How can multi-agent systems count unique park users?
A Case Study of Counting the Number of Unique Users in Linear and Non-Linear Trails - A Multi-Agent System Approach
This research explores counting unique park visitors using a multi-agent system of inexpensive cameras and distributed processing. The system analyzes visitor attributes like speed, direction, clothing color, and activity to identify individuals, constructing trails and comparing data between camera agents to avoid double-counting. Key points for LLM-based multi-agent systems include: distributed attribute collection and central processing, agent communication for unique user identification and trail construction, and potential for energy saving through selective agent activation based on predicted arrival times. The authors highlight the system’s affordability and potential for real-time online implementation, eliminating data storage needs and privacy concerns.