# Low-Cost Sensor Based on SDR Platforms for TETRA Signals Monitoring
## 2 Material and Methods
### Sensor Testing Methodology in the Real Environment  
The design and implementation of the sensor were based of the assumption of achieving a low-cost sensor with a high degree of portability, to be simply used for outdoor measurements. The size, weight and power are important requirements. The sensor's control was achieved in two variants: (a) with a laptop; (b) with a Raspberry Pi device. The small single-board computer had the following characteristics: Processor: Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5 GHz; RAM: 4 GB LPDDR4-3200 SDRAM; Connectivity: 2.4 GHz and 5.0 GHz IEEE 802.11 ac wireless, Bluetooth 5.0, BLE, Gigabit Ethernet; Power supply: 5 V DC via USB-C connector (minimum 3 A). To meet the mobility conditions and to ensure the local control interface of the Raspberry computer, it was equipped with a high-performance display model HyperPixel 4.0. The protection of the components of the Raspberry device was provided by preparing a 3D printed resin housing (short curing time, high level of details with firm edges and smooth surfaces). The housing has a system of holes that allow optimal operation of the fan by passing the air flow to the outside. Figure 9 shows the portable sensor with all its components. The approximate cost of such a sensor is EUR 320 (ADALM Pluto SDR platform: approx. EUR 130; HiperPixel 4.0 touch display: approx. EUR 40; Raspberry Pi: approx. EUR 50; Cooling fan: approx. EUR 10; Housing: approx. EUR 10; Motorola GMAE4256 magnetic antenna: EUR 45; GN-803G USB GNSS GPS GLONASS Receiver:A virtual private network (VPN) was implemented for remote sensor management. The network architecture is shown in Figure 10. The VPN server was deployed on a Raspberry Pi 3B+ computer, using the open source OpenVPN solution. The sensors were configured to automatically connect to the VPN when they start, when there is an Internet connection available. This creates a private virtual network that works regardless of how customers (sensors) are connect to the Internet. The system administrator thus has direct access to the sensors regardless of how they connect to the Internet. They can establish Secure Socket Shell (SSH) connections to configure the operating system, or can view and operate directly in the graphical interface of the sensors using the graphical desktop interface sharing system, Virtual Network Computing (VNC). The Internet connection of the sensors is made through Wi-Fi access points, in the 2.4 or 5 GHz bands, with the communication infrastructure being provided by both mobile data service providers and data service providers through wired networks (in the case of sensors located in fixed locations). The files resulting from the measurements and deposited in the storage memory of each sensor are automatically synchronized on the File Transfer Protocol (FTP) server, at programmable time intervals, using the rsync utility. This has the advantage of greatly reducing data traffic in the network as the synchronization of files is carried out by checking the time of files' modifications and their sizes, with the data transmission taking place only if necessary. Figure 10: Network architecture for the remote management of the sensors. Figure 9: Portable sensor elements controlled with the Raspberry Pi. In order to process the data recorded by the field sensors, a software application has been written. It allows different analyses--for example, the representation of the electromagnetic field level measured by a particular sensor on the map, on any of the 200 TETRA channels. The field testing (in situ) of the sensor took into account not only the static sensor, but also the moving one. Therefore, its placement on a vehicle was considered, while data collection through the private remote management network and the subsequent analysis of the results were enabled. The itineraries of the vehicle carrying the sensor were chosen so as to allow a constant travel speed.