← Back to Case Studies
CASE STUDY — 02 / Outdoor · Privacy-First
Privacy-Protected
Geolocation Analysis
Capturing real-world mobility and community engagement through on-device processing — rich behavioral indices without ever transmitting identifiable location data.
Care Products
Smartphone App
On-Device Processing
MOBILITY PROFILE — 3 DAYS
Unique Spots
5
Total Outings
4
Max Distance from Base
163 km
Precise Address Disclosed
None ✓
↓ Sample data below
SAMPLE DATA
Outdoor Mobility Overview
One participant · Mar 1 – 3, 2026 · No GPS coordinates stored
MOBILITY PROFILE — 3 DAYS
MAR 01
Duration
359.9 min
Max Distance
41.5 km
First Out
10:44
Return
18:57
VISITED TARGET SPOTS
Fengbin 7-11, Achin Seafood
MAR 02
Duration
236.3 min
Max Distance
42.9 km
First Out
06:14
Return
10:10
VISITED TARGET SPOTS
Tz Hospital, ZY-Home, McDonald Hualien CC
MAR 03
Duration
594.3 min
Max Distance
163.4 km
First Out
14:05
Return
Overnight
VISITED TARGET SPOTS
Tz Hospital
The Privacy Challenge in Outdoor Research
Location data is among the most sensitive personal information a study can collect. Traditional GPS-tracking approaches require storing detailed movement logs on central servers — a significant IRB and participant consent barrier that has historically limited the scope of community-based research.
Care Active solves this with an on-device processing architecture: raw GPS coordinates are processed locally on the participant's smartphone. Only derived, abstract behavioral variables reach the research platform.
Behavioral Variables Derived
Despite never exposing actual places visited, the system generates a comprehensive mobility profile for each participant:
Distance from Home
Distribution
Statistical distribution of distances traveled from home across time — a validated mobility index in aging research.
Total Distance
km / day
Cumulative travel distance as an objective measure of physical activity and community mobility.
Outing Frequency & Duration
Per day
Number of times a participant leaves home and total time spent outside — sensitive markers of independence and engagement.
Target Spot Visits
Count & Dwell
Visit frequency and dwell time at researcher-defined locations of interest, without exposing precise coordinates.
IRB Compliance by Design
The system's architecture makes IRB approval substantially easier to obtain. Because precise location data is never collected or stored by the research platform, many of the most common ethical concerns around location tracking are addressed at the infrastructure level — not through policy alone.
Next Case Study
Object Motion &
Routine Analysis
See how a single sensor transforms everyday objects into behavioral instruments.
View Case Study 03 →