Everything is Alive (EiA) is described by the authors of this paper as an ambitious vision and architecture for a future where smart real-world objects dynamically discover and interact with other real or virtual objects, humans or virtual human avatars, and the rest of the real-world environment. The authors state that this future “ubiquitous intelligence” will transform the real world “into a smart semantic world where intelligent objects harmoniously coordinate with each other by utilizing omnipresent sensors.”
The paper describes how their EiA framework aims to collect knowledge through key concepts they call (1) ubiquitous intelligence, (2) cyber-individual, and (3) brain informatics. These interact and enable a multiple-tiered and complex data cycle that satisfies their Wisdom Web of Things (W2T). By abstracting and modeling real-world objects, 3D simulations and other virtual avatar-like interactions are made more transparent. For example, the first data layer involves using real-world sensors to collect raw data, including that from radio frequency identification (RFID) tagged objects. A process of cleaning, integration, and storage then converts the data into information. Other phases describe moving through knowledge and wisdom, while including greater correlations with cloud, social, and other semantic networked information.
The paper concludes with two detailed case studies. One defines a robot housekeeper developed with a smartphone and the Android development kit. After a virtual world is created, they test in the real world, where a robot roams around to detect new smart objects. They also show how remote monitoring and control of a smart house would be possible. They rely on objects discovering other object application programming interfaces (APIs) and then manipulating their services based on shared “goals.” Although not implemented, the authors also mention the future need for providing security while respecting privacy aspects.
The EiA architecture has a notable goal, where all objects are represented by smart interacting agents, some even representing “brain informatics,” which are the actual mechanisms used by humans. Unfortunately, this unrealistically broad
scope and the lack of a related research section don’t help the reader grasp the actual research contributions. Hopefully, these issues will be clarified in future research reports.