# Internet of Everything (IoE) Taxonomies: A Survey and a Novel Knowledge-Based Taxonomy
## 6 Results
### Validation of Proposed IoE Taxonomy in Distinct Domains
The transformations or automation provided by these applications consist of conversions of tacit-explicit-implicit knowledge when people, things, and data are connected in the IoE environment to provide relevant services and collective intelligence. Table 3 classifies these 11 applications using the proposed IoE taxonomy. The full results and details are available in [136]. Regarding IoE applications that benefit from data analytics, we selected 30 applications in [PERSON] et al. [114], which analyzed (for the 2011-2017 period) the top five application domains: health, living, environment, industry, and transport. We categorized the selected applications (from distinct domains and with diverse analytical capabilities) in order to validate the IoE taxonomy, as presented in [136]. As a sample for application of the proposed IoE taxonomy, Table 3 shows the categorization of 5 applications that were selected from [PERSON] et al. [114] (smart clothing monitoring [148], travel routing [149], chemical process monitoring [150], smart farming [151], and on-shelf availability [152]). We prioritized applications with descriptive capabilities, which are the primary source of knowledge creation. The five applications consist of knowledge sharing between sensors' explicit knowledge, tacit human knowledge, and implicit knowledge in systems. Smart clothing monitoring [148] is a monitoring system improved with a machine-learning algorithm for diagnostic and predictive analytics of patients' health conditions. Travel routing [149] suggests the best travel routes, using analytical techniques for traffic flow prediction in order to predict future traffic flow. Chemical process monitoring [150] uses predictions to provide quality monitoring and enhanced control systems in plants to automatically react and prescribe process improvements \"to prevent off-grade products\". Smart farming [151] applications discover relevant events on semantically enriched data streams from sensors related to two smart farming scenarios. Moreover, on-shelf availability [152] is a system that improves shoppers' experiences, forecasts demand and provides insights on buyers' behavior. [PERSON] et al. [114] emphasized similarities between knowledge hierarchy, which transforms data to wisdom with analytical capabilities of IoE applications. Their study formed a comprehensive hierarchical classification of analytic capabilities (descriptive, diagnostic, discovery, predictive, and prescriptive), where each level of the hierarchy lies in the previous tier and relates to a corresponding level of data-to-knowledge-wisdom hierarchy approach. However, the study neglected the characteristics of knowledge processes and combination of tacit (from humans), explicit (sensed data), and implicit (analytics) knowledge, which we consider to be the great impact for knowledge created from analytics capabilities and value creation from intelligent services. We addressed this understanding in the proposed knowledge-based IoE taxonomy, which characterizes knowledge sources in terms of the smart services they provide, their characteristics, and how they interact to provide foresight: real-time data (explicit knowledge) combines with models from learning systems (implicit knowledge) to recommend action (integrating tacit knowledge from human sensors). Additionally, we used the proposed IoE taxonomy to understand nine domains of cyber-physical systems (CPS) [135]; the full results and details are available in a dataset within a technical report [136]. In Table 3, we validated the IoE taxonomy in terms of the main characteristics of CPS applications [135]. CPS applications incorporate physical processes, highly networked computers, machines, and robots to interact with the physical world in an extremely integrated and technical environment. They have a vital impact on older people's daily lives, as well as on healthcare, agriculture, manufacturing, energy and critical infrastructures, logistics, transport, security, and safety.