## 2 Related Works
According to the obtained results, the performance of LoRa transmission (i.e., the percentage of successfully received packets and the RSSI of received packets) was fairly variable when the distance and the number of LoRa devices were scaled. It was also shown that direct line of sight (LOS) strongly influences the performance of LoRa connectivity. When there were too many obstacles, the LoRa gateway stopped receiving packets. The best distance reached in experiments was about 890 m.  
[PERSON] et al. experimentally explored the coverage and performance of LoRa technology for tracking a fleet of vehicles in the context of smart cities [26]. The authors stated that the success of the vehicle tracking application depends directly on its ability to send the coordinates to the Internet, even when obstacles (i.e., trees, elevated buildings, flatlands, valleys) are in their way. They also expressed that the obstacles attenuate the signal propagation, and reduce communication range. Beyond that, they also reported that the irregular terrain profile could even interrupt communication. The physical layer of LoRa technology can be up to 5 km in urban areas due to its robustness against a high degree of interference, multi-path fading, and Doppler effects. The experimental tests were realized using commercial, assembled, and programmed LoRaWAN tracker devices. A LoRa gateway with a Semtech SX1301 chip was placed on the rooftop of a building on the university campus. Both RSSI and SNR values were measured by the gateway and recorded to evaluate the influence of different vehicle speeds. The obtained results showed that the minimum radius of the gateway was 2.5 km. Additionally, limited research studies carried out geolocation tracking with NB-IoT technology. At this point, it should be highlighted that the NB-IoT was initially used for stationary devices due to the lack of 'handover' support mechanisms in 3 GPP Release 13. In mobile networks, handover refers to a procedure of transferring an ongoing session of a mobile terminal when it moves away from one coverage to another. Due to no handover ability, LTE Cat NB1 mobile devices must re-register to the network whenever they move to a new cell. Therefore, they consume extra power, and intermittent disconnects frequently happen. Furthermore, the cell reselection procedure is initiated only after the mobile device has been completely disconnected from the last cell location. However, with the 3 GPP Release 14, the enhanced NB-IoT specifications bring connection re-establishment to LTE Cat NB2 devices, allowing them to move from one BS to another without renegotiating a new connection through the 'handover' mechanism [27]. [PERSON] et al. designed and implemented the LPWAN-based On-Board Unit (OBU) for personal mobility devices [28]. Unlike their previous study, the authors aimed to analyze the performance of NB-IoT technology. The designed OBU hardware was composed of two mainboards. The first board includes the CPU and memory using a small-scale computer, Raspberry Pi Zero W. The second board integrates the Lantronix A2235-H GPS receiver, the Murata CMWX1 ZZABZ-093 LoRaWAN transceiver, and the Quetel BC95-G modem. The OBU was attached to an e-scooter driven between 10 and 20 km/h around the campus in the experimental study. Compared to the results of the previous work [24], the obtained results verified that the NB-IoT technology scales worsen with each base station and consume more energy but that they offer a clear advantage regarding service quality. The main contribution of this study is introducing a theoretical approach to evaluate the transmission limits of LoRa and NB-IoT technologies for rural, suburban, and urban areas. In the considered agricultural vehicle tracking application, the LoRa and NB-IoT technologies enable transmitting GPS data at a long distance. Since the travel distance of agricultural vehicles is limited on the small- and medium-scale farmlands, the handover problem will not happen for geolocation tracking.