Hal Varian predicts that in the coming decades, "the ability to take data—tobe able to understand it, to analyse it, to extract value from it, to visualise it, to convey it—is going to be an enormously significant skill." This paper presents a novel approach for enhancing vehicle communication and conducting traffic analysis using LoRa (Long Range) technology. As the number of vehicles on the roads continues to grow, effective traffic management and real-time communication among vehicles become crucial for ensuring safety and optimizing traffic flow. The proposed system leverages the low-power, long-range capabilities of LoRa to establish a reliable and wide-reaching communication network for vehicles. The system architecture includes LoRa-enabled onboard units (OBUs) installed in vehicles, which enable data exchange among neighboring vehicles and road infrastructure. Additionally, LoRa gateways are deployed across key locations, facilitating the collection and aggregation of vehicle data. The LoRa-based communication network enables seamless communication, even in remote and challenging terrains.To analyze traffic patterns, the paper presents a robust data analytics framework that processes and interprets the data gathered from the LoRa-enabled OBUs. Various traffic parameters, such as vehicle density, speed, and congestion levels, are monitored and analyzed in real-time to provide valuable insights to traffic management authorities and drivers. Moreover, the proposed system offers predictive capabilities to anticipate potential traffic bottlenecks and optimize traffic signal timings, thereby reducing overall congestion and enhancing road safety.Overall, this paper presents a comprehensive solution for vehicle communication and traffic analysis, leveraging the advantages of LoRa technology. The proposed system has the potential to revolutionize modern transportation systems by enabling seamless communication and data-driven traffic management, contributing to safer and more efficient road networks.
Vehicle communication and Traffic analysis using LoRa Technology
2023-12-01
1347680 byte
Conference paper
Electronic Resource
English
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