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Cloud Service for Elderly Care: Daily Activity Recognition

This cloud service aims to integrate resources and provide care services and information to elderly individuals, caregivers, and researchers through daily activity recognition. It includes technical components such as inference engine improvement, ADL data mining platform, cloud middleware, data collection, live data transfer platform, active recognition adjustment, ADL database, and healthcare platform service. The goal is to improve elderly care and provide valuable insights for better healthcare decision-making.

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Cloud Service for Elderly Care: Daily Activity Recognition

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  1. Cloud Service for Elderly Care Subject 4 Daily Activity Recognition for Elderly Care 傅立成 教授 郭斯彥 教授

  2. Outline • Introduction • Technical Components • Scenario 2

  3. Objectives • Three goals of cloud-based platform • Integrate various resources of elderly care. • Provide necessary care services and information to elders, care-givers and researchers. • Provide extensible service provision interface to extend our service 3

  4. Inference Engine Improvement ADL Data Mining Platform Cloud Services Healthcare Platform Cloud Database Service Expansion Demo Technical Components (5)Healthcare Platform Service (4)ADL Data Mining Platform (3)Inference Engine Improvement (2)Cloud Middleware Cloud Middleware（Live E!、API） Activity Recognition Weather (1)Data Collection 4

  5. Data Collection （1/5） • WSN • Indoor Temperature, Humidity • Outdoor Temperature, Humidity, Rainfall • Heartbeat, Systolic, Diastolic • User Feedback • Excretion frequency • Quality of sleep • Pain index • Activities of Daily Living • Read • Watch TV • Prepare Food • Drink • Go out & Go home • Sleep • Clean 5

  6. Live E! Data Transfer Platform or sensor data Cloud Database Cloud Middleware（2/5） • Live E! protocol • Developed by The University of Tokyo • IEEE 1888 • API for cloud data center • Design a highly reliable middleware to access cloud databases. • The high flexibility feature of cloud facilitates dynamic adjustment of servicesand the receiving of useful information. Cloud Middleware 6

  7. Active Recognition Adjustment ADL Database (HBase) Home Service Inference Engine Adjustment（3/5） • Use self-developed cloud MREM algorithm to adapt home-side activity recognition model to context change dynamically. Cloud Collaborative Mode Mining Service Model Update Cloud Model Update Service Activities Data MREM: MapReduce-Assisted EM 8

  8. ADL Data Mining Platform（4/5） • Objectives • Mine useful caring knowledge from collected data • Serve as a readily accessible web service. • Possible combining applications • Chronic diseases alerting system • Other possibilities. • Properties: • Large-scale MapReduce enabled data mining. • Directly connection with the healthcare platform • Mining result may directly return to the healthcare platform. • Automatic medical advices generation. Other Cloud Database Data Mining Platform Households Cloud Middleware Other Information

  9. Attention XML FaceBook Elderly Information Caring Record Healthcare Platform Service(5/5) • Provide current information • body measurement, activity of daily living (ADL), and doctor prescription • To elderly and their families, and medical institutes. • Support Caring record for medical staff to better understand elderly people from long-term health status. • Explore potential applicative possibility through caring records analysis • Data mining related applications • Enhance social involvement of elderly people through Facebook application • Automatic sentence analysis and generation 10

  10. Thanks for your attention

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