Aeyesafe
Timeline
1 Month (Jan. - Feb. 2025)
Platform
Web
Collaborators
2 Web developers, 1 PM
My role
I collaborated with the team to develop and test a web-based system, focusing specifically on designing the device management aspect of the platform.
THE CONTEXT
Bridging Care Gaps with IoT Intelligence
Aeyesafe is an AI healthcare company. We received a commission from a nursing home with the goal of helping the nursing home's caregivers to more effectively monitor the health conditions of the elderly through IoT devices.
The Challenge
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Elderly Care Challenges
Caregivers often face difficulties in continuously monitoring the physical condition of the elderly, especially with the increasing number of seniors and the complexity of their health issues.
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Technology Integration
The integration of IoT devices in elderly care has opened new possibilities for remote monitoring and health management, but it also brings the challenge of managing and understanding these devices efficiently.
Research Methodology & Insights
Deep Dive into User Needs
To anchor our design in real-world needs, we conducted a mixed-methods research approach, blending qualitative and quantitative insights.
User Interviews: Uncovering Pain Points
Participants: 10 in-depth interviews (60–90 mins) with caregivers (8) and procurement staff (2).
Methods: Semi-structured interviews + contextual inquiries to observe workflows.
Key Findings:
"I spend hours setting up devices—time I should spend with residents."
Insight: Complex onboarding delayed caregiving.
"I miss critical alerts buried in data overload."
Insight: Unprioritized data caused oversight risks.
"We forget maintenance until devices fail."
Insight: No system for proactive device upkeep.
Market Analysis: Identifying Industry Gaps
Reviewed 12 competing platforms, revealing:
Fragmented workflows: Tools lacked integration between monitoring and maintenance.
Overly technical interfaces: Assumed advanced user expertise.
Synthesizing Insights
We mapped findings into three core design opportunities:
Simplify device onboarding to reduce setup time.
Prioritize critical health data to prevent oversight.
Proactively manage maintenance to avoid failures.
Personas: Bringing Users to Life
Sarah, the Nurse: Needs quick device access during hectic shifts.
Linda, the Administrator: Requires high-level oversight for resource planning.
Personas guided feature prioritization, ensuring solutions met diverse needs.
From Insights to Solutions
Research directly shaped the platform’s architecture
Simplified Onboarding
Problem: Caregivers wasted time configuring devices.
Solution: Step-by-step guides with visual cues cut setup time by 40% (user testing results).
Customizable Dashboard
Problem: Data overload obscured critical alerts.
Solution: Drag-and-drop widgets let users prioritize metrics (e.g., heart rate, fall detection).
Maintenance Alert System
Problem: Reactive repairs disrupted care.
Solution: Automated alerts for battery life, calibration, and warranty expiry.
Solution Framework
Created to envision how the feature would be used in real-life situations.
Core Architecture
Active Device Console
Smart Triage System
Color-coded status rings (Red = Vital sign sensors)
ML-prioritized alerts (Fall detection > Room temp)
One-Click Handoff
Select devices → Assign to colleague → Auto-generate handoff report
Inventory 360°
Device DNA Profiles
Maintenance history
Battery cycle count
Calibration status
Setup Revolution
Bulk Onboarding
Scan device QR wall
AI matches to room layouts
Auto-configure thresholds
Alerts and Notifications
Set up alerts for device maintenance needs.