Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT
In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manne...
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| Ngôn ngữ: | English |
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IJECE
2022
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| Truy cập trực tuyến: | https://ijece.iaescore.com/index.php/IJECE/article/view/24764 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5948 http://doi.org/10.11591/ijece.v12i1.pp785-792 |
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oai:localhost:PNK-59482022-08-17T05:54:50Z Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT Thi Thu, Nguyen Phuc Thinh, Doan Anh-Ngoc Le Acceleration CarSafe In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manner. It enables automatic actions to help the driver safer. Also, from these data, our software can detect the crash situation. The software will then automatically send messages with the user's location to their emergency departments for timely assistance. The application will also issue the same alert if it detects a driver of a vehicle driving too long. The algorithm's quality is assessed through an average accuracy of 96.5%, which is better than the previous work (i.e., 93%). 2022-07-13T02:00:03Z 2022-07-13T02:00:03Z 2022 Bài trích https://ijece.iaescore.com/index.php/IJECE/article/view/24764 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5948 http://doi.org/10.11591/ijece.v12i1.pp785-792 en IJECE |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
Acceleration CarSafe |
| spellingShingle |
Acceleration CarSafe Thi Thu, Nguyen Phuc Thinh, Doan Anh-Ngoc Le Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT |
| description |
In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manner. It enables automatic actions to help the driver safer. Also, from these data, our software can detect the crash situation. The software will then automatically send messages with the user's location to their emergency departments for timely assistance. The application will also issue the same alert if it detects a driver of a vehicle driving too long. The algorithm's quality is assessed through an average accuracy of 96.5%, which is better than the previous work (i.e., 93%). |
| format |
Bài trích |
| author |
Thi Thu, Nguyen Phuc Thinh, Doan Anh-Ngoc Le |
| author_facet |
Thi Thu, Nguyen Phuc Thinh, Doan Anh-Ngoc Le |
| author_sort |
Thi Thu, Nguyen |
| title |
Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT |
| title_short |
Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT |
| title_full |
Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT |
| title_fullStr |
Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT |
| title_full_unstemmed |
Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT |
| title_sort |
develop algorithms to determine the status of car drivers using built-in accelerometer and gbdt |
| publisher |
IJECE |
| publishDate |
2022 |
| url |
https://ijece.iaescore.com/index.php/IJECE/article/view/24764 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5948 http://doi.org/10.11591/ijece.v12i1.pp785-792 |
| _version_ |
1751856290001321984 |
| score |
8.891145 |