###### Abstract
The display of conceptual, unorganized, and high-dimensional data, such as corporate data, social media information, and textual information, is the subject of data visualization. Much effort has gone into establishing cost-effective and reliable traffic monitoring systems on a global scale. To increase traffic choices, one common method is to use computer vision to capture and evaluate relevant photos from existing urban video surveillance. Camera-based solutions such as this have modest infrastructural requirements and give vast aerial coverage, enabling traffic monitoring at multiple locations. The computerized system covers more ground than traditional traffic monitoring that relies on fixed-point sensors. Image processing methods are broadly utilized in a diversity of areas, such as aviation, healthcare, traffic control, and environmental object assessment [4]. The study of analytical reasoning helped by communicative visual interfaces is known as visual analytics, and it concentrates on producing human-computer practices and approaches for data processing, knowledge development, and problem resolution. It is an applied investigation subject which tries to provide practical solutions for a variety of application areas, including transportation. The best results are obtained when visual analytics investigators, who often lack subject experience, collaborate closely with domain experts. Unfortunately, although visual analytics investigators have performed extensively with transportation-related information and established a range of methodologies and instruments, which could be beneficial to transportation domain practitioners and researchers, such work has been restricted in the transportation field. Inadequate communication has two negative implications. Visual analytics investigators have a restricted awareness of the transportation domain's challenges, needs, and constraints, which shall limit the utility and usability of the approaches they develop. The transportation community, on the other hand, is mostly unaware of the benefits that visual analytics may provide [5]. In terms of price, simplicity of installation and management, and better measurement capabilities, wireless magnetic sensor networks are an appropriate option for induction circuits for traffic control on motorways and at crossings. Wireless detection does have the ability to change the way traffic information is acquired by offering great geographic volume and precision observations. Inductive loop sensors, micro-loop probes, pneumatic road tubing, piezoelectric wires, and other weigh-in-motion monitors are used in many traditional traffic monitoring systems. These were selected due to their higher traffic detecting efficiency. To get the most out of these ITS solutions, large-scale implementation of traffic regulations on all major motorways and minor streets is required. As a result, real-time traffic data are necessary at these locations. Even though computer vision and visual analytics is a well-developed field of information technology, its identification, categorization, and tracking capabilities are not frequently used in daily life. As a result, we currently lack an automatic traffic control system for city roadways that can respond to changes in urban traffic in an automated manner [6].