## 3 Communication in IoT
### Edge Computing in Precision Farming  
IoT incorporation in precision farming has brought about changes in the communications of actuators and sensors with remote servers. With respect to networking technologies, modern IoT-capable nodes provide new energy-saving transceivers and network topologies that are tailored to field conditions where mobile and WiFi base stations are rare [191]. Multiple topologies that use wireless sensor networks can route data messages via communication nodes to reach a gateway with the internet connectivity, as shown in the proposal from [PERSON] and [PERSON] [192]. More recent developments with IoT involve network protocols to communicate through the internet with remote devices via applications designed for data reduction. For monitoring purposes, for example [191; 193; 194], researchers used the MQTT protocol for data collection from sensor nodes at greenhouses. These protocols allowed the gathering and analysis by [PERSON] et al. of data at intermediate cloud middleware [195]. A further expanded analysis of this topic can be found in the work of [PERSON] et al. [196]. A gateway using ZigBee collects data from a real deployment of sensors, which are then sent to a data cloud driven by FIWARE through web-based protocols. The work takes advantage of open interfaces to build a number of client applications that can access the cloud module. However, no IoT protocols are used, and only an early version of FIWARE is used. [PERSON] et al. [197] presented research on how to handle crops in PA environments using the cloud plane. The FIWARE core is used here, along with a collection of additional enablers, to communicate with IoT gateways through a variety of protocols, such as Message Queuing Telemetry Transport (MQTT) or Constrained Application Protocol (CoAP), where current and historical data are stored in the cloud for analytics. The output of FIWARE is assessed for PA using a collection of synthetic tests, but no real implementation of the proposal is provided. As per [PERSON] et al. [198], a refined optimization has to be made in FIWARE to get it implemented over fog computing domain. The incorporation of intermediate processing stages in the data path is an evolution of mainly cloud-based platforms. Before sending monitored data to the cloud, [PERSON] [199] performed local preprocessing at data collection gateways. [PERSON] et al. [200] expanded on this concept by evaluating a range of IoT protocols and technologies in a real hydroponic implementation to achieve effective computation-offloading. Moreover, a similar method for computation offloading was also implemented by [PERSON] et al. [201] in the domain of aeroponics. However, in these works, a lack of flexibility is noticeable in the way edge computing is implemented, and this layer is exclusively oriented to data fusion. [PERSON] et al. [202] proposed a hybridization of Artificial Intelligence (AI) with IoT in precision agriculture. However, it was found that there is still a big gap between AI and IoT due to computational resources. In this regard, they proposed an inclusion of Graphical Processing Unit (GPU) in the edge device to enhance the computational services [202]. For an efficient computation offloading, [PERSON] et al. [203] proposed ThriftyEdge which has the substantial potential to support computational intensive tasks by proper offloading across local device and edge cloud in proximity. ThriftyEdge is well suited to be deployed in ad hoc networks for precision agriculture [203]. The IoT-based generic monitoring system was defined by [PERSON] et al. [204]. It was deployed and validated on floriculture domain, with a setup of monitoring weather and soil conditions. Strategically, the goal was to foresee such diseases which could impede plantations proactively. For example, bacterial leaf spots, damp-off root rots, soft rots, and bacterial spots are among such diseases. HPE's overall architecture is cloud-centric and uses an edge computer node to gather information from the distributed sensor network.