Real-Time Carbon Footprint Tracking in Urban Transport Networks

The urban transportation systems produce a lot of carbon emissions. Still, most of the carbon monitoring systems that are in use are based on latent data and aggregated data, or at worst, on biological data that is not dynamic as far as the case of a real-time scenario of emission is concerned. This time lag limits the ability of commuters, urban designers, and policymakers to make informed, timely decisions to reduce environmental impacts. The lack of local visibility into real-time emissions also constrains the move to climate-sensitive mobility in cities and to carbon responsibility. This paper describes the Real-Time Urban Carbon Emissions Fusion Platform (R-UCEFP) as a scalable yet innovative data processing platform capable of providing carbon footprint data at the street or route level to bridge this deadly data gap. R-UCEFP will combine sensor data from various sources, e.g., vehicle and on-board emission sensors, social transportation IoT feeds, ambient environmental sensors, and traffic flow analytics. The system's emissions feedback is high-resolution and real-time. It is provided through advanced machine learning and data fusion techniques (spatiotemporal), accessible to both end-users and municipal systems. The model in question enables connecting to the created smart city infrastructure and mobility-as-a-service (MaaS) providers without issues. R-UCEFP will offer commuters guidance on the eco-routing decisions to take and a heatmap of emissions, so urban planners can optimise policy and create infrastructure built in real time. This Better Paper provides details on how the system was designed, its modular ability to ingest data, trained fusion layers, and visualisation capabilities. Preliminarily, the platform's applicability with respect to its open-world implementation has been demonstrated through tests in a simulated urban testbed, assessing its feasibility, accuracy, and potential. The article adds to the operationalisation of real-time city carbon responsibility, thereby establishing additional green, intelligent and receptive urban transportation systems.

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