cityofaustin / hack-the-traffic Goto Github PK
View Code? Open in Web Editor NEWA Transportation-Themed Hackathon hosted by the City of Austin and the UT Center for Transportation Research
A Transportation-Themed Hackathon hosted by the City of Austin and the UT Center for Transportation Research
First, thanks so much for releasing this data! It's an amazing dataset and I anticipate that we only touched the surface of potential solutions it enables at the event yesterday.
One problem I discussed with a few other people at my table was distinguishing cars from bicycles from pedestrians. We could draw thresholds based on the assumption that cars travel faster than bikes, which travel faster than pedestrians, but this is not always true: during rush hour bikes might outstrip cars; in rush hour + accident, pedestrians might even win.
While cars / bikes / peds might all be carrying iPhones, there are likely some devices that are clear indicators of a specific category, like a smart dashboard system in a newer car.
For this purpose, it would be useful to retain the first three octets of the original MAC Addresses, which indicates the vendor of the device, and only anonymize the subsequent octets.
Having even limited vendor cues could be useful for bootstrapping a clustering algorithm to automatically distinguish (to some degree) between cars / bikes / peds.
Related to #9, I have a few questions about the MAC addresses that appear in the dataset. Can you explain / describe:
8f:bd:9e:e9:18
, in one day's data, will that be the same device as every other 8f:bd:9e:e9:18
in the rest of the data?
And if relevant, can you briefly describe the ETL process and anticipated frequency of updating those data sources with the latest sensor readings?
It should probably be "lines, words, and bytes."
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