The Lifespan of Human Activity Recognition Systems for Smart Homes

Area of Science:

• Computer Science
• Artificial Intelligence
• Ubiquitous Computing

Background:

• Smart home environments require robust human activity recognition (HAR) systems for automated assistance and health monitoring.
• Existing HAR systems need continuous improvement to adapt to personalized and idiosyncratic resident behaviors.

Purpose of the Study:

• To provide a systematic analysis and technical definition of the lifespan for smart home HAR systems.
• To establish a framework for developing and improving HAR systems through data-driven procedures.

Main Methods:

• Systematic analysis of HAR system development phases within a smart home context.
• Definition of technical solutions required for each phase of the HAR system lifecycle.
• Focus on data-driven procedures for continuous system improvement.

Main Results:

• A defined lifespan for HAR systems, outlining distinct phases from development to continuous improvement.
• Identification of technical solutions tailored to each phase of the HAR system lifecycle.
• A framework for designing state-of-the-art HAR procedures.

Conclusions:

• The proposed lifespan framework facilitates the creation of more functional and adaptable HAR systems.
• Data-driven approaches are crucial for the continuous enhancement of HAR systems in smart homes.
• This work provides a structured methodology for advancing HAR technology in personalized living environments.