Myths about mobile SDK data
π Accuracy & Reliability β While individual GPS signals may have errors, modelling large-scale datasets using sensor fusion and building-matching ensure high precision.
π Demographic Bias β 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.
π Privacy & Consent β An ethical SDK like Accuratβs requires explicit user consent, complies with privacy laws and uses aggregation and anonymization techniques to protect identities.
π Comparison to Traditional Traffic Data β 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).
π User Participation β 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.
π Pedestrian vs. Car Traffic β 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.