Air pollution has a significant impact on human health and the economy. Air quality in Sydney is usually very good by international standards. For more information about air quality in Sydney, how our ventilation systems work to manage air quality within and outside the tunnels, and what has contributed to improve vehicle emissions visit the [Air Quality Portal](https://v2.communityanalytics.com.au/rms/air-quality/#). This dataset provides standardised measures of: * Carbon Monoxide * Nitrogen dioxide * Nitrogen oxides * Ozone * Sulfur dioxide * Particles < 10μm diameter * Particles < 2.5μm diameter * BTEX * Methane * Non-Methane Hydrocarbons * THC The data captured is from 01/01/2004 - 31/12/2017 and only includes sites where RMS had access to the monitor's data. More information about the sites covered can be found in the Report and associated data files.

This dataset includes the final Technical Note and accompanying GIS datasets delivered by Cardno and UNSW for their proof-of-concept Passive Surveillance Index (PSI) trial in Parramatta, through TfNSW’s Safety After Dark Innovation Challenge (SADIC). The PSI scores walking routes based on quantifiable indicators. The tool may be a starting point for planners to make informed decisions on how safe cities may factor passive surveillance into their design. The [web map](https://cardnoanz.maps.arcgis.com/apps/webappviewer/index.html?id=82110546dbce47f58a4bbb47e94a6779) visually displays the PSI for different times of the night across the trial area. This website works best using the Google Chrome browser. Contact: Elizabeth Muscat, [elizabeth.muscat@cardno.com.au](mailto:elizabeth.muscat@cardno.com.au) Output: the SADIC PSI Data zip file and technical report

Macquarie University and the City of Ryde Council installed pedestrian-counting sensors throughout Macquarie Park, as part of a project to ease congestion in the growing education, residential, retail and business hub. The pedestrian counters monitored pedestrian flow and blockages, and the data will be used to improve safety and connectivity to transport services. Historical transport, parking and pedestrian data are consolidated on an open-source platform to inform planners and local businesses across Macquarie Park. A dashboard to view the data can be found at [http://smartcity-api.science.mq.edu.au/](http://smartcity-api.science.mq.edu.au/) The raw data that makes up the dashboard is available below.

**Smart Cities, Smart Liverpool, Smart Pedestrian Project** Thousands of people walk through the Liverpool city centre every day and, through the Smart Pedestrian Project, the paths they take will help shape the city’s future. Liverpool City Council is counting pedestrian and vehicle movements around the city centre, collecting data from smart devices and camera-counting technology. The data is stripped of any identification and relayed and collected for analysis by researchers from the University of Wollongong. Liverpool City Council now uses this data to inform planning decisions and respond to the rising number of residents and workers making their way around the city centre every day. Liverpool City Council secured an Australian Government Smart Cities and Suburbs grant to jointly fund the project. Liverpool City Council worked with IT Integration Company Meshed and the University of Wollongong to deliver the technology. Meshed supplied the Low Power Wide Area Network and developed a Wi-Fi smart device counter. The university developed the people and vehicle-counting technology and data analysis. The technology makes use of the city’s existing CCTV cameras to capture images. No images are transmitted over the network, so there is no risk to privacy. This dataset lists the API endpoint URLs to retrieve data for the smart pedestrian project. A dashboard to view the data can be found at [https://pavo.its.uow.edu.au/](https://pavo.its.uow.edu.au/) **Please read the API documentation as you need to provide the parameters to make any API calls.** An example has been provided below that lists all the visual sensors. The API is divided in two sections: sensors, and readings (data gathered by sensors). Unless otherwise noted: \* all datetimes are ISO formatted \* all responses are JSON-formatted