We have designed an efficient methodology for urban data capture using electric cars and capabilities already installed in cities, such as garbage collection vehicles. In these we’ve installed:

• Tablets with self-developed software with which we record incidents such as types and quality of roads, traffic, traffic lights in good and bad condition, bumps, potholes or informal settlements, among others.
• Self-developed sensors, recording data of the imperceptible: Temperatures and humidity (climate), pollution levels and air quality (health and environment), noise pollution (health and comfort), lighting in roads and public spaces, among others (security). 
• Computer Vision cameras trained with Machine Learning. With Artificial Intelligence we recognize and register relevant events and objects on public roads, such as presence of brands, conglomeration of people, among others.

Data records can be replicated in real time as alerts in our platform or through APIs to other monitoring and information centers, enabling an immediate response. All our devices are interconnected with IoT logging data in a structured way in our server, generating digital BIG DATA databases. With data analytics and data science we produce dynamic maps and informative dashboards that show the status of cities. Strategic alliances and cross-referencing of internal data with external data open up a real possibility to:

• Planned urban development, with statistics, evidence, predictions and simulations, giving way to machine learning and artificial intelligence applied to city management.
• Identification of activities relevant to various industries such as construction (location and status of construction sites), banking (location of branches, ATMs and relationship with lighting levels and conglomeration), distribution of goods (understanding of the road system in real time), telephony (brand presence on public roads), and others. 
• Market research based on a complete reality and not only based on sample frames.