# Use of Wireless Sensor Networks for Area-Based Speed Control and Traffic Monitoring
## 4 LoRaWAN Area-Based Speed Control
### LoRaWAN Radio Interface  
In an attempt to address the aforementioned considerations, the authors proposed an area-based speed control system using LoRaWAN technology. The system architecture, illustrated in Figure 2, is based on the standard LoRaWAN system architecture shown in The system is designed to consist of a number of end nodes (ENs--sensors and speedometers) arranged along roads throughout the monitored area, measuring the speed of passing vehicles in real time. The data are sent via gateways (GWs) to a network server (NS), from where it is forwarded to an application server (AS) that runs core software. Additionally, the data are sent to a database (DB), from which it can be accessed by other application servers and services. In the initial phase of the research, off-the-shelf, outdoor-ready 24 GHz radar modules were used as EN terminal devices. These were connected via an RS485 link to commercially available LoRa terminals operating in the 868 MHz band. The entire setup was powered by 12 V batteries. Ultimately, the plan is to integrate the 24 GHz radar and LoRa transmission modules into a custom monolithic device. Additionally, it is envisioned that the device will be adapted to run on renewable energy sources, primarily solar power, but also wind energy.  
Data from the gateways to the network server are transmitted via a fixed cable link. Although data transmission over the GSM LTE network is possible, it is used as a backup solution to enhance system reliability. The use of the GSM LTE network incurs fixed subscription fees for SIM card maintenance, which are significantly higher when using telemetry cards than for private applications, making this a substantial obstacle. For the same reason, the EN end devices do not use the GSM LTE network at all in the proposed solution. In this case, the LoRa-based solution demonstrates a clear and distinct advantage.  
Data come from speed sensors as well as metadata on the current network transmission parameters. Processed and visualized data are sent via the GSM LTE network to end users, both stationary (e.g., surveillance centers) and mobile (e.g., police patrols). Data visualization enables immediate traffic safety assessment relative to the current state of speed limit compliance and traffic volume. This makes it possible to dispatch a patrol car to conduct static speed checks at the specific location currently presenting the highest hazard to traffic safety. Mobile users are supported by a GPS location system, which requires nothing more than simple classic GPS receivers, as demonstrated in previous studies [59].  
It seems that with a sufficiently long system operation time and the collection of relevant data, it will be possible not only to monitor traffic in the classic way--traffic volume and vehicle speed--but also to use machine learning or even artificial intelligence  
Figure 1: Additional elements are included due to the system’s intended purpose and the extra functions and capabilities required.  
Figure 2: Architecture of the proposed solution. (Source: authors’ own image based on [51; 52; 53]).  
to predict traffic safety risks, as well as when and where the greatest risks are likely to occur. The validity of this thesis can be confirmed once field tests have been carried out and preliminary results collected.