## 2 Literature Review
Finally, in [37] a review of WSN-based agricultural applications was presented and a comparison was conducted among different wireless technologies or protocols, such as Wi-Fi, Bluetooth, ZigBee, GPRS/3G/4G, LoRa, and SigFox. None of these surveys considered the methods of energy efficiency of LoRa implementations in precision agriculture based on the amount of network traffic and the size of sent packets with regard to transmission rate, which is the subject of research in this article. The majority of the research conducted on LoRa and LoRaWAN has been focused on features such as coverage, range, network capacity, throughput, delay, scalability, and robustness, for instance in [25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42]. However, limited consideration of features suchas energy consumption has been given, unlike the considerations in this article. It is essential because many LoRa devices are not powered by the grid. Prompted by the challenges of energy consumption, some recent works have focused on the power dissipation of sensors within wireless sensor networks [15]. Although the analyses in the majority of the proposed papers suggested to estimate the amount of energy consumed by a sensor node, LoRa technology was not directly included in their energy models [43]. Thus, for instance, in [44], an energy model for ultra-low power consumption of sensor nodes was presented. However, the radio frequency module used in the study did not include LoRa technology. Another model of energy estimation was presented in [45] aimed to achieve low energy consumption of sensor nodes. In order to save energy, it was concluded that the microcontroller and the communication module must be idle as long as possible when they are not active. Although these papers provide useful results, LoRa technology was not considered in the performed analysis, as is the case in this article. Furthermore, some other studies which took LoRa communication into account did not study the optimization of the consumption of energy of LoRa sensor nodes. For instance, in [46], a comparison of LoRaWAN classes was presented and their energy consumption models were proposed. Although the obtained results are based on real measurements, the paper did not study the effects of LoRa parameters such as communication range, coding speed, and transmission power level on the total energy consumed, which is the subject of research in this article. The analyses presented in [31] deal with this topic to a limited measure, providing only incomplete estimates on parameters related to LoRaWAN energy efficiency. However, they did not consider the practical behavior of the hardware of the LoRaWAN device, nor the effect of the main LoRaWAN mechanism settings and parameters, which is also the subject of research in this article. Moreover, only a few works provided data relevant to the current consumption of LoRa and LoRaWAN devices, obtained from a manual or by experimental measurements [31; 32; 33; 34; 36; 47]. Such details correspond to device states of sleep, transmission, as well as reception [47]. Although the developed models enable the characterization of lifetime and energy costs of LoRaWAN device, these models do not include, for instance, energy consumption used within the processing state of sensor units, which is also the subject of research in this article. In addition, based on the information relevant to transmit, receive, and sleep states of a LoRa/LoRaWAN device, a few analytical models of LoRa and LoRaWAN energy consumption have been published, for example, in [31; 36]. They include the lifetime of sensor nodes and the energy cost of data delivery. However, these models are also very basic since consideration needs to be given to several other states for a LoRa and LoRaWAN device that exist and are involved in communication. These include, for instance, a detailed calculation of time for message transmission, provided only in [48].