Work team coordination is becoming a major challenge in the contemporary complex working environments. Coordination process takes place through direct interaction and explicit communication, but it takes also advantage of informal social network within team members. Consequently, in order to develop realistic model of team coordination, we need to measure and model such interactions in real world environments. We present an agent-based model for simulating people movement in a workspace, which may be used as tool for developing and testing social relationship models. We demonstrate the model by simulating office life in one of our laboratories and comparing the results to actual measurements obtained with a sensor network.

Human behavior is characterized by a hugevariability. Accordingly, automatic recognition andmathematical modeling of human activities are verydifficult tasks even in relatively simple environments. Sensor technologies embedded into everyday livingspaces provide us an unprecedented extent ofinformation on people behavior, but these pervasiveenvironments are often hard to set up and raiseprivacy issues. We present a Monte Carlo simulation,which may be used as tool for developing and testingbehavior models. We demonstrate the modelsimulating the office life in one of our laboratories,and compare the results to actual measurementsobtained with a sensor network.