System takes input video from real time mobile phone camera and process frames by using MATLAB and use the trained neural network YOLO to detect and count the number of people present in the scene.Based on number of people detected and predefined thresholds the system will display the most relevant and expensive advertisement for longest time in the busiest location and vice versa for less crowded areas.
Objectives
The main objective of this system is to improve the efficiency and automation in advertisement techniques.
To increase the sales of successful products through targeted promotions.
To increase awareness of new products among consumers.
To utilize modern technology in the advertising industry.
To strengthen the offline advertisement industry to match the success of online advertising.
Socio-Economic Benefit
Increased revenue for businesses.
Better customer engagement.
Cost-effective advertising.
Improved public safety.
Job creation.
Methodologies
The methodology of our system is Agile-Model.
Outcome
Developed Smart Advertisement System
Automated Advertisement Process
Increased Revenue Generation
Enhanced User Experience
Accurate Object Detection and Counting
Integration with External Systems
Documentation and User Manual
