Cloud based Single Shot Multi Box Detection (SSD) Architecture Models for Jakarta Traffic Jam Monitoring
Alfan Presekal1, Muflih Fathan2, Misbahul Fajri3, I Gde Dharma Nugraha4, Kalamullah Ramli5
1Alfan Presekal*, lecture on Computer Engineering, Department of Electrical Engineering, Universitas Indonesia.
2Muflih Fathan, Student of Computer Engineering, Universitas Indonesia.
3I Gde Dharma Nugraha, lecture in Department of Electrical Engineering, Universitas Indonesia.
4Kalamullah Ramli, Professor on Computer Engineering in Computer Engineering, Universitas Indonesia
5Misbahul Fajri, Dep. of Computer Engineering, Universitas Indonesia.
Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 3617-3622 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7896129219/2019©BEIESP | DOI: 10.35940/ijitee.B7896.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Traffic jam is still one of the main problems in Jakarta Indonesia. To encounter this problem, we proposed system to monitor the road and perform calculation on vehicles speed and road density. To achieve this, we used SSD to detect vehicle traffic on Jakarta’s road which obtained from public IP Camera. The main contribution of this work are utilization of public IP Camera and remote traffic analytics via cloud based artificial intelligence system. As a result, the program can perform monitoring on roads condition in real time. The accuracy of the system in average is 80% with highest accuracy achieved 92% to detect vehicle speed and road density.
Keywords: Object Detection, Vehicle Detection, Deep Learning, Single Shot Multibox Detection, Cloud Computing.
Scope of the Article: Cloud Computing.