POSTECH’s U-Health Monitoring and Support Smart Home for the Elderly

1. Contract “Services To The Home” Autonomic System Health care part Hospital / doctor Specialized organization Remote diagnosis Service Provider EEG Knowledge Monitor Respiratory rate Analyze Temperature ECG Autonomic computing part Information filtering / aggregation Situation / context modeling Intelligence reasoning Decision making caregiver Pulse Plan SpO2 Smart Home Network Coordinator Execute GPRS Data Network Cellular Network Internet Home networking part Information gathering Service discovery Appliance discovery Smart Home Accelerometer Home Gateway Emergency Sensor Sensing part Actuator Home control unit Home automation POSTECH’s U-Health Monitoring and Support Smart Home for the Elderly ZigBee Sensor Smart Home Services Medical Server Wireless Sensor Base ECG Sensor Service Bio sensor Environment sensor Sensor Contract U-Health Service Healthcare Providers ( Control System ) Networked Appliances Medical Wireless Sensors Network Hui Wang1, Hyeok-soo Choi2, Nazim Agoulmine1,3, M. Jamal Deen1,4 and James Won-Ki Hong1 1ITCE, POSTECH, Pohang, South Korea 2Computer Science & Engineering, POSTECH, Pohang, South Korea 3Computer Science, University of Evry Val d’Essonne, France 4ECE Department, McMaster University, Hamilton, Ontario, Canada General Research Framework Autonomic Computing Part • Autonomic decision-making Home Network Part • WBAN ( Wireless Body Area Network) • Ontology model for U-health smart home • Requirements • Semantically Rich Knowledge Base: Capture concepts and relationships • Dynamically Updateable Knowledge Base: Enhance with new information during lifecycle • Context awareness: Situation awareness in smart home & identify specific contexts. • Support semantic reasoning: Infer new facts and update Knowledge Base. • SHOM (Smart Home Ontology Model) • Using OWL (Web Ontology Language) to define classes and relations between them • OWL-DL (Description Logic) based on SHOIN Description Logic. OWL-DL ensure decidability • Concepts related to Smart Home Network, Appliances, Humans. • Decision Making • a. Data gathering through medical and environment sensors. • b. Data aggregation, fusion and filtering • c. Inferred information using First-order Engine Smart Home Components Importance & Motivation • Allow elderly to live independently and safely • Significant reduction in health-care costs • Many aspects of elderly well-being and safety can be automated • Early detection of health problem  early treatment  less expensive and better health • Improve chronic and geriatric care at home • Bring healthcare to remote locations & in poor countries through convergence application of ICT, NT and BT Plan • Information-based sensor scheduling to improve energy efficiency and low latency Sensor 1 Situation assessment How the world evolves? context • Motivation • Specific disease Determine relevant parameters of symptoms. • High-level information  Key relations among these symptoms. • Determine best body sensor(s) for specific parameters of symptoms. • Quantify sensing and communication operations for diagnosis. • Propose cooperative diagnosis models for different body sensors. • Approach • An Information-based probabilistic relation model • A Cost function over the energy expenditure • A correlation model between utility gain and energy loss Sensor 3 Data Sensor 2 Revise goals Goals Sensor tasking/action Actuators Generate/revise decision rules (SHOM) Demo Smart Home at POSTECH Information utility Heart Beats Sensor SpO2 Sensor Research Challenges • Algorithm • System Architecture Presence Smoke Detection Start SpO2 • Compatibility with low-cost standardized manufacturing • Intelligent sensors & actuators design • Ultra low power design of integrated circuits and systems • Best cost-performance reliability • Compatibility with existing techniques and healthcare models. • Interdisciplinary collaboration • Social/Societal implications • $$$$$ Initialization Motion Sensor Compute initial knowledge Knowledge good enough? Yes Light Path for Obstacles avoidance • Environment discovery • Addressing and routing • Self-organisation and Self-healing • Networks composition and mobility • Virtualization • Context modeling • Self -detection algorithms • Self-diagnosis algorithms • Intelligent sensing and monitoring • Learning Coordinator Statistical Analysis Decision Making Core No Knowledge Base AI Rules Sensor selection Knowledge Base Reasoning Decision Making Send information query Conclusions Monitoring Analyze Execute Appliance Control OS Platform • Improve quality of life & reduce healthcare costs • Enhance comfort and safety of elderly at home • Reduce stress and burden to family members • Design & testing of interface circuits with sensor elements • Progress in intelligent sensing, monitoring, and semantic decision making • Synergistic application of ICT, BT and NT for health and social well-being of humanity, especially elderly persons Wait for information Open Services Framework Sensors Actuators Update knowledge Physical Environment • subject to Smart Home + Humans Finish RFIDTag