Jan 23, 2025
Using AI in the Mobility Industry to Track Emissions
Tawanda Bwerudza
CEO and Founder
Introduction
As the world accelerates efforts to combat climate change, the mobility industry plays a critical role in reducing carbon footprints. According to the Intergovernmental Panel on Climate Change (IPCC), the mobility sector directly emitted approximately 8.9 gigatonnes of CO₂ equivalent in 2019, accounting for about 15% of total greenhouse gas emissions and roughly 23% of global energy-related CO₂ emissions.
Similarly, data from the International Energy Agency (IEA) indicates that transport accounts for around 24% of global CO₂ emissions from energy.
Innovative solutions are needed to monitor and mitigate environmental impacts. Artificial Intelligence (AI) is emerging as a game-changer, enabling real-time emissions tracking, predictive analytics, and smarter decision-making.
The Role of AI in Emissions Tracking
AI-powered systems leverage vast amounts of data from IoT (Internet Of Things) sensors, GPS devices, satellite imagery, and on-board diagnostics (OBD) systems to track emissions at an unprecedented level of detail.
These technologies offer:
Real-Time Monitoring: AI processes data from vehicles, fleet managementsystems, and environmental sensors to calculate emissions on a granular level.
Predictive Analytics: Machine learning models analyze driving patterns,fuel consumption, and route efficiency to forecast emissions and suggest greener alternatives.
Automated Reporting & Compliance: AI streamlines compliance withenvironmental regulations by generating automated reports and alerts,reducing the burden on mobility companies.
AI-Powered Solutions in the Mobility Industry
Several AI-driven innovations are transforming emission tracking and Management:
Smart Fleet Management - AI analyses fleet data to optimize routes, reduce idling time, and recommend eco-friendly driving behaviours. Predictive maintenance detects engine, Batteries and Motors’ inefficiencies and prevents excessive emissions before breakdowns occur.
EV & Hybrid Vehicle Optimization - AI-powered battery management systems extend battery life and improve energy efficiency in electric and hybrid vehicles. Smart charging algorithms help optimize charging schedules to reduce reliance on high-carbon energy sources.
AI-Based Carbon Footprint Calculators - Mobile applications and enterprise platforms use AI to estimate emissions based on travel patterns and fuel usage, allowing businesses and individuals to track their impact.
Traffic & Urban Planning - AI-driven simulations help city planners design sustainable traffic flows, reducing congestion and lowering transportation emissions. Integration with smart traffic lights and vehicle-to-infrastructure (V2I)communication enhances fuel efficiency across urban mobility networks.
Challenges & Future Prospects
Despite its promise, AI-driven emissions tracking faces challenges, including:
Data Privacy & Security: With large-scale data collection, protecting user privacy and securing information against cyber threats is crucial.
Integration with Legacy Systems: Many transportation companies still operate on outdated infrastructure, making AI adoption complex and costly.
Regulatory Hurdles: Standardizing AI-powered emissions tracking and aligning with global environmental policies requires ongoing collaboration.
Looking ahead, advancements in AI, edge computing, and blockchain technology will further enhance emissions tracking, ensuring transparency and accountability in the mobility sector.
Conclusion
AI is revolutionizing emissions tracking in the mobility industry, empowering businesses, governments, and individuals to make data-driven decisions for a sustainable future. By leveraging AI’s capabilities, the industry can take a significant step toward achieving net-zero emissions and combating climate change. Tracking emissions with AI provides crucial data that can drive decarbonization efforts in several ways. By analyzing real-time emissions data, AI can identify inefficiencies in mobility networks, such as underutilized freight routes, excessive idling, or suboptimal driving behaviours. This insight allows companies and policymakers to optimize routes, improve fuel efficiency, and shift to lower-carbon alternatives like electric or hydrogen-powered transport. As AI continues to evolve, its role in sustainable mobility will become even more critical—driving efficiency, reducing emissions, and fostering a cleaner, greener planet.