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.