The ATHENA
Activity-awareness for Human Engaged Wellness Applications


Overview
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Brief overview of the System

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Motivation
  • To Build a system over the assistive technologies that can take care of mental health, physical health and social-wellbeing to provide a smart care for individuals as well as population level.
  • To provide a common platform which process activities, emotions and social networks followed by the human behavior analysis.
  • To utilize the cutting edge technology for storage and processing to solve the bottleneck issues of massive sensory data processing.
Goals
  • Our goal is to process the human activities, emotions and social interaction all together for providing the wellness services.
Features
  • Developing a proactive approach to adopt healthy lifestyle in our daily routines.
  • Solving the primitive challenges of core algorithms such as recognition rate, cost and processing overheads to asses the contexts.
  • Introducing novel light-weight classifiers that works well inside the smart devices.
  • Providing Cloud computing infrastructure as a cost effective solution for computation intensive tasks.
  • Utilizing Hadoop based infrastructure to store the massive sensory data.
  • Introducing the feedback mechnism to provide the more robust and accurate services.
  • Make the proposed system available to the other developers through information sharing proper interface so that they can build and develop the services applications over the core technology framework.
Uniqueness
  • ATHENA provide a common platform to process mental, physical and social health and provide wellness services for the active lifestyle.
  • The underneath component of context-aware processing will be able to work independently and flexible, so that it can be tweaked according to the targeted application.
  • The feedback methodology to re-train the context-aware processing module and increase the usefulness of our services according to the user preferences and configurations.
  • Storing massive amount of hetrogeneous sensory data in Hadoop based infrastructure that are able to process the massive queries.
  • Our proposed platform will be deployed over the cloud as a backbone infrastructure that reduce the cost and make available to different smart devicesand platforms.