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The main objective of GAMBAS is to develop an innovative and adaptive data acquisition and processing middleware to enable the privacy-preserving and automated use of behavior-driven services that are able to adapt autonomously to the context of their users.

Addressing the Challenges

GAMBAS is geared towards addressing the complete set of challenges in order to provide a truly integrated solution, thereby closing a significant gap between today’s systems and the vision of ubiquitous computing. Towards this end, the primary result of the project is the realization of a Generic Adaptive Middleware, i.e. a set of application-independent services, to support the development and utilization of Behavior-driven Autonomous Services.

As depicted below, the GAMBAS middleware will enable the development of novel applications and Internet-based services that utilize context information in order to adapt to the behavior of the user autonomously. To do this, the middleware will provide the means to gather context in a generic, yet resource-efficient manner and it will support the privacy-preserving sharing of the acquired data. Thereby, it will apply interoperable data representations which support scalable processing of data gathered from a large number of connected objects. In order to make the resulting novel services accessible to the user, the middleware will also support intent-aware interaction by providing a constant stream of relevant recommendations for services.

The GAMBAS approach
The realization of this middleware requires the development and integration of a flexible context recognition framework that is able to capture the context of users (e.g. location, activity, plans, intents), an interoperable data model to represent context information, a scalable data processing infrastructure to query and aggregate context information and to integrate context into services, a suite of security protocols to enforce the user’s privacy when sharing context information and last but not least, a recommendation system to largely automate the discovery and selection of relevant services available to the user. In addition, it requires tools to simplify the configuration of privacy policies which ensures that the user’s privacy expectations are met to improve the user experience and to increase user acceptance.

The Middleware Potential

As a consequence, the implementation of this middleware by the GAMBAS consortium will result in substantial inno-vations in the research areas of context recognition, data modeling and processing, data privacy and human computer interaction. In addition, the implementation will require the use and integration of existing research results in the area of communication support for ubiquitous computing scenarios.
To reach this ambitious goal with the available resources, the GAMBAS project will base its work on the concept of hierarchically organized Internet-connected objects that has been initially the focus of two previous European projects (Embedded WiSeNts, EMMA – FP6) and is currently adapted to ubiquitous computing scenarios by the PECES FP7 project with the collaboration of some of the GAMBAS consortium members. By actively leveraging the results of previous projects, it will be possible within GAMBAS to:
  1. Have a decisive impact in the design and development of solutions to the challenges given above despite the limited duration of the project.  
  2. Use its available resources optimally, thus avoiding “reinventing the wheel” by design.
  3. Minimize the technological risks by building upon well-proven methods and technologies, and thus, maximizing the achievability of the GAMBAS goals.
Furthermore, in order to validate the results in a realistic environment, the GAMBAS consortium will develop a prototype application that builds upon the concepts and mechanisms provided by the middleware and the associated tools. In particular, the GAMBAS prototype application will be developed for the public transportation domain for the following reasons:
  1. Public transportation is a truly ubiquitous domain in which almost everybody is immersed in at certain times, e.g. daily commute from/to work, business trips, vacation and leisure, etc.
  2. Public transportation is a complex domain that exhibits all of the challenges described above.  
  3. Technological solutions can be shown easily through simulation or constrained real settings.
  4. Robust working solutions have the potential to make a significant and high impact.

Securing Impact

The long-term impact of the GAMBAS project will be secured by the provisioning of publicly available specifications of all research and developments efforts and by the dissemination activities performed by the members of the consortium.
In summary, the GAMBAS project has the following scientific and technical objectives:
1. Development of a generic adaptive middleware for behavior-driven autonomous services by developing and integrating the following components:
  • Models and infrastructures to support the interoperable representation and scalable processing of context information gathered by a large number of connected objects.  
  • Frameworks and methods to support the generic yet resource-efficient multi-modal recognition of context information via physical and virtual information sources.
  • Protocols and tools to derive and generalize as well as enforce user-specific privacy-policies when sharing context information via insecure networks.  
  • Techniques and concepts to optimize the interaction with behavior-driven autonomous services by providing suitable recommendations on the basis of user intents.
2. Validation of the previously described middleware and its associated components using lab test and a prototype application in the public transportation domain.

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