AI Enabled SDG Tracker to Enhance Automotive Business Strategies

The Sustainable Development Goals (SDGs) established by the United Nations serve as a global framework for fostering sustainable industrial growth. In the automotive sector, aligning business strategies with SDGs is critical for ensuring environmental sustainability, economic efficiency, and social responsibility. This paper presents an AI-driven SDG Tracker designed to evaluate and enhance sustainable business practices in the automotive industry. By leveraging text analysis techniques (NLP), predictive analytics, and statistical modeling models, the system enables organizations to monitor their sustainability efforts, optimize resource utilization, and align with regulatory frameworks. The SDG Tracker focuses on SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action), assessing key performance indicators (KPIs) such as carbon emissions, waste management efficiency, renewable energy usage, and ethical labor practices. A key feature of the SDG Tracker is its integration with an offline automated chatbot, developed using the Ollama framework, allowing users to access compliance reports and recommendations without an internet connection. The chatbot incorporates fine-tuned NLP models, ensuring contextual understanding and accurate guidance, while techniques like the Synthetic Minority Oversampling Technique (SMOTE) enhance data representation, improving model robustness. By implementing this AI-driven SDG Tracker, automotive businesses can make informed decisions, enhance their sustainability reputation, and contribute to global environmental and ethical standards.