“Intelligent Environments (IEs)” is growing fast as a multi-disciplinary field allowing many areas of research to have a real beneficial influence in our society. The basic idea behind these systems is that by enriching an environment with technology (sensors, processors, actuators, information terminals, and other devices interconnected through a network), a system can be built such that based on the real-time information gathered and the historical data accumulated, decisions can be taken to benefit the users of that environment.

Expected benefits of this technology can be: (a) increasing safety (e.g., by monitoring lifestyle patterns or the latest activities and providing assistance when a possibly harmful situation is developing), (b) comfort (e.g., by adjusting temperature automatically), and (c) economy (e.g., controlling the use of lights).

The Journal on Reliable Intelligent Environments focuses on theoretical developments and lessons learnt on the deployment of IEs. The broad areas represented in the journal reflect the fact that reliability of software systems is the result of a number of approaches combined so an overarching principle of our publication will be to be open and flexible to embrace all type of techniques which can increase confidence in Intelligent Environments systems:

• selection, installation and calibration of equipment
• deployment and maintenance problems
• requirements
• modeling
• simulation
• testing
• validation
• formal verification
• people-centred computing
• tools
• pilots design
• software development process
• security
• privacy
• usability
• safety
• performance
• quality of service
• large-scale integration
• scalability
• adaptiveness and autonomicity

• Covers intelligent environments of any scale, ranging from smart materials and wearable networks in clothes, to smart buildings and systems of geographic scale, such as smart cities and geosensor networks
• Encourages and disseminates all types of techniques, methods and tools which can make Intelligent Environments safer to use, more widely accepted and trusted, more resilient to hardware and software problems
• Examines every stage from equipment selection to modeling, scalability, testing and verification to large scale integration and deployment.