The term “context awareness” can have different meanings for different people, or be used in different ways. For instance, in the domain of smartphones, some may say that applications using location and wireless connectivity information are context-aware, and others may even think that the term means that smartphones can or should sense the state of mind of the user. For example, if the user is excited and her hands are shaking, the phone can use a correction algorithm for the events of the touch screen, or if the user is rushing to do something, the phone can behave according to that state of mind. The common usage generally refers to analyzing information using sensors and being able to change behavior according to this information.

Recent studies in the field of ubiquitous computing have started to shift from location awareness and basic activity recognition to context awareness, using the knowledge base gained from the previous studies.

This paper presents a context-aware framework for cross-platform applications. In section 1, the authors start by explaining what context awareness is from their point of view and what is to be expected from context information. This information contains data collected from the devices we are using, like Wi-Fi connectivity, ambient light sensors, or geographical location. In section 2, after explaining why this information is important, they provide a list of context-aware systems to show the state of the art of this area. Section 3 explains what Webinos is and how it works. In sections 4, 5, and 6, they explain how context acquisition is done on Webinos and provide a detailed architecture of how this works. In sections 7, 8, and 9, they explain what kind of queries the program needs.

The strongest points of this paper lie in the relevance of the topic discussed. Increasing numbers of mobile phones and portable devices contain sensors that are getting better and more precise, making the context awareness issue ready to mature. Due to the reasons explained before, applications and frameworks that cope with context awareness help us discover new areas and problems, and contribute to the knowledge base in this field.

The analysis of related work made me feel that either the analysis was weak or that the work dates back a few years, because the selected literature is quite old. Almost all of the references go back to 2005, despite more recent significant changes in the field. A performance benchmark or a capability comparison with [1] or similar frameworks would provide better insight to the readers. Lastly, [2] and [3] discuss many of the latest developments in this field.

This is a timely area that has attracted significant attention from the research community. Even though the paper gives a detailed description of the system, it lacks experimental results. More examples of how Webinos can be used might help the reader, and would attract more interest in the system.