In this chapter we describe Cooperative Surveillance Agents (CSAs), which is a logical framework of autonomous agents working in sensor network environments. CSAs is a two-layer framework. In the first layer, called Sensor Layer, each agent controls and manages individual sensors. Agents in the Sensor Layer have different capabilities depending on their functional complexity and limitation related to specific sensor nature aspects. One agent may need to cooperate in order to achieve better and more accurate performance, or need additional capabilities that it doesn’t have. This cooperation takes place doing a coalition formation in the second Layer (Coalition Layer) of our framework. In this chapter we have proposed a framework architecture of the CSAs and protocols for coalition management. The autonomous agents are modeled using BDI paradigm and they have control over their internal state. But cooperative problem solving occurs when a group of autonomous agents choose to work together to achieve a common goal and make a coalition. This emergent behavior of cooperation fits well with the multi agent paradigm. We present an experimentation of CSAs. In this environment, the agent perception is carried out by visual sensors and each agent is able to track pedestrians in their scenes. We show how coalition formation improves system accuracy by tracking people using cooperative fusion strategies.