Multi-sensor Logical Decision Making in the Single Location Surveillance Point System

As demand for surveillance of physical locations increases, automated decision making software can help maintain the rising costs of human monitoring. The variety in different types of sensors is also growing, and making use of their consolidated data can improve the decision making process. Using the constructive research method, we aim to define a design of a surveillance system's decision making component that utilizes data fusion from multiple types of sensors. As a solution we present the Logical Decision Making Server (LDMS), used in the Single Location Surveillance Point (SLSP), a system designed for monitoring an indoors location. The decision making capabilities in the LDMS are based on user-configurable security rules, which allow security personnel to define threats based on current and recent event reports from any or all of the environment’s sensors. The LDMS has been successfully developed and integrated into an SLSP implementation.