Projects per year
Project Details
Description
A government-funded healthcare innovation project focused on architecting and deploying secure, non-obtrusive technical frameworks for remote senior citizens living alone. The project establishes infrastructure baseline layouts to support real-time data collection across distributed domestic living quarters.
Key findings
Designed and successfully deployed secure Wireless Sensor Networks (WSN) and Internet of Things (IoT) hardware architectures. Integrated predictive AI modeling into the backend infrastructure to capture behavior changes, providing a low-cost, scalable framework for municipal-level ambient health tracking.
Layman's description
This project focuses on building a safe, budget-friendly network of wireless home sensors to look after senior citizens who live by themselves. By setting up these smart, non-intrusive sensors around the house and linking them to artificial intelligence, the system helps monitor the health and daily safety of the elderly remotely, alerting caregivers if anything seems wrong.
| Short title | Remote Elderly Health Care |
|---|---|
| Acronym | Shanghai Municipal Major Project |
| Status | Finished |
| Effective start/end date | 01/12/2012 → 31/12/2019 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
Keywords
- Wireless Sensor Networks (WSN), Internet of Things (IoT), Remote Care, Ambient Assisted Living (AAL), Smart Home Architecture, Predictive AI
Projects
- 4 Finished
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SAAD: Smart Aging Anomaly Detection (SAAD) ( MSCA H2020)
Ghayvat, H. (Supervisor) & Andersen, H. B. (Project participant)
01/10/2018 → 31/10/2020
Project: Research
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FogCueEs: FogCueEs Device (CÚRAM): Wearable electrical stimulation device for real-time gait guidance in Parkinson's Disease
Ghayvat, H. (Supervisor)
01/06/2017 → 30/06/2019
Project: Research
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Royal Society Fellowship: Royal Society Research Fellowship – Human activity recognition
Ghayvat, H. (Project participant)
01/01/2015 → 31/12/2017
Project: Research