# Use of Wireless Sensor Networks for Area-Based Speed Control and Traffic Monitoring
## 7 Conclusions  
Vehicle traffic monitoring systems, particularly those related to traffic volume and speed control, will remain essential components of road traffic management, road safety improvement, and tools for reducing the risk of traffic accidents for a long time. Therefore, the search for new technological and system solutions that enhance the effectiveness of monitoring and controlling vehicle speed is both justified and desirable. One such technology is a low-energy LoRaWAN sensor network, which can facilitate the creation of a system for traffic volume monitoring and area-based speed control. The key to the smooth, reliable, and efficient operation of such a system is adequate radio coverage of the controlled area. By analyzing the results obtained, it can be concluded that the practical implementation of an area-based vehicle speed control system using LoRaWAN technology is feasible. In a specific radio system, the primary factors influencing the achieved radio coverage are the height of the transmitting and receiving antennas, the radiation characteristics, and the gain of the transmitting antenna. However, it is important to remember that in practice, the heights of antenna installations will be limited by several constraints, both technical and economic. The power of the transmitted signal from the transmitting station is also subject to legal and technical limitations. Regardless of the adopted limit value of the receiving signal, given the parameters and locations of the transmitting stations, full radio coverage of the given area and its main road system is not achieved in the analyzed model. Coverage gaps occur primarily in the northern and northwestern parts of the area, mainly due to the remoteness of the transmitting stations and significant forest cover in these regions. However, these areas are also characterized by roads with much lower traffic volumes and poorer quality road surfaces. Therefore, a road network coverage of more than 80% of the area can be considered satisfactory. Nevertheless, this coverage value is likely to change, and possibly decrease, as the diversity of the terrain and the height and density of buildings increase. Consequently, it should not be expected that the required number of transmitting stations  
Figure 12: Area radio coverage with a signal exceeding the preset value. can be determined solely from a basic relationship relating only to a one-dimensional space. Thus, radio coverage planning should become a fundamental element of traffic monitoring systems and the design of area-based vehicle speed control solutions. The authors intend to continue research on the presented concept of monitoring and controlling vehicle speed. They plan to carry out field tests to compare the actual measurement results with the simulation test results. The next steps include deploying network devices in the presented area, with the ultimate goal of implementing the proposed solution in practice within that area. As an additional measure, the plan is to extend LoRaWAN devices by integrating renewable energy technology. This is intended to simplify the deployment of terminal devices in the field. Additionally, the possibility of integrating the proposed solution with Police Management Systems will be explored. A change in the procedures for directing police patrols for speed control has been adopted as an organizational objective. The proposal is to modify the selection of speed control sites, focusing only on areas where there is currently the highest road safety risk. The positive results of the research and the implementation of area-based vehicle speed control have broader implications. Not only will this contribute to increasing road safety, which is the primary objective of the ongoing research, but it will also provide real-time, comprehensive, and significantly more detailed traffic volume data compared to spot measurements. This will enhance the accuracy of tracking changes in vehicle traffic flows and improve the precision of traffic models.