The Hillcrest Aging-in-Place Prototype is a fully active research environment focused on comfort stability, supportive automation, mobility-friendly lighting, and environmental cues designed to reduce cognitive load.

This home demonstrates how intelligence can support independence without intrusive technology.

Purpose

To understand how environmental stability, supportive routines, and low-effort automation enhance independence for aging residents.

Systems Deployed

Safety & Stability Automation

• Safety-aligned evening lighting

• Sunrise/sunset exterior lighting

• Motion-responsive pathways

• Predictable environmental routines

• Smart thermostat routines tuned for comfort stability

Comfort Intelligence

• Temperature smoothing for day/night transitions

• Central HVAC comfort behavior

• Automation that reduces manual adjustments

Robotics Support

• Robot vacuums and mops for cleaning support

• Low-friction floorpath mapping

• Charging station optimization

• Reduced clutter testing for robotic mobility

Design & Wellness

• Calm lighting tones

• Mobility-friendly layout adjustments

• Outdoor spaces supporting grounding and fresh air

Research Focus

Environmental Stability

How predictable routines improve comfort and reduce stress.

Safety Lighting

Evening and night pathways that reduce fall risk.

Automation Reduction of Cognitive Load

Lighting and comfort that adjust automatically.

Robotics for Support Tasks

Vacuuming, mopping, and regular maintenance tasks that reduce physical strain.

Environmental Cues & Wellbeing

Micro-movement, fresh air, natural light, and sensory stability.

Early Insights

• Safety-aligned lighting pathways reduce nighttime disorientation.

• Low-effort automation reduces the number of daily tasks required for comfort.

• Stable environmental routines improve perceived wellbeing.

• Robotic cleaning reduces physical effort without requiring complex interaction.

• Predictable comfort patterns help regulate day-to-day rhythm.

Roadmap

• assistive robotics integration (Phase 2–3)

• expanded sensing for environmental stability

• outdoor mobility-friendly enhancements

• micro-edge local intelligence integration

• care-supportive automation patterns