February 1, 2017 | Written by: Ed Cuoco
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In this blog series, business partners detail their experiences of the StormWave research project, which involved 23 students from Eindhoven University building an electric motorcycle (StormWave) to cover 40,000 kilometers in 80 days. Over the past few weeks, NXP shared their contribution to this promising IoT story, as well as KPN, TomTom, Itility and IBM. Today we conclude with The Weather Company, part of IBM and the world’s largest private weather enterprise, delivering on average more than 45 billion requests for weather information on a daily base.
The student teams’ return on November 2 heralds a new and significant phase in the STORM project, now the collected raw data is ready to be explored and analyzed. We get a preview from Ed Cuoco, director of data science at the business solutions division of The Weather Company, about his expectations of the results.
Ed received the first batch of data soon after the students’ return on November 2, and was impressed with its quality:
“We got hold of a tremendous amount of weather and battery data, which we can leverage to gain insights and start having informed conversations with various groups, such as utility companies, about battery efficiency for electrical driven cars and battery performance during complex, long-distance route transport. These are real conversations, because even minor changes in efficiency can have meaningful financial implications for such organizations.”
Correlations between weather and mechanics
The ability to combine practical weather conditions with variables like battery usage and efficiency are incredibly valuable to Ed:
“In the next few years we expect a big push in fields like ground transportation and efficient solutions to store energy, and this particular dataset speaks to all of that. The STORM data allow us to define a baseline dataset from which we can derive correlations, and consequently start having conversations about the relationships between weather, mechanics, chemistry and storage. Even if the outcomes tell us that road or battery conditions don’t have any impact to the battery, that’s still a really useful find.”
The Weather Company donated a personal weather station which enabled students to collect data in remote places that are usually difficult to access. Still, this is not what reflects the true value of their efforts according to Ed:
“The individual weather data from one motorcycle at one certain location is not that useful to us. Within this particular research area we tend to prefer a continuously streaming source of information, due to the sheer complexity of physics of weather and climate.” In Ed’s view there is a simple principle at stake here: you need a lot of data to tell you a lot about patterns over time. “More data is always interesting, especially experiments with different kinds of vehicles and distances. As a data scientist you prefer conditions in an experiment to be relatively similar to an earlier one, so you can analyze the deviations and draw a line between the two datasets.”
Big data: making the case for STORM
Therefore, Ed makes a case for similar initiatives like STORM:
“This project really corresponds with my belief that scientific projects garner the best results once they span a large period of time, let’s say at least a year, and are actually out there in the world. It forces you to collaborate in a meaningful way and build forth on other ideas, all in a very short time frame. Such a project may perhaps not be feasible for any academic or research team, but the more this happens the more useful these projects will prove to be in the long run. I’d regard it as a significant advantage for the students and their future employers that they participated in this project.”
The STORM World Tour began in the southern Netherlands city of Eindhoven, starting with a route that circumnavigated the northern hemisphere, leaving Europe via Central Asia and then crossing North America before they returned to Eindhoven again on November 2.
You can learn more about the STORM project via:
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