AI-based Sustainable Vehicle Monitoring System for Existing Internal Combustion Vehicles
Keywords:
Self-serving data marts, AutoML, data governance, enterprise data warehousing, metadata management, AI-driven analytics, Social media, Natural Language Processing, Sentiment Analysis., computer-mediated communication, Federated data governance, anti-money laundering, cross-institution collaboration, data privacy, AI, virtual data warehousing, sustainability, vehicle retrofitting, OBD-II diagnostics, Internet of Things, Predictive Maintenance.Abstract
The transportation industry is a major contributor to carbon emissions, with internal combustion engines responsible for over 25% of the total. Despite advances and regulations encouraging the shift to electric vehicles, the transition from diesel engines remains slow, as expected. Many countries have heavily relied on diesel engines, which makes the switch to electric vehicles more difficult due to the higher costs of buying and replacing internal combustion engines with electric ones. Therefore, this report suggests a solution: retrofitting existing ICE vehicles with AI-powered sustainable vehicle monitoring systems. This upgrade involves installing sensors that work with OBD-II diagnostics to monitor emissions, fuel use, and driving habits in real time. Gathering this data aims to develop personalized, eco-friendly driving recommendations that help reduce overall emissions. This method provides a cost-effective, sustainable, and environmentally friendly alternative to high carbon emissions. It is also scalable, even in regions with limited financial resources.
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