Sensor-Based Activity Recognition

TLDR

Research on sensor‑based activity recognition has made significant progress and attracts growing attention across disciplines, yet a high‑level overview of the state of the art is lacking. The paper surveys the development and current status of sensor‑based activity recognition, distinguishing data‑driven and knowledge‑driven approaches and outlining promising future research directions. It reviews vision‑based versus sensor‑based methods, major sensor‑based approaches, and their strengths and weaknesses, structuring the discussion around the data‑driven versus knowledge‑driven paradigms.

Abstract

Research on sensor-based activity recognition has, recently, made significant progress and is attracting growing attention in a number of disciplines and application domains. However, there is a lack of high-level overview on this topic that can inform related communities of the research state of the art. In this paper, we present a comprehensive survey to examine the development and current status of various aspects of sensor-based activity recognition. We first discuss the general rationale and distinctions of vision-based and sensor-based activity recognition. Then, we review the major approaches and methods associated with sensor-based activity monitoring, modeling, and recognition from which strengths and weaknesses of those approaches are highlighted. We make a primary distinction in this paper between data-driven and knowledge-driven approaches, and use this distinction to structure our survey. We also discuss some promising directions for future research.