Design of Audio-Based Accident and Crime Detection and Its Optimization
The development of transportation technology is increasing every day; it impacts the number of transportation and their users. The increase positively impacts the economy's growth but also has a negative impact, such as accidents and crime on the highway. In 2018, the number of accidents in Ind...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Politeknik Negeri Padang
2023-03-01
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| Series: | JOIV: International Journal on Informatics Visualization |
| Subjects: | |
| Online Access: | https://joiv.org/index.php/joiv/article/view/1643 |
| _version_ | 1811159807026003968 |
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| author | Afis Asryullah Pratama Sritrusta Sukaridhoto Mauridhi Hery Purnomo Vita Lystianingrum Rizqi Putri Nourma Budiarti |
| author_facet | Afis Asryullah Pratama Sritrusta Sukaridhoto Mauridhi Hery Purnomo Vita Lystianingrum Rizqi Putri Nourma Budiarti |
| author_sort | Afis Asryullah Pratama |
| collection | DOAJ |
| description | The development of transportation technology is increasing every day; it impacts the number of transportation and their users. The increase positively impacts the economy's growth but also has a negative impact, such as accidents and crime on the highway. In 2018, the number of accidents in Indonesia reached 109,215 cases, with a death rate of 29,472 people, which was mostly caused by the late treatment of the casualties. On the other hand, in the same year, there were 8,423 mugs, and 90,757 snitches cases in Indonesia, with only 23.99% of cases reported. This low reporting rate is mostly caused by the lack of awareness and knowledge about where to report. Therefore, a quick response surveillance system is needed. In this study, an audio-based accident and crime detection system was built using a neural network. To improve the system's robustness, we enhance our dataset by mixing it with certain noises which likely to occur on the road. The system was tested with several parameters of segment duration, bandpass filter cut-off frequency, feature extraction, architecture, and threshold values to obtain optimal accuracy and performance. Based on the test, the best accuracy was obtained by convolutional neural network architecture using 200ms segment duration, 0.5 overlap ratio, 100Hz and 12000Hz as bandpass cut-off frequency, and a threshold value of 0.9. By using mentioned parameters, our system gives 93.337% accuracy. In the future, we hope to implement this system in a real environment. |
| first_indexed | 2024-04-10T05:48:27Z |
| format | Article |
| id | doaj.art-400af5afc0914e6d9c78430cc744aa39 |
| institution | Directory Open Access Journal |
| issn | 2549-9610 2549-9904 |
| language | English |
| last_indexed | 2024-04-10T05:48:27Z |
| publishDate | 2023-03-01 |
| publisher | Politeknik Negeri Padang |
| record_format | Article |
| series | JOIV: International Journal on Informatics Visualization |
| spelling | doaj.art-400af5afc0914e6d9c78430cc744aa392023-03-05T10:27:22ZengPoliteknik Negeri PadangJOIV: International Journal on Informatics Visualization2549-96102549-99042023-03-017121422010.30630/joiv.7.1.1643468Design of Audio-Based Accident and Crime Detection and Its OptimizationAfis Asryullah Pratama0Sritrusta Sukaridhoto1Mauridhi Hery Purnomo2Vita Lystianingrum3Rizqi Putri Nourma Budiarti4Politeknik Elektronika Negeri Surabaya, Surabaya, IndonesiaPoliteknik Elektronika Negeri Surabaya, Surabaya, IndonesiaInstitut Teknologi Sepuluh Nopember, Surabaya, IndonesiaInstitut Teknologi Sepuluh Nopember, Surabaya, IndonesiaUniversitas Nahdlatul Ulama Surabaya, Surabaya, IndonesiaThe development of transportation technology is increasing every day; it impacts the number of transportation and their users. The increase positively impacts the economy's growth but also has a negative impact, such as accidents and crime on the highway. In 2018, the number of accidents in Indonesia reached 109,215 cases, with a death rate of 29,472 people, which was mostly caused by the late treatment of the casualties. On the other hand, in the same year, there were 8,423 mugs, and 90,757 snitches cases in Indonesia, with only 23.99% of cases reported. This low reporting rate is mostly caused by the lack of awareness and knowledge about where to report. Therefore, a quick response surveillance system is needed. In this study, an audio-based accident and crime detection system was built using a neural network. To improve the system's robustness, we enhance our dataset by mixing it with certain noises which likely to occur on the road. The system was tested with several parameters of segment duration, bandpass filter cut-off frequency, feature extraction, architecture, and threshold values to obtain optimal accuracy and performance. Based on the test, the best accuracy was obtained by convolutional neural network architecture using 200ms segment duration, 0.5 overlap ratio, 100Hz and 12000Hz as bandpass cut-off frequency, and a threshold value of 0.9. By using mentioned parameters, our system gives 93.337% accuracy. In the future, we hope to implement this system in a real environment.https://joiv.org/index.php/joiv/article/view/1643audio recognitiondataset manipulationoptimizationneural networkssurveillance system. |
| spellingShingle | Afis Asryullah Pratama Sritrusta Sukaridhoto Mauridhi Hery Purnomo Vita Lystianingrum Rizqi Putri Nourma Budiarti Design of Audio-Based Accident and Crime Detection and Its Optimization JOIV: International Journal on Informatics Visualization audio recognition dataset manipulation optimization neural networks surveillance system. |
| title | Design of Audio-Based Accident and Crime Detection and Its Optimization |
| title_full | Design of Audio-Based Accident and Crime Detection and Its Optimization |
| title_fullStr | Design of Audio-Based Accident and Crime Detection and Its Optimization |
| title_full_unstemmed | Design of Audio-Based Accident and Crime Detection and Its Optimization |
| title_short | Design of Audio-Based Accident and Crime Detection and Its Optimization |
| title_sort | design of audio based accident and crime detection and its optimization |
| topic | audio recognition dataset manipulation optimization neural networks surveillance system. |
| url | https://joiv.org/index.php/joiv/article/view/1643 |
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