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Related Experiment Video

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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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Review on Human Action Recognition in Smart Living: Sensing Technology, Multimodality, Real-Time Processing,

Giovanni Diraco1, Gabriele Rescio1, Pietro Siciliano1

  • 1National Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.

Sensors (Basel, Switzerland)
|June 10, 2023
PubMed
Summary

Smart living uses sensing and human action recognition to improve daily life. This review synthesizes key research areas for advancing these technologies in smart environments.

Keywords:
ambient assisted livingdeep learninghuman action recognitioninteroperabilitymachine learningmultimodalityreal-time processingresource-constrained processingreviewsensing technologysignal processingsmart citysmart communitysmart environmentsmart homesmart living

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Ubiquitous Computing

Background:

  • Smart living integrates technology into homes and cities to enhance quality of life.
  • Sensing and human action recognition are foundational to smart living applications.
  • Effective human action recognition is vital across domains like energy, healthcare, and transportation.

Purpose of the Study:

  • To provide a comprehensive review of human action recognition in smart living environments.
  • To synthesize main contributions, challenges, and future research directions in the field.
  • To highlight the critical role of sensing and action recognition in smart living.

Main Methods:

  • Literature review focusing on human action recognition in smart living.
  • Identification and synthesis of five key research domains: Sensing Technology, Multimodality, Real-time Processing, Interoperability, and Resource-Constrained Processing.
  • Analysis of sensor modalities beyond visual data for action recognition.

Main Results:

  • Human action recognition is essential for diverse smart living applications.
  • Five critical domains (Sensing Technology, Multimodality, Real-time Processing, Interoperability, Resource-Constrained Processing) are identified as crucial for deployment.
  • The review consolidates current knowledge and identifies gaps in the field.

Conclusions:

  • Sensing and human action recognition are pivotal for developing and implementing smart living solutions.
  • Further research in the identified key domains is necessary to advance the field.
  • This paper serves as a valuable resource for researchers and practitioners in smart living and human action recognition.