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PErvasive Computing in Embedded Systems (PECES)
Start date: 01 Oct 2008, End date: 31 Dec 2011 PROJECT  FINISHED 

The overarching goal of the PECES project is the creation of a comprehensive software layer to enable the seamless cooperation of embedded devices across various smart spaces on a global scale in a context-dependent, secure and trustworthy manner.The increasing number of devices that is invisibly embedded into our surrounding environment as well as the proliferation of wireless communication and sensing technologies are the basis for visions like ambient intelligence, ubiquitous and pervasive computing. The benefits of these visions and their undeniable impact on the economy and society have led to a number of research and development efforts. These include various European projects such as EMMA or AMIGO that develop specialized middleware abstractions for different application areas such as automotive and traffic control systems or home automation. These efforts have enabled smart spaces that integrate embedded devices in such a way that they interact with a user as a coherent system. However, they fall short of addressing the cooperation of devices across different environments. This results in isolated 'islands of integration' with clearly defined boundaries such as the smart home or office.For many future applications, the integration of embedded systems from multiple smart spaces is a primary key to providing a truly seamless user experience. Nomadic users that move through different environments will need to access information provided by systems embedded in their surroundings as well as systems embedded in other smart spaces. Depending on their context and on the targeted application, this can be smart spaces in their vicinity such as 'smart stores' or distant places with a specific meaning such as their home or their office or dynamically changing places.PECES is committed to developing the technological basis to enable the global cooperation of embedded devices residing in different smart spaces in a context-dependent, secure, and trustworthy manner.
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