๐ Pedestrian and Air Quality Sensor Data
How might we improve usersโ experience of their city by using data from pedestrian and vehicle counters and/or air quality sensors?
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Digital Thinks
The Digital Thinks 'Luminair' project uses environmental and IoT data to explore questions and opportunities for health, wellbeing, placemaking, sustainability and awareness around air quality. Through commonalities and patterns of data locally and nationally, we consider how air quality data can be collated and visualised.
Contributing to public spaces, community awareness and education, the project proposes incorporating environmental data into public art such as visual lighting indicators to inform community and support individuals and communities in making informed decisions day-to-day for improved health, wellbeing and sustainability.
Luminair takes air quality data from several datasets across australia, where dedicated air monitoring stations and Internet of Things (IoT) data is being collected. Data sources include:
All datasets include a 'PM10' air quality reading relating to particle matter in the air that can be used to measure impacts on health and wellbeing impacts from exposure based on air quality standards. Other comparable attributes include location, date and time.
Each source dataset has been gathered from the listed repositories and consumed as an excel or API for a point in time measure and comparison. Historical data is available for some datasets to also measure change and trends over time.
Data has been collated into a table to draw insights and explore questions raised from the proposed challenges and ideas generated within the project.
Taking a design thinking approach to the challenges and data, we have explored questions like
In combining these datasets, we've started to make some observations about air quality in various places and nationally. We can see that air quality is generally good or very good, however another quick observation is that the highest and lowest readings to vary greatly in the same place.
With more time and consideration beyond GovHack, there would be a great opportunity to look at standardising data being published around air quality to be able to benchmark and paint a picture of air quality locally, nationally and globally
The idea we'd like to proposed beyond the GovHack weekend is to integrate air quality data into public spaces and art. It could be as simple as a colour changing light on a pole, to show an easy visual indicator, or more detailed displays that change and adapt, based on conditions.
Visual indicators can have a great impact on peoples experience in a city or place, and increase accessibilty of the data being publicly available and easy to consume.
Our future cities and environment will depend on how we plan them, and also how we use them. Through combination and collaboration, we are able to generate new insights, share more information and increase community accessibility and wellbeing.
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While exploring air quality data over the GovHack weekend, we have also tested consuming air quality API to provide instant and personalised notifications to customers and communities.
Using recipe builder IFTTT, a prototype of using the Webhooks function to send notifications was tested to be able to send an instant email to an individual when air quality changes to poor.
Using Microsoft Flow we were also able to prototype a combination of steps that call the API once an hour, parse the measurement received and push notifications to a chosen device.
This was omitted from the video due to time constraints of producing a max. 3 minute video. Supporting screen shots are in the supporting evidence of work folder.
Description of Use Air quality data from Queensland Government API used to combine and compare with other air quality datasets for PM10 readings
Description of Use Air quality data from SEED NSW Lower Hunter used to combine and compare with other air quality datasets for PM10 readings
Description of Use This animation is used to assist in demonstrating fine air particle pollution in the video
Description of Use Air quality data from Queensland Government and Townsville used to combine and compare with other air quality datasets for PM10 readings
Description of Use Air quality data from CSIRO Sydney particle study used to combine and compare with other air quality datasets for PM10 readings
Description of Use Air quality data from CSIRO Sydney particle study used to combine and compare with other air quality datasets for PM10 readings
Description of Use Air quality data from SEED NSW API used to combine and compare with other air quality datasets for PM10 readings
Description of Use Air quality data from City of Darwin used to combine and compare with other air quality datasets for PM10 readings
Description of Use Air quality data from Smart Cities, Smart Liverpool, Smart Pedestrian Project used to combine and compare with other air quality datasets for PM10 readings
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