# Internet of Everything (IoE) Taxonomies: A Survey and a Novel Knowledge-Based Taxonomy
## 1 Introduction  
The Internet of everything (IoE) is a term that was first defined by CISCO in 2012 [1] as a network of networks that reunites people, processes, data, and things in network connections more significant and valuable than ever [2; 3; 4]. While the Internet of things (IoT) is a dynamic global network infrastructure [5] concerned about things (i.e., physical devices, accessed through the Internet), IoE laws an upper foundation over IoT and is concerned with intelligent network connections and technologies [6; 7; 8; 9]. IoE supports creating new capacities, better-off competencies, and outstanding economic opportunities for businesses and society [1]. For [PERSON] and [PERSON] [10], IoE expands on the IoT concept by connecting devices and people in one network. Beyond the concept of IoT, the IoE paradigm covers a wide range of Internet-based concepts; for example, the Internet of people (IoP), which considers social networks and connections among people; and the industrial Internet (II), which is focused on data of interest to industry [7]. The concept of IoE incorporates nanosensors in diverse objects using nano-networks. It provides access to data that had previously been impossible to sense. This technology transition involving IoE is a concept called the Internet of Nano things [11]. With more relevant connections than machine-to-machine communications, IoE has enabled the global democratization of skills, including person-to-machine and person-to-person connections [12; 13]. Accordingly, [PERSON] et al. [4] argue that IoE extends the concept of IoT by exceeding the connections of things and integrating common impacts, risks, and economic benefits for the novel interconnected society. Thus, \"intelligent services\", together with the \"things\", represent the \"everything\" in IoE [14]. For [PERSON] and [PERSON] [13], IoE is a superset of IoT and requires advanced capabilities within the area of information sharing. The IoE paradigm can extract and analyze real-time data collected from diverse and heterogeneous IoE environments, from simple sensors and actuators to complex robotic devices, and from autonomous service agents to human actors [3]. Thus, IoE applications require appropriate measures to be taken in the initial phases of their design and implementation [13]. Artificial intelligence (AI) integrated into smart devices provides the increasing deployment of innovative and useful IoE-based applications, where people and things interact appropriately within a social context and multi-user environment [11]. Processes are the core of IoE; they represent network \"connections\" and real-time data/information flows [15] among IoE nodes [16]. The result is smartness and intelligence [17], and real-time insights working in concert [18], far beyond IoT context disruptions [19], addressing the societal and organizational needs for more data and more actionable intelligence. Actions and interactions within the IoE environment create and expand knowledge in a transcending process through which entities (people, things, and data) acquire new knowledge and new interactions are created in knowledge-creation cycles [20]. This transformation from data to knowledge in IoE provides essential insights and various possible applications [21; 22]. Value-generating activities come through knowledge processes that filter data, information, and knowledge into a decision context, in which it becomes actionable intelligence [23]. A knowledge-based strategy for selecting and managing technologies and decision support artifacts (big data, data, information, knowledge, and intelligence) assists in the management and governance of data and technologies to ensure great benefit from IoE's capacity to provide enhanced intelligent services. Figure 1 shows the \"four enablers\" (people, data, processes, and things) in IoE. Several taxonomies for IoT [24; 25; 26; 27; 28; 29; 30] and IoE [17; 31; 6; 13; 32], have been proposed.