The goal of the SafetyNet system is to provide federal, state and local officials with the technology and capabilities to protect the homeland's ports, borders, and other security sensitive perimeters and infrastructures. SafetyNet is a collaborative effort between UTA and Advanced Acoustic Concepts (AAC) of New York (with offices in Texas) with possible partnerships with Montana State University, Vermont Bennington Microtechnolgoy Center, UTEP (Center for InterAmerican and Border Studies), Texas A&M Corpus Christi, Texas A&M College Station, ProLogic, and State and Federal agencies involved in port and border security. SafetyNet is a pervasive, common perimeter security system to provide surveillance and interrogation for: harbors/ports, borders, high value / high risk facilities, airport/train yard perimeters, and shipping containers. A "Peer Review Process" (PRP) is being utilized to select and integrate the required technologies. PRP utilizes "Best of Breed" for technology insertion by leveraging the commerical market, product reuse, rapid technology insertion means, and periodic testing. The system includes a self-organizing smart sensor network in which the system can be configured to satisfy the requirements of any site by adjusting the sensor suite. The enabling technologies include: off-the-shelf sensors such as video, radar, acoustic, IR, biochemical, seismic/pressure, gamma ray, magnetic, etc. The higher layer includes an innovative pervasive computing system that will utilize the concept of "community computing" to deploy intelligent software agents to: select and fuse relevant sensor data, make threat-detection decisions, make context-based action recommendations to counter threats. SafetyNet aims to interface with the existing legacy systems and databases. For example, if SafetyNet detects the presence of a suspicious container on a cargo ship, its software agents can query the US Customs Service or Port Authority databases for additional information about the owner of the container or cargo ship itself. Such information will then be fused with other pieces of sensory data and used in threat-detection decisions.