4W1H and Particle Swarm Optimization for Human Activity Recognition

This paper proposes a paradigm in the forensic area for detecting and categorizing human activities. The presented approach uses five base variables, referred to as 4W1H (“Who,” “When,” “What,” “Where,” and “How”) to describe the context in an environment. The proposed system usesself-organizing mapsto classify movements for the “How” variable of 4W1H, as well asparticle swarm optimization clusteringtechniques for the grouping (clustering) of data obtained from observations. The paper describes the hardware settings required for detecting these variables and the system designed to do the sensing.