Abstract
Digital inclusion in the Ecuadorian amazon is known as a problem, which intensified with the pandemic. Since social distance is now the norm, we constructed a WiFi access point (WAP) scanner to map and analyze its data. We correlated it with ancillary geoinformation to observe its potential and limitations as a method for indirect data collection. Our result indicate that WAP correlate weakly but positively with nightlight, young population, accessibility to economical centres, and negatively with slope. Moreover, we differentiated vulnerability naming patters from Service Set Identifiers (SSDI) and differentiated the number of WAPs according to land cover for differentiate urban from rural areas. This output is now offering increasing applications to get updated rought estimates of internet activity and indirectly correlations to socio-economic conditions, technology practices, and opportunities for natural language processing. Therefore, we conclude that wardriving offer interesting opportunities for mapping social data but also concerns as an indirect data collection method.
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