Empowering People with Disabilities in Smart Homes Using Predictive Informing

Area of Science:

• Assistive Technology
• Smart Home Environments
• Artificial Intelligence

Background:

• Investigating Ambient Assisted Living (AAL) and Enhanced Living Environments (ELE) in smart homes.
• Focusing on improving accessibility and quality of life for individuals with disabilities.
• Addressing the need for personalized and adaptive living spaces.

Purpose of the Study:

• To explore the potential of smart home technology for people with disabilities.
• To develop a conceptual mathematical model for predictive user information.
• To define a taxonomy of smart home components and their interactions.

Main Methods:

• Utilizing artificial intelligence (AI) and machine learning (ML) systems.
• Analyzing user preferences, habits, and potential incident data.
• Proposing a conceptual mathematical model for data analysis and prediction.
• Defining a taxonomy of communication technologies, devices, and sensors.

Main Results:

• A conceptual mathematical model for generating predictive user information was proposed.
• A taxonomy of smart home technologies and their interactions was defined.
• The integration of assistive technologies can adapt homes for diverse user needs.

Conclusions:

• Smart home environments with AI/ML can significantly enhance the lives of people with disabilities.
• Established data sets are crucial for future AI and ML model development.
• The proposed model provides a foundation for personalized assistive living environments.