Climate change and environmental concerns have brought significant attention to the reduction of carbon dioxide (CO2) emissions This is true particularly in the automotive sector where CO2 emissions is a major contributor to the global Climate Change crisis. As governments and organizations seek to reduce their carbon footprint, accurate prediction of CO2 emissions by vehicles has become essential for implementing effective mitigation strategies which starts with proper measurements/predictions. In this case study our MinskyTM, AI engine was used to predict CO2 emissions from vehicles helping in the development of sustainable transportation solutions. To address this issue, there is a growing need for predictive analytical models that can estimate CO2 emissions based on various vehicle characteristics and usage data. The goal of this case study is to leverage Minsky's AI capabilities to build a predictive model that accurately estimate CO2 emissions from different types of vehicles.
After a comprehensive evaluation of the data, Ai labs used AI capabilities of Minsky to accurately build predictive model the historical data which comprised of attributes such as Make, Model, Vehicle class, Engine Size, Fuel Consumption, Fuel type, Cylinders etc. Our objective is to develop a robust predictive model that precisely estimates CO2 emissions, relying on diverse vehicle characteristics and usage data. This AI-driven solution promises to provide accurate emissions estimates for various types of vehicles, aiding in the industry's ongoing efforts to combat environmental challenges and promote sustainable transportation practices.