Artificial intelligence detects mileage patterns
Hot on the Tracks
© Lead Image © sermax55, 123RF.com
On the basis of training data in the form of daily car mileage, Mike Schilli's AI program tries to identify patterns in driving behavior and make forecasts.
New releases in the Deep Learning category are currently springing up from publishing companies like mushrooms out of the ground, with "neural networks" here and "decision trees" there. Armed with brand new open source tools such as TensorFlow or SciKits, even the average consumer can treat their home PC to a helping of artificial intelligence (AI). What could be more obvious than feeding your trusted home Linux box with acquired data and checking whether it can then predict the future based on historical values and by applying new AI techniques.
Simply Linear
As discussed in a previous issue of this column, I have an Automatic adapter in my car that collects driving data via the OBD-II port and stores the data on a web service via the mobile phone network [1]. Scripts then use the REST API to retrieve the data from the network and can thus be used to determine the exact time when the car was driven and where it went.
For example, it is easy to retrieve the daily mileage and output it as a CSV file (Figure 1) or plot the odometer data graphically over a time axis for an entire year (Figure 2).
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