The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).
If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.
Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.
BibTex Citation Data :
@article{JOIV1643, author = {Afis Pratama and Sritrusta Sukaridhoto and Mauridhi Purnomo and Vita Lystianingrum and Rizqi Budiarti}, title = {Design of Audio-Based Accident and Crime Detection and Its Optimization}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {7}, number = {1}, year = {2023}, keywords = {Audio recognition; dataset manipulation; optimization; neural networks; surveillance system.}, abstract = {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.}, issn = {2549-9904}, pages = {214--220}, doi = {10.30630/joiv.7.1.1643}, url = {http://joiv.org/index.php/joiv/article/view/1643} }
Refworks Citation Data :
@article{{JOIV}{1643}, author = {Pratama, A., Sukaridhoto, S., Purnomo, M., Lystianingrum, V., Budiarti, R.}, title = {Design of Audio-Based Accident and Crime Detection and Its Optimization}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {7}, number = {1}, year = {2023}, doi = {10.30630/joiv.7.1.1643}, url = {} }Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
__________________________________________________________________________
JOIV : International Journal on Informatics Visualization
ISSN 2549-9610 (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
W : http://joiv.org
E : joiv@pnp.ac.id, hidra@pnp.ac.id, rahmat@pnp.ac.id
View JOIV Stats
is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.