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In this article, we reflect on Artificial Intelligence (AI) and its cognitive domain, Machine Learning (ML), and how these technologies may be the future for controlling greenhouse gas emission levels in the transport and logistics sector.
In recent years, greenhouse gas (GHG) emissions and their negative impacts on the global climate have been often debated. Fortunately, tangible steps have been taken to reduce these emissions, as shown by the German Climate Action Plan 2050 and the European Green Deal. In addition, global corporate endeavors like the Carbon Disclosure Project (CDP), which helps companies and cities disclose their environmental impact, and other science-based initiatives have also been implemented to reduce companies' carbon emissions.
Along with these government and corporate initiatives, Artificial Intelligence (AI) and its cognitive domain, Machine Learning (ML), are also increasingly used to mitigate climate change and are driving the future of GHG emission levels for private individuals and organizations. As for the transport and logistics sector, we believe ML tools can also be particularly helpful in making data-driven decisions regarding carbon emissions.
Over time, using Artificial Intelligence and Machine Learning in the transport and logistics sector has successfully tackled carbon emissions. Here are some examples: