## 3 LPWAN-Based Agricultural Vehicle Tracking  
The agricultural vehicle tracking application helps farmers to integrate vehicles and machinery into their existing smart farm management system. This capability allows them to decide on the proper and efficient use of resources in their farming activities. Beyond that, the farmers can deploy their vehicles and machinery in an optimized way. Therefore, it can be possible to provide cost-effective routing and mobility management. The performance and success of the vehicle tracking application tightly depends on the wireless connectivity involved in the smart farm infrastructure for data transmission. When considering the tracking of vehicles and machinery on large-scale agricultural fields, the use of LPWANs comes forward thanks to their advantageous features such as large coverage, energy efficiency, and low complexity. Therefore, LoRa and NB-IoT technologies were considered to enable the proposed IoV-based agricultural vehicle tracking application. The considered system model consists of agricultural vehicles and machinery that can be used to execute farming operations. As in a typical IoT deployment, the system architecture is separated into three layers, namely the field layer, the network layer, and the cloud layer. The field layer contains the agricultural vehicles and machinery inside and outside the farm. The network layer allows wireless connectivity through LoRa technology with proprietary (non-cellular) network implementation or NB-IoT technology with an existing cellular network of mobile operators. All collected data were aggregated by a LoRa gateway (GW) or an LTE base station (BS) and forwarded to the cloud server. Finally, the cloud layer is responsible for storing and processing the data by providing a reliable, accessible, and scalable environment. Figure 1 shows the overall model of the IoV-based agricultural vehicle tracking application. In the considered application, vehicle tracking is enabled based on GPS services. GPS is a satellite-based navigation technology which presents precise location information of tracked assets (e.g., machinery, vehicles) just in time. GPS satellites broadcast signals that contain the information required for localization. When a GPS receiver picks up broadcasted signals from at least four satellites, it determines the geographical location on the Earth's surface. Accordingly, the positioning data (geographic coordinate, speed, time, and velocity) can be calculated automatically [29]. Over the past decade, GPS-based applications have been largely used for precision farming activities, such as vehicle guidance, farm planning, field mapping, soil sampling, and crop scouting. GPS technology can also allow for labor tracking in large farmlands. All these applications represent a significant opportunity for farmers to be more productive and efficient in their farming businesses while simultaneously reducing environmental pollution [30; 31]. On the field layer, it is assumed that each agricultural vehicle is equipped with a vehicle tracking unit (VTU), which is a printed circuit board (PCB) that carries the global positioning system (GPS) receiver and radio-frequency (RF) transceiver as well as the microcontroller and necessary components. The GPS receiver acquires signals from satellites and determines the location, speed, and direction of vehicles and machinery. RF transceiver provides a wireless connection to a LoRa GW or an LTE BS, depending on the wireless connectivity employed for agricultural vehicle tracking. Therefore, the gathered information is transmitted to the cloud server as the agricultural vehicles/machinery move. Finally, the cloud server makes data analytics on collected location data and converts the valuable information into visuals (charts, graphs, and maps) that farmers can access at any remote location with an internet connection. LoRa and NB-IoT technologies were designed to improve dense IoT networks' coverage, energy efficiency, and scalability.