AI tracks public seating use in Sydney trial

Public seating in Sydney
The AI-supported public seating being trialed in Sydney. | Photo: Supplied by UNSW

Moveable, AI-supported seating is being used in Sydney to better understand how people use public spaces.

Created by UNSW Sydney industrial designers in collaboration with Massachusetts Institute of Technology (MIT) urban technology planners, the experimental outdoor furniture is being rolled out by Transport for NSW in a project aimed to enhance the usability and inclusivity of public space.

The project specifically aims to better understand how women, girls, and gender-diverse individuals use public spaces.

UNSW Industrial Design Associate Lecturer Gonzalo Portas said the innovative outdoor benches featured motion-activated LED lighting and were monitored by AI technology to learn more about how people interact with their urban environments.

Mr Portas said members of the public could interact with the seating and participate in a survey.

“Through this project, we hope to create a model for smart, safe, and inclusive public spaces that can be replicated across various urban environments,” he said.

“By involving diverse voices in the design process and leveraging cutting-edge technology, we aim to address the unique needs and preferences of underrepresented groups in public spaces.”

Mr Portas said the seating units had a distinctive and durable design made from recycled plastic sheets.

He said each one was relatively lightweight allowing them to be used and moved around based on user preference.

“Users can flexibly sit in various positions, including cross-legged on top, perching on the edge, reclining against them, or straddling them like benches.”

Mr Portas said the smart seating incorporated LED lighting strips, which illuminated when there was movement nearby to increase visibility.

“The seating area is monitored using AI vision technology, which detects general movement and usage patterns.

“Observations and surveys alongside the technology are used to understand user characteristics like gender, which is incorporated into the analysis.”