Health Innovation Projects (HIP@DISC) – Connections everywhere with a Web of devices and heterogeneous “Big Data” stores (Ambitious Individual Projects addressing a common theme, meeting as a group)
Smart cities (www.ibm.com/thesmartercity) allow citizens to more actively engage with their surroundings with smart phones, social media and sensing devices. The network of interconnected devices has been termed The Internet of Things (IOT). This project aims to explore the augmentation of such cities by combining sensor technologies from a number of devices – Merck Serono medical devices, RFID/NFC/QR tags, Microsoft Kinect and Smart Phones – and social media. A smart health scenario is chosen, within a smart city, where the citizen can monitor their own health whilst generating data trails that record their lifestyle. Such smart health scenario is premised on software and services that are able to collect, store and analyse data in a natural and pervasive manner (embedded into everyday life).
HIP@DISC will provide a number of innovative FYPs that address connection to specific devices, visualisation of data, cloud big-data storage and intelligent data analysis.
Although each project is individual (and assessed as such), the projects offers a real chance to interconnect and experiment on a wider environment with both technology and usability opportunities. The group will also work together on literature gathering and analysis. The supervision will be carried out by Prof. Barnett, Dr. Bell and Prof. Young; and include meetings with Merck Serono providing industry context and perspective. You are likely to have meetings with academics over the course of the year in order to fully support different activities and parts of the project.
Some possible project ideas:
• Medical device data acquisition using smartphones (3 separate projects).
• Smart phone development using GPS tracking to collect mobility information and interact with health service providers on the move (seeking services in a Smart City).
• Smartphone capture of wellbeing and happiness (including direct entry and sensor based inference).
• RFID, NFC or QR codes to label physical proximity to either track their movement or use of specific objects (devices or medicines).
• Diet and medical tracking with self-management on a smartphone.
• Kinect sensor (NUI) allowing user tracking in their physical environment at home (with interaction with virtual health professionals)
• Big Data storage in the Cloud – storing data for other projects in the cloud
• Data visualisation of cloud based Big Data (using Smart Phones, PCs or Ambient screens)
• Data visualisation of real time data of the Web of Devices (using Smart Phones, PCs or Ambient screens)
• Intelligent data analysis of Big Data (using clustering or other algorithms).
• Intelligent data analysis of Social Media Data (using clustering or other algorithms).
• Pharma data analysis (and Reporting) of drug performance
• Smart Phone recommender systems for Smart Health
• Co-design of the smart health mobile services (promoting interaction between citizen and health provider)