Ferrara Pilot: Difference between revisions
(Created page with "The Ferrara Pilot focuses on 4 building scenarios: schools, offices, entertainment, and residential. Each scenario involves different types of occupants, activities/behaviours and buildings’ properties. The pilot is driven by the proactive role of the local community: behavioural change campaigns will be activated for collecting “warm data” (experiences and perceptions) together with the installation of low-cost multi-sensors indoor devices (Sentinels) and remote r...") |
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The Ferrara Pilot focuses on 4 building scenarios: schools, offices, entertainment, and residential. Each scenario involves different types of occupants, activities/behaviours and buildings’ properties. The pilot is driven by the proactive role of the local community: behavioural change campaigns will be activated for collecting “warm data” (experiences and perceptions) together with the installation of low-cost multi-sensors indoor devices (Sentinels) and remote reference stations to obtain comprehensive information about indoor air pollutant concentrations. | The Ferrara Pilot focuses on 4 building scenarios: schools, offices, entertainment, and residential. Each scenario involves different types of occupants, activities/behaviours and buildings’ properties. The pilot is driven by the proactive role of the local community: behavioural change campaigns will be activated for collecting “warm data” (experiences and perceptions) together with the installation of low-cost multi-sensors indoor devices (Sentinels) and remote reference stations to obtain comprehensive information about indoor air pollutant concentrations. | ||
Latest revision as of 11:35, 5 June 2024
The Ferrara Pilot focuses on 4 building scenarios: schools, offices, entertainment, and residential. Each scenario involves different types of occupants, activities/behaviours and buildings’ properties. The pilot is driven by the proactive role of the local community: behavioural change campaigns will be activated for collecting “warm data” (experiences and perceptions) together with the installation of low-cost multi-sensors indoor devices (Sentinels) and remote reference stations to obtain comprehensive information about indoor air pollutant concentrations.