# Integration of Autonomous Wireless Sensor Networks in Academic School Gardens
## 1 Introduction  
Wireless Sensor Networks are being actively adopted as enablers for context aware communication capabilities within multiple scenarios, such as Smart Cities and Smart Regions [1, 2]. Within Smart City/Region concept, developments in the management of healthcare systems, water resources and waste, energy and transportation systems have been published in recent years [3, 4, 5, 6, 7]. Among these, agricultural management is gaining relevance since it concerns a fundamental aspect of human survival: feeding. As in the other mentioned cases, information and communication technologieshave also been adopted in order to improve multiple aspects of agriculture [8]. In this context, WSNs play a key role, given to the fact that they constitute inherent distributed systems, in which current platforms allow the inclusion of multiple analogue/digital input/output ports. Furthermore, the use of wireless communication systems enables ubiquity as well as ease of deployment. Multiple challenges must also be handled, such as compact form factors, reduced energy consumption, interference handling and variable node density allocation. In this sense, HetNet solutions as well as incumbent 5G systems provide user access/interference control mechanisms, which rely on radio propagation characteristics in site-specific fashion, such as Self Optimizing Networks, Cloud RAN or Cooperative MAC schemes [9]. Adequate network operation and design require wireless channel analysis and optimization in order to minimize interference, energy consumption and enhance overall quality of service. This is of particular interest in the case of wireless sensor networks, given inherent restrictions in their operating conditions, as well as in the potentially large number of nodes present in the network. All these advancements lead to the so-called Precision Agriculture and Smart Agriculture, where the information gathered by sensors (such as environmental parameters [10] or chemical component and soil water detection [11]) provide support to decision systems [12], facilitating the adoption of measures in order to optimize resources such as water or fertilizers [13; 14; 15; 16], control and manage plant growth [17], as well as to detect, prevent and treat diseases [18; 19]. One of the main advantages that this kind of systems can provide is the possibility to control and act from a location far away from the crops. This is feasible by means of IoT systems, which send to a Cloud (through a gateway) the information gathered by the WSN deployed on the crops [20]. Thus, the information can be stored and managed from any device connected to the Internet. In fact, there are a few works which present Cloud-based solutions for agricultural environment applications [21], a FIWARE-Based IoT platform for Precision Agriculture [22] and for hydroponic precision farming [23]. At this point, it is worth noting that commercial Smart Agriculture solutions are already in the market [24]. Regarding the communication between these devices, in most of the cases wireless technologies to deploy WSNs and IoT-based systems for Precision Agriculture and Smart Agriculture are used [25], such as Bluetooth [26] or GSM and Infrared communications [27]. But due to its ideal characteristics to deploy WSNs (low power consumption, low cost and high number of devices allowed per network), ZigBee is the most employed wireless technology [28; 29; 30; 31; 32; 33], where transceivers are mounted and controlled by Arduino and Raspberry Pi boards in most cases. Even for precision agriculture based on mobile UAVs (Unmanned Aerial Vehicles) communicating with ground sensors, ZigBee has been used [34]. In this context, this work presents an educational application based on the combination of the capabilities provided by WSNs with parameter observation in a school garden in order to enhance the outcomes within the learning process of students in primary school.