26 min listen
Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea - #300
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea - #300
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
ratings:
Length:
30 minutes
Released:
Sep 18, 2019
Format:
Podcast episode
Description
Today we're joined by Kalai Ramea, Data Scientist at PARC, a Xerox Company. With a background in transportation, energy efficiency, art, and machine learning, Kalai has been fortunate enough to follow her passions through her work. In this episode we discuss: Her environmentally efficient pursuit that lead to the purchase of a hydrogen car, and the subsequent journey and paper that followed assessing fueling stations Kalai’s next paper, looking at fuel consumption at hydrogen stations using temporal clustering to identify signatures of usage over time, grouping the stations into categories With the construction of fueling stations is planned to increase dramatically in the next 5 years, building reliability on their performance is crucial A sneak peek into how Kalai incorporates her love of art into her work! Check out the show notes, and the refresh, at twimlai.com!
Released:
Sep 18, 2019
Format:
Podcast episode
Titles in the series (100)
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