Integrating Easy Ways of Identifying and Locating Objects in an Image/Video

Introducing Our Client

Our client was a well-known Sri Lankan construction contractor. They established their corporate headquarters in Colombo. As a leading name in the industry, they have aided in the construction and engineering of numerous projects throughout Southeast Asia and neighboring countries. The company gained valuable experience in a variety of construction-related fields, including civil engineering, building construction, interior design, and electrical/mechanical aid.

Challenges and Objectives of Our Client

Typically, the consignment tracking processes are carried out by the consignment tracking executives. They are authorized for frequently monitoring each consignment as it is transported from point A to point B. The managers will maintain constant contact with truck drivers, logistics companies, and transportation regulators in order to keep the system's real-time information relevant. Because the entire process is carried out manually, errors are unavoidable. Such errors can result in the inclusion of unnecessary data, which can have a detrimental effect on the entire logistics supply chain. Concerned about these inconveniences, our customer desired to effectively automate the consignment tracking procedure.

Several of our client's criteria included the following:

  • To keep track of the vehicles that enter and exit the premises
  • Automatic recognition of the vehicle's license plate and registration number
  • Immediate activation of red alerts for blacklisted vehicles
  • Entering traffic data and viewing it in an easy-to-use administrator dashboard
  • Labeling vehicles according to their model number, manufacturer, and so on.

How Did Allianze InfoSoft Contribute to Our Client's Success?

Following an analysis of the project's requirements, we designed a system that makes use of computer vision technologies. It was capable of monitoring vehicles entering and exiting the property. This method was developed with the use of machine learning algorithms that have been programmed to recognize and detect vehicles in the immediate neighborhood. Additionally, the solution was capable of counting these vehicles, categorizing them according to their make, model, and kind, and then logging them into an organized database.

We began by calculating the number of vehicles passing through the intersection in each direction. Our team developed a sophisticated segmentation algorithm that recognizes the pixel value associated with moving vehicles. The system maintains a track of the targeted item – the vehicle's trajectory. This is to determine the direction of the vehicle. Vehicles are primarily tallied depending on their path direction, which is either inward or outward, as determined by the detected motions.

Lastly, the system can detect the license plate and registration number of the vehicle. It can recognize the type of vehicle and categorize it according to segments such as two-wheelers, dump trucks, cars, etc. The system was able to count and classify vehicles in real-time with a high level of accuracy under different environmental situations such as the presence of shadows. Finally, the device is capable of detecting the vehicle's license plate and registration number. It is capable of identifying the type of vehicle and classifying it into categories such as two-wheelers, dump trucks, and automobiles. The system was able to accurately count and identify vehicles in real-time under a variety of environmental conditions, including the presence of shadows. To get our authentic object identification service, contact our professionals at [email protected]. We are here to provide you with the best industrial solutions available.