As P2P-TV applications are widely used on the Internet, its disadvantages shows up with its conventions, particular the easier spread of erotic, violent or pirated content. To address this problem, this paper presents a system that can accurately identify and closely monitor the P2P-TV traffic passing through a campus network. It consists of five core modules: data collection, traffic identification, active measurement, video content detection and filter, and center of visualization. The basic flow of the content monitoring contains five steps: 1) the data collection module collects mixed traffic from the campus gateway, 2) the traffic identification module classifies the mirrored traffic and identifies the P2P-TV traffic flows of the corresponding platforms and their channels watching by the viewers in the campus network, 3) the active measurement module is driven to probe the behavior, IP addresses and geographical positions of online viewers, 4) the video content detection and filter module recovers the video content from the identified P2P-TV traffic and performs anomaly detection, and 5) the center of visualization module is responsible to interact with other modules and visualizes all results on the web in various manners.