Big Data Analytics for Processing Real-time Unstructured Data from CCTV in Traffic Management

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Faqih Hamami, Iqbal Ahmad Dahlan, Setya Widyawan Prakosa, Khamal Fauzan Somantri

2020 2020 International Conference on Data Science and Its Applications, ICoDSA 2020 Conference paper Cited by 10 Quartile

Abstract

Todays many devices generate data everywhere and anytime. Data grow massively and becomes complex thing that needs to be handled. Unstructured data is one type of big data that is difficult to process and consists of unstable attributes. In traffic management, CCTVs are installed to monitor the specific location in the highway. CCTV generates unstructured data in image and video format. These data are difficult to process due to the complexity of the data. This research proposes to implement big data analytics to process real-time unstructured data from CCTV into knowledge displayed in web dashboard. We implement the YOLO framework with YoloV4 Architecture and COCO dataset for traffic flow counting and detecting illegal parking which is categorized as abnormal situation. Unstructured data from CCTV then transformed into semi-structured format in JSON. Data also can be visualized in real time to facilitate local authority to understand the highway situation. Historical data are stored in the NoSQL database to deep more knowledge such as vehicle traffic pattern. The proposed system requires the ROI drawing line as trigger to count the passing vehicles. These experiments are conducted from open CCTV for traffic online in Bali Tower Public Streaming. The prototype result is able to detect the object with 10 fps. © 2020 IEEE.

Affiliations

Telkom University, School of Industrial and System Engineering, Bandung, Indonesia; Indonesia Defense University, Military Engineering Faculty, Bogor, Indonesia; National Taiwan University of Science Technology, Electronic and Computer Engineering, Taipei, Taiwan; Universitas Pendidikan Indonesia, Faculty of Mathematics and Science, Bandung, Indonesia

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