Intelligent Information Systems

Our research on intelligent information systems (I2S) is concerned with the application of Artificial Intelligence (AI), services computing and semantic technologies for innovative means of intelligent data analysis and service coordination in smart information systems in the Internet.

Vision

Intelligent information systems in the future Internet of Things and Services are envisioned to provide users with intelligently assisted real-time access to relevant data and service coordination anywhere, anytime, on any device, to anyone, safe and secure. Agent technologies for individual or joint AI action planning and learning, inter-agent communication, negotiation and coordination can be used to implement autonomous, rational, proactive, adaptive and collaborative behaviour of such systems with intelligent agents. Services computing enables intelligent agents to provide and coordinate (discover, select, negotiate, compose, execute) their own and other services more flexibly and efficiently in different IT environments. Semantic technologies enable the semantic interoperation of distributed heterogeneous data, services and process models by these agents for intelligent information systems in support of industry and business, as well as our private and social  life.

Research Areas

The I2S research team of the DFKI-ASR department has long-standing, internationally recognized expertise and competencies in the following research areas:

  • Semantic search and composition planning of services in dynamic, heterogeneous and distributed environments
  • Automated negotiation of charged data and services (bargaining, coalition formation, auctions)
  • Semantic data stream analysis with uncertainty and semantic explanations to human users
  • Hybrid deep learning for scene interpretation and action planning by autonomous agents

Technologies

The I2S team offers innovative and implemented technologies for

  • Service coordination 
  • Semantic data analysis
  • Negotiation mechanisms
  • Process optimisation

Selection of our open-source and partly awarded software tools and benchmarks.

Applications 

Our technologies for intelligent data analysis and service coordination have been applied to various industrial use cases:

  • Production planning and logistics in agriculture and forestry
  • Process optimisation in automotive and metal processing
  • Intelligent condition monitoring / predictive maintenance
  • Semantic business process management in smart retail
  • Smart event management and social media analysis
  • Smart decentralized power regulation in micro-grids
  • Mobile medical assistance services in health care
  • Adaptive navigation in autonomous driving 

Selected intelligent information systems of our team have also been  demonstrated at the CEBIT, the Hannover Industry Fair (HIM) and the International Consumer Electronics Show (CES).

Selected Projects

Our research and development has been conducted in many projects funded by the European Commission, national government and industry.  The team contributions to selected research projects are as follows:

  • REACT (BMB+F; 2017 – 2020): Autonomous Driving – Learning and Simulation Environment for Critical Traffic Scenarios.  Team contributions: Hybrid deep learning for scene interpretation and navigation planning by autonomous cars and pedestrians in critical traffic scenarios. Simulation of adaptive (hybrid deep learning based) behavior of autonomous agents (cars, pedestrians) in virtual 3D environment with openDS.
  • CREMA (EC H2020 Factory of the Future, RIA; 2015 – 2017): Cloud-Based Rapid Elastic Manufacturing. Team contributions: Optimization of semantic service-based business process models in BPMN at design time and runtime; Largest publicly available manufacturing ontology CDM-Core with focus on machinery maintenance and automotive exhaust production.
  • INVERSIV (BMB+F; 2014 – 2017): Integrated Verification, Simulation and Visualization for Industrial Applications. Team contributions:  Semantic and probabilistic sensor data stream analysis for fault  detection and diagnosis; Integration with model-based prognosis and worker support; Parallel and distributed solutions of NP-hard manufacturing problems.
  • ICM-Hydraulic (HYDAC GmbH; 2013 – 2015): Intelligent Condition Monitoring of Hydraulic Machines. Team contributions: Combined statistical and hybrid semantic sensor data stream analysis for highly accurate fault detection and diagnosis of hydraulic machines; Automated generation of semantic explanation of diagnosis result to the human operator; Application to condition monitoring of wind turbines.
  • SocialSensor (EU FP7, IP; 2011 – 2014): Real-Time Multimedia Content Search and Analysis in the Social Web. Team contributions: Semantic middleware; Automated semantic search and composition planning of media servicess; Mobile (Android) application MyMedia for semantic end-to-end search and streaming of videos and live recordings.

Selected Publications

Selected publications on different research results of the team and their application in different industries are listed below:

Contact

PD Dr. Matthias Klusch (Team leader)

I2S Research Team:  http://www.dfki.de/~klusch/i2s