Brief Summary of the Project
Data Extraction and Analysis is a data-driven solution that leverages public APIs provided by electric vehicle (EV) original equipment manufacturers (OEMs) to collect, process, and analyze vehicle usage and charging data.
The project addresses the lack of actionable, fine-grained insights into EV driving behavior and charging patterns faced by energy providers and mobility service companies. While EV adoption is growing rapidly, many companies struggle to forecast energy demand accurately, design effective dynamic pricing models, and tailor services to different EV user profiles.
Our solution extracts anonymized EV data to identify driving profiles, charging habits, peak usage times, and location-based demand patterns. These insights enable companies such as Galp to optimize energy distribution, adapt dynamic tariffs, and create personalized EV-focused energy products.
The target audience includes energy providers, EV charging infrastructure operators, and smart mobility platforms. The expected outcome is improved energy demand forecasting, more efficient grid utilization, and enhanced customer engagement through customized energy offerings. A strong emphasis is placed on data security, privacy, and interoperability with home energy management systems to support a holistic smart mobility ecosystem.
Team Motivation
The team is motivated by the intersection of data science, energy systems, and sustainable mobility. With backgrounds in information systems and data analysis, we see a strong opportunity to apply analytical techniques to real-world challenges created by the rapid electrification of transport.
Participating in this initiative allows us to work on a realistic industry problem, collaborate across disciplines, and develop a solution with tangible commercial and societal impact. We are particularly interested in how data can bridge the gap between EV users and energy providers, enabling smarter decision-making and more efficient energy use.
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