## 2 Related Research and Motivational Challenges  
Bearing in mind that the work introduced in this article is focusing on the adoption of context awareness as well as in the collaboration of some specific technologies employed for Agriculture 4.0 (remote sensing, cloud computing, IoT), it was considered appropriate to look into the related recent research (published in the present decade) referring as much as possible to PF applications. The state of the art finally presented reflects the results of a thorough literature review, performed according to the methodology introduced by [PERSON] and [PERSON] [34] as it is considered to be quite efficient for locating related research sources that fulfil strict qualitative criteria [35]. As a consequence, a holistic review of the latest literature in the area of context awareness indicates that several middleware-centric schemes for wireless sensory applications in various sectors are offered, such as Gaia [51], PRISMA [52], Aura [53], CORTEX [54], MobiPADS [55], MiddleWhere [56], CORTEN [57], SOCAM [58] and CARMEN [59]. Although these works are assumed to be largely outdated as they were presented during the previous decade and do not entirely adjust to the current trends of technology, certain elements presented in them have been elaborated and involved in some recent works. The most representative works, found in the literature of the present decade, concerning context-aware middleware frameworks for wireless sensing and data acquisition, are set forth below:  
* ACoMS+ presented by [PERSON] et al. as in [60], is a framework according to which resource efficiency and context-aware management functionality of sensing infrastructures are achieved by embedding sensor networks middleware to the middleware for context-aware applications. * FlexRFID suggested by [PERSON] et al. as in [61] is a middleware solution capable of managing large amounts of Radio Frequency Identification (RFID) and sensor scanned data as well as of executing applications' business rules in real time via a policy-based business rules layer for controlling all its services. Additionally, the middleware supports convenient addition and removal of all capturing data hardware devices. * SeCoMan, which is the abbreviated title for Semantic Web-based Context Management, was presented by [PERSON] et al. as in [62] and refers to a context-aware framework that offers predefined queries for enabling the development of smart applications used to share information about indoor location of users as well as objects. * A middleware architecture framework was introduced by [PERSON] and [PERSON] as in [63], supporting automatic discovery and context integration based on Semantic Web services, to provide various context-aware services. * CA4 IoT project developed by [PERSON] et al. as in [64] attempts to enable the development of a sensing as a service platform through the integration of context awareness properties to IoT middleware solutions. However, the project does not provide a replete middleware solution for managing context data as it mainly concentrates on the notion of introducing a method for selecting the most suitable sensors for specific tasks. Even though these reviewed middleware solutions are functional, most of them are oriented toward specific applications, contributing fragmentarily to PF developments as they do not provide significant inferences related to the subject of this article. Actually, despite the fact that due to the diverse underlying challenges, there is a wide scope for research in the area of context-aware data or service management applications for PF, the solutions offered are rather limited and narrowed. Within this context, the work presented by [PERSON] and [PERSON] as in [65] deals with the issue of introducing and evaluating two approaches that incorporate context awareness, in order to define a strategy for acquiring wireless sensory data from an agricultural parcel with optimum energy preservation. A corresponding approach is found as in [66] wherein [PERSON] et al.