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


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.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL