing and Artificial Intelligence Journal avs avs’ sensors computer vision internet of thing (iot) internet of vehicles (iov) autonomous driving traffic accident prevention |
| title | IoT-Based Vision Techniques in Autonomous Driving |
| title_full | IoT-Based Vision Techniques in Autonomous Driving |
| title_fullStr | IoT-Based Vision Techniques in Autonomous Driving |
| title_full_unstemmed | IoT-Based Vision Techniques in Autonomous Driving |
| title_short | IoT-Based Vision Techniques in Autonomous Driving |
| title_sort | iot based vision techniques in autonomous driving |
| topic | avs avs’ sensors computer vision internet of thing (iot) internet of vehicles (iov) autonomous driving traffic accident prevention |
| url | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/28821 |
| work_keys_str_mv | AT mohammedqaderkheder iotbasedvisiontechniquesinautonomousdriving AT mohammedareeali iotbasedvisiontechniquesinautonomousdriving |