Myths about mobile SDK data

Accuracy & Reliability – While individual GPS signals may have errors, modelling large-scale datasets using sensor fusion and building-matching ensure high precision.

Demographic Bias – GPS is not only used by a lucky few. All social classes & age groups are covered and biases can be corrected using weighting techniques and external benchmarks like census data.

Privacy & Consent – An ethical SDK like Accurat’s requires explicit user consent, complies with privacy laws and uses aggregation and anonymization techniques to protect identities.

Comparison to Traditional Traffic Data – GPS data provides dynamic, real-time insights beyond major roads, unlike costly and fixed-location traditional sensors. It can compliment hardware solutions or datasets that are skewed to one vehicle type (e.g. floating car data).

User Participation – Despite a strong privacy-sensitive era many users remain to allow background location to be shared for app functionality. Data in exchange of benefits is an accepted balance for many people.

Pedestrian vs. Car Traffic – GPS data is considered to be skewed to footfall vs car traffic. It is true that given the slower movement of a pedestrian, more coordinates in e.g. a city center are collected for pedestrians than cars. However, interpolation of coordinates as a normalisation technique and smart algorithms can differentiate walking from driving using speed, stop patterns, and route types in order to interprete data signals in the correct manner.