The findings suggest that both participants and authorities adopted a narrow perspective on IT as a production tool to support business-related skills such as word processing and spreadsheets, which were believed to broaden access to employment opportunities. The social agents in this study are authorities in the municipal government and African-American adults taking part in a community technology initiative in an urban, working-class neighborhood.
In this ethnographic study, I examine the discourses that social agents enact as they increase their awareness of information technology (IT) and the digital divide. We illustrate how each component of this framework can be implemented for this specific activity recognition problem and demonstrate how different implementations compare and how they impact overall recognition performance. We conclude with the educational example problem of recognising different hand gestures from inertial sensors attached to the upper and lower arm. We detail each component of the framework, provide references to related research and introduce the best practise methods developed by the activity recognition research community. We then describe the concept of an activity recognition chain (ARC) as a general-purpose framework for designing and evaluating activity recognition systems. We first discuss the key research challenges that human activity recognition shares with general pattern recognition and identify those challenges that are specific to human activity recognition. It specifically focuses on activity recognition using on-body inertial sensors. This tutorial aims to provide a comprehensive hands-on introduction for newcomers to the field of human activity recognition. With activity recognition having considerably matured so did the number of challenges in designing, implementing and evaluating activity recognition systems.
The last 20 years have seen an ever increasing research activity in the field of human activity recognition.
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