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The implementation of weather data in logistics systems is a forward-looking topic that can significantly increase the efficiency and reliability of supply chains. In such a scenario, real-time weather data is integrated into the logistics management system to dynamically adjust transport routes, optimise shipping times and minimise risks such as delays or damage to goods. Using advanced algorithms and AI technologies, this weather data is analysed and transformed into meaningful insights that help decision makers take proactive measures. For example, if a storm is approaching, the intended route for a truck can be changed to avoid dangerous conditions. Or in extreme temperatures, temperature-sensitive goods could be shipped in specially insulated containers. In addition, fuel and labour costs can be reduced by optimising routes and schedules. However, integrating such weather data is not trivial and poses challenges for companies such as data acquisition, consistency of data quality and integration into existing systems. Data protection and cybersecurity issues must also be considered to ensure the integrity of the system. Nevertheless, the benefits outweigh the difficulties and the implementation of weather data in logistics systems is expected to become increasingly important in the coming years. Not only does it offer economic benefits, but it can also help to increase safety and reduce environmental impact, for example by avoiding unnecessary journeys.