Machine learning platform for dynamic device and sensor quality evaluation

A non-transitory computer readable medium having stored thereon instruction code that, when executed by at least one processor of a computing platform, causes the computing platform to:

• identify, for each of a plurality of consecutive driving trips specified within driving data, a time difference between an end point of a first driving trip and a starting point of a second driving trip;
• determine a percentage of the time differences that exceed a predetermined period of time;
• determine, based at least in part on a comparison of the percentage to a predetermined percentage value, a device evaluation score indicative of an accuracy of the driving data;
• and
• selectively exclude the driving data from subsequent driving score computations when the device evaluation score is below a predetermined accuracy threshold, thereby reducing a likelihood of a driving score being computed based on inaccurate data.

A computer-implemented method comprising:

• identifying, for each of a plurality of consecutive driving trips specified within driving data, a time difference between an end point of a first driving trip and a starting point of a second driving trip;
• determining a percentage of the time differences that exceed a predetermined period of time;
• determining, based at least in part on a comparison of the percentage to a predetermined percentage value, a device evaluation score indicative of an accuracy of the driving data;
• and
• selectively excluding the driving data from subsequent driving score computations when the device evaluation score is below an predetermined accuracy threshold, thereby reducing a likelihood of a driving score being computed based on inaccurate data.