Engineering context-aware systems

According to Anind Dey [1], context is:“Any information that can be used to characterize the situation of entities (ie whether a person, place or object) that are considered relevant to the interaction between a user and an application, including the user and the application themselves. Context is typically the location, identity and state of people, groups and computational and physical objects.” Today's computer systems are unaware of the user's context. They do not know what the user is doing, where is the user, who is nearby and other information related to the user’s environment. They just take the explicit input from the user, process it, and then output the result. Regarded as computing for the next generation, pervasive computing will greatly change the way computers behave. The basic idea is to instrument the physical world around us with various kinds of sensors, actuators, and tiny computers. The huge amount of information can then be collected and processed by computer systems, enabling computer systems to deduce the user’s situation and act correspondingly with user’s intervention. One demanding challenge for pervasive computing is how to collect and process data from sensors and other sources. Most early researchers built their solution in an ad hoc way to investigate the problem space [2][3]. They had to consider everything, including the details of reading sensor data, distributing sensor data, and transforming sensor data into high-level data as well as application adaptation behaviour. From software engineering perspective, this makes developing applications for pervasive computing very cumbersome.