Initial Situation: Modern paradigms such as Service-oriented and Pervasive Computing are currently influencing the capabilities future systems will provide. Context-aware runtime adaptivity, openness during runtime for new services and a strong focus on user assistance will be some of the prominent features these systems will have to engage. Especially user-oriented embedded systems such as automotive comfort systems or telecommunication devices will be influenced by such characteristics in the next years. In the automotive domain, for instance, the connectivity between internal systems and external devices (e.g. mobile phones, notebooks, palms) or other external “things” such as other cars, traffic management systems or media services will highly increase. At the same time new technologies (e.g., 3D-sensors) and new functionality with regard to an improved environment recognition will be integrated into car systems in even shorter times. The main challenges are to specify and develop not only the systems functionality but even the interactions under the circumstances of changing environments, usability requirements and safety as reliability concerns as well.
Although much effort has been already spent on the development of ambient technologies, a proven and systematic engineering approach and corresponding development support (e.g. frameworks) that supports building context-aware systems with a strong user orientation and predictable quality and behaviour are still missing.
However, without such a systematic methodology and engineering support, it will become very difficult to handle the complexity of such systems. This could lead to problems in the predictability of the developed results with regard to user acceptance or dependability.

Goal: The overall goal of this project is to research the aforementioned problems, engineer and evaluate solutions, and generalize them into an appropriate engineering approach that streamlines the development of adaptive, mobile systems with a predictable quality, behavior and user acceptance. This approach will be supported by corresponding frameworks / platforms and tools to optimize the professional development of user-oriented adaptive systems. In cooperation with industrial partners solution demonstrators will be developed that will provide the basis for latter products.

Measurable Results: The project activities will result in the following assets:
1. A formal, well-founded model on context definition, context recognition and context–based adaptivity with regard to dependable behavior and high user acceptance.
2. An efficient and effective engineering approach that allows developing and specifying systems in a user-driven manner that finally leads to predictable and context-aware solutions.
3. An (open-source) platform that allows context-recognition, context-analysis and context-aware adaptation through dynamical identification and composition of plug-and-play services or the situation in the environment 
4. A tool and infrastructure environment that supports the development of such systems based on the developed research results.
5. A set of realistic demonstrators that are built based on the aforementioned results and provide the basis for products produced by the industrial partners.

Target Domain: Automotive and / or Telecommunication

High-level WP:

1. Development of an holistic user-driven engineering approach

2. Development of an context-recognition and context-aware adaptation model

3. Architectural design

4. Development of an service oriented platform to support context-recognition and adaptation

5. Senor technologies for context-recognition 

6. Tool development

7. Evaluation

• Research in context-recognition and adaptivitiy
• Development of a platform that supports context-recognition and adaptivity
• Tool development to support the engineering approach
• Case study development of prototyp solutions based on the project results

• Electronic Suppliers (for the Automotive Domain)
• Telecommunication Provider
• Tool and Platform developer
• Research experts for context-recognition and adaptive systems