![]() ![]() This data is useful when combined with other people movement and asset usage data for understanding how people use Argyle Square over time. They capture times of stage usage as well as duration to help us to understand how the community uses this amenity. There are three ERS stage movement sensors installed on the roof of the stage. We m ay use this da t a t o s u p p o r t s e r v i c e t ea m s w h o main t a in t h e p a r k and inf o rm t h e d e s i g n o f f u t u r e p a r k s. W h i l e w e're not sure what the data will show us, our the ory is that t h e d a t a can h e l p u s b e t t e r u n d e r s t an d h o w o u r c o m m u n i t y u s e b i n s. ![]() We collect Netvox R718X bin sensor d a t a to understand how bins are used in Argyle Square. We might use this data to understand how tree coverage impacts air quality. T his data may inform future tree planting decision making as we work to mitigate the effects of climate change.Īir quality data collected via our EMS air quality sensors shares insights into prevalence of polluted air, its concentration, and how long that bad air remains in a location enabling historical trend analysis. This data will help us develop historical trend analysis, to understand the different microclimates of the park and how much cooling and heating effects are at each location. Netvox temperature and humidity sensors are installed in 4 locations across the park, with three out of the four locations measuring the microclimate s created by different tree species including elm and gum. T his data may be used as an input into future climate change mitigation strategies like urban heat island effect. The microclimate generated by an urban space such as Argyle Square can increase the frequency of fog, the intensity of storms, the concentration of polluted air, and how long that bad air remains in the city. ![]() Atmos weather station sensors collect m icro-climate data to compare to Bureau of Meteorology data and understand how Argyle Square's weather conditions are different to the rest of Melbourne, which is useful for historical trend analysis. ![]()
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