AI-based Sustainable Vehicle Monitoring System for Existing Internal Combustion Vehicles (London Journal of Research In Computer Science and Technology, 2025)
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.
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.