Healthcare for the Elderly using the IoT
summary
A prototype links a Java-based gateway with a smartphone, smartwatch and iBeacons for room-level location to monitor countryside elders, detect falls (accelerometer + impact pattern) and trigger enterprise workflows via an IoT cloud. Tests show beacon TX power and GPS gaps require filtering; GPS turns on only when leaving home to save battery. Design scales: 5,000 users at five-minute intervals produces ~100–200 million events for analysis, and the cloud pipeline performs aggregation, detection and routing to responders.
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chapters (25)
- 0:00Introduction to IoT healthcare
- 1:16Aging population challenges
- 5:38Limitations of step counters
- 7:37Critical indicators for monitoring
- 10:02Data collection and hardware
- 12:52Beacon setup for room tracking
- 16:40Device usability for elderly
- 17:59Phone selection and battery life
- 20:13Cloud connectivity for devices
- 22:14Software requirements and GPS
- 25:53Fall detection algorithm
- 28:40Emergency button functionality
- 29:25TV-set integration for monitoring
- 32:22Data filtering and accuracy
- 34:01Key monitoring metrics
- 35:07Data volume and scalability
- 36:42Live data streaming
- 37:07Cluster processing with Apache Flink
- 42:28Location tracking and alerts
- 44:01Contact person system
- 45:13Mobile app remote control
- 46:37Simplified gateway setup
- 47:58User acceptance and privacy
- 48:40Data privacy and security concerns
- 49:03Q&A session
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