With the continuing expansion of the domain of interest and the increasing complexity of the collected information, intelligent techniques for fusion processing have become a crucial component in information fusion applications. The problem of Information Fusion has attracted significant attention in the artificial intelligence community, trying to innovate in the techniques used for combining the data and to refine state estimates and predictions. Intelligent systems can improve information fusion based on the context management aimed at supporting decision making, since the quality of decision making depends upon the quality of information at hand.
Research on Intelligent Systems and context-based information fusion in distributed sensor networks has matured during the last decade and many effective applications of this technology are now deployed. This special issue will collect a representative sample of the latest scientific developments and their effective applications, to assess the impact of the approach, and to facilitate technology transfer. Special care will be given to highlight successful opportunities in the application of AI paradigms to open challenges in information fusion, and practical approaches to solve real-world problems. Potential topics include, but are not limited to:

• Information Fusion, Context representation and exploitation.
• Hard & Soft Fusion.
• Robustness and Adaptation in Distributed Sensor Networks
• Intelligent Algorithms in Distributed Sensor Networks.
• Situation Awareness, Reasoning under Uncertainty.

The topics included cover design and development of modern information fusion applications taking new tools from artificial intelligence:

• Design of real fusion systems under hard/soft performance specifications: output constraints, bounded errors, human interaction, etc.
• Use of soft computing techniques for developing and adapting data fusion.
• Multi agent interaction and coordination in distributed sensor networks
• Representation and exploitation of high-level and contextual information in real systems.
• Data provenance and data pedigree in distributed sensor networks.
• Information sources in real applications with unknown uncertainty models.
• Description of representative problems with situations in which conventional techniques may fail (contextualized fusion systems such as defense, security, indoor localization, etc.)

International Journal of Distributed Sensor Networks is an open access journal, which means that all published articles are made freely available online without a subscription, and authors retain the copyright of their work. The most recent Impact Factor for International Journal of Distributed Sensor Networks is 0.203 according to 2011 Journal Citation Reports released by Thomson Reuters (ISI) in 2012.