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Humanity-Tech technology is based on connectivity. The main function of it is to allow public environments to be connected in the sense that technology serves users and promoters.


Our systems integrated into a selection of connected object sensors (IOT) allow data to be collected in relation to the immediate environment of the users of street furniture services. This allows, among other things, greater personalization of the "customer experience" within public spaces.


The data collected is then compiled and processed in an artificial intelligence learning model to bring out typical user-profiles and usage trends, thus enabling cities and developers to improve their supply of services.



real-time data analysis (IOT)

  • Cloud usage data

  • People counting / Traffic (Public mode)

  • User recognition (Private mode - APP)

  • Targeted communication with users

  • Allows the display of advertising content (Media management portal)

  • Access to External IOT modules

  • Usage matrix - User mapping

  • Integrated Artificial Intelligence

  • Cellular connectivity 4G/LTE

  • Integrated IOT module (Temperature, Air, Pressure, Noise, Presence)

  • Bi-Directional WiFi access point.

  • Personalized statistical reports

Environmental data:

  • Ambient and historical temperature

  • Relative humidity

  • Air quality

  • Noise pollution

  • Daylight sensing


Traffic data:

  • Presence according to defined zones

  • Movement of passers-by

  • Density of passers-by

  • Proximity detection


Connected data:

  • Analysis of neighboring networks

  • Management of connected devices

  • WiFi access point

  • Signal strength analysis





data collected

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analysis of CROSSED data

The analysis of cross data is done through a learning process in Artificial Intelligence from the collected data. It makes it possible to derive usage trends and standard user profiles in order to further personalize the service offer of cities and event promoters.


The analysis are multiple and configurable according to the surveyed environments and to the specific needs in relation. For example, it would be possible to highlight trends in crowd movement for a given area as a function of the outside temperature. It would then be possible to direct these crowds with service proposals adapted to them, as a positively or negatively perceived variable. The result for users is reflected in an improvement in the services perceived and in the efficiency in the deployment of the services granted by the cities and the promoters.

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