Constructing an Ambient intelligence development framework

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Constructing an Ambient Intelligence Development Framework: 

Constructing an Ambient Intelligence D evelopment F ramework Student: Bui Vu Hoang Co-supervisor: Assoc. Prof. Bui The Duy Co-supervisor: Dr. Vu Thi Hong Nhan

Content: 

Content Introduction Our Ambient Intelligence Development Framework Implementation & Results Conclusion Demo

Content: 

Content Introduction Our Ambient Intelligence Development Framework Implementation & Results Conclusion Demo

Introduction: 

Introduction Ambient Intelligence was Introduced by the Information Society Technologies Advisory Group in 2001. There are many Ambient Intelligence development frameworks Exp : WOSH [ http :// wosh.sourceforge.net/docs , 2007] CAMPUS [ Karin et al, 2008]

Contribution: 

C ontribution Problem: Ambient Intelligence requirements satisfaction Our solution: A framework that intuitively satisfies the requirements

Ambient Intelligence Requirements: 

Ambient I ntelligence Requirements Ubiquitous computing Distributed, collaborative Plug-n-play Ubiquitous communication No coupling Real-time data streams Intelligent user interfaces

WOSH: 

WOSH Advantages Feature extensive Suitable for large areas Disadvantages Coupling between components Possible duplications

CAMPUS framework: 

CAMPUS framework Advantages No coupling Global communication Disadvantages No data storage

MICA framework: 

MICA framework A framework for agent-based systems Developed by New South Wales University.

MICA: 

MICA Blackboard: A central place for Communication Data storage Agent and Blackboard transports Developers can focus on the component

MICA: 

MICA Transports’ mechanisms are slow No buffer to ensure data rate No mechanism to provide seamless data streaming components

Content: 

Content Introduction Our Ambient Intelligence Development Framework Implementation & Results Conclusion Demo

Our AmI Development Framework: 

Our AmI Development Framework Agent-based Based on MICA framework Supports real-time data streaming

Design goals: 

Design goals Plug-n-play Agents can join and start operating Collaboration Multiple agents can access a single data stream No direct coupling Agents operate without knowing the existence of other agents

Overall view: 

Overall view

Broadcaster & Receiver Registration: 

Broadcaster & Receiver Registration

Streaming Registration Monitor: 

Streaming Registration Monitor

Broadcaster Registration: 

Broadcaster Registration

Receiver Registration: 

Receiver Registration

Overall view: 

Overall view

Broadcaster stream: 

Broadcaster stream

Receiver stream: 

Receiver stream

Component design: 

Component design

Overall view: 

Overall view

Content: 

Content Introduction Our Ambient Intelligence Development Framework Implementation & Results Conclusion Demo

Implementation: 

Implementation Video encoder/decoder: Xuggle RTP stack: Efflux Java, Eclipse IDE Video format: MPEG4, 320x240p, 25fps 3 Intel Core i3 2.5GHz machines with 2GB of RAM running on Windows 7 Ultimate 32bit Wired network

Results: 

Results Avg. speeds Broadcaster Receiver Packets/s 2600 90 bits/s 30M 1000k Standard videoconferencing quality: 384kbps Standard audio quality: 128kbps High quality Skype video call: 500kbps

Content: 

Content Introduction Our Ambient Intelligence Development Framework Implementation & Results Conclusion Demo

Conclusion: 

Conclusion A framework design that supports Dynamic components Collaborative components No direct coupling between components A working prototype with high performance

Future work: 

Future work Create an actual small scaled AmI system in our lab with the framework Make improvements to the framework Fix bugs Add more features Long term goal: promote our framework to be a standard and high quality AmI development framework

Content: 

Content Introduction Our Ambient Intelligence Development Framework Implementation & Results Conclusion Demo

Demo: 

Demo

Thank you for listening: 

Thank you for listening