Sustainable Freight Analytics: Capacity and Emissions Visualization using Python

Abstract

In the present day, people are relying on to proceed with their business based on accu-rate data. The mission of this Thesis has clear goal to prepare an authentic dashboard which can calculate minimum path using the most popular GoogleMaps to compare hu-man centric fetched data with the technology based accumulated data. Obviously, tech-nology helps us to make our process easy to figure out the actual distances where mul-tiple emission factors help to determine the actual WTW emission in CO₂e Kg. The visu-alization of components inside maps clearcuts the authenticity of location with prime impact. The Live Calculation table works in parallel with the movement of the compo-nent in each leg. The calculation comes automatically after touching each leg with load and unload data. This thesis creates a detailed CO2 emission calculator in accordance with the requirements of ISO 14083 for refrigerated road transport. Propulsion fuel, TRU fuel consumption and refrigerant leakage are combined in single WTW model. An integrated time-based (L/h) and distance-based (L/100 km) TRU energy model is pro-posed, utilizing parameter sets (a, b), which are dependent on driving environments like town, city, mixed and linehaul operations. Refrigerant leakage losses are apportioned on annual basis to individual transport chain components based on distance-related ac-tivity shares following guidelines established by ISO, GLEC. The model also includes dy-namic vehicle weight, route-based division and average-speed class and TKM–special-ized assignment for consistent per-leg emissions.