In the digital age, data is abundant, growing at an unprecedented rate. It is projected that by 2050, we will have 50,000 zettabytes of data, a thousandfold increase from 2020. To harness the potential of this vast information pool, users require efficient frameworks.
In this study, the Observatory streamlines analytics to find the most efficient locations for EV (electric vehicle) charging stations through its PinPoint tool. It is a resource for those looking to install new EV charging stations to assess, identify, and arbitrage the best locations for an efficient EV network. This exercise demonstrates how the PinPoint tool identifies the most efficient locations for EV charging stations in Barcelona.
Analysis
The process presented in this article serves anyone looking to install an EV charging station, from city councils who are working towards net zero emissions to any entity seeking to host a Tesla Motors supercharger.
The process leverages AI for data mining, efficiently processing the data through its algorithms to derive valuable and understandable insights. By interpolating various data sources such as the average income per neighborhood, land use, road categorization, population density, power excess, leisure areas, and others, the Observatory outputs a quantitative analysis of the ideal spots to install new EV charging stations, and identifies the existing EV chargers that would benefit from an upgrade.
This study presents unbiased results obtained through data interpolation. The analysis assists entities in identifying opportunities within EV industry. Participants conducting this study in their respective cities can present it to their city councils to obtain licenses for starting operations of their EV charging stations network.
In this particular case, the Observatory examines the most populated area of Barcelona. The results highlight the areas with demand for EV infrastructure and pin points the exact areas to install new EV infrastructure.
Why do we develop this?
Traditionally, geospatial analysis is a complex undertaking requiring expertise and data management from multiple sources. The Observatory simplifies this process by leveraging AI tools and open-source datasets within its platform. This simplification facilitates users in evaluating land value and development potential, thus democratizing and automating this process to a wider audience.
Note: This analysis is adjustable to various needs and applied to every city worldwide
This is a study performed by LAIA Observatory. We are building tools to democratize geospatial analysis. Register to the waitlist here:
