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Home Application Smart Cities

Melbourne to use AI to keep city streets safe and clean

FutureIoT Editors by FutureIoT Editors
August 22, 2023
Photo by Felix Haumann: https://www.pexels.com/photo/park-near-modern-building-during-daylight-3626248/

Photo by Felix Haumann: https://www.pexels.com/photo/park-near-modern-building-during-daylight-3626248/

To decrease the frequency of waste contractor visits to busy areas, the City of Melbourne has offered residents and businesses subscription-based access to large-capacity compactor facilities. With the compactor in place, Council then wanted to understand how the service was being utilised and how to mitigate illegal waste dumping, which can quickly create safety and hygiene issues in the area.

Under its ‘emerging technology testbed’ initiative, the City of Melbourne worked with Nokia to leverage an existing network of installed cameras as Internet of Things (IoT) sensors to monitor one of the compactors.

The Nokia Scene Analytics solution employs an AI-powered algorithm to filter and collate data from the cameras, while also combining other data sources, such as operational data on the compactor itself, to create real-time alerts and produce reports.

Initial tests show

Initial trial results demonstrate that Scene Analytics can support the City’s objectives for better, safer citizen experiences while simultaneously lowering maintenance and downtime costs for waste management services.

Sally Capp

Lord Mayor Sally Capp, City of Melbourne, says the solution is a great example of using new technology to help remove illegal waste more quickly, make our city cleaner and protect the environment.

"This innovative project will help to avoid hazards and make our streets even cleaner by allowing our waste services to better understand behaviour trends related to the illegal and dangerous dumping of waste,” she continued. 

How the technology works

The trial allowed for real-time monitoring and detection of activity in the vicinity of the compactor using a virtual tripwire. Object detection and object counting was used to identify and count items to show how the compactor was impacted by items incorrectly placed within it, while also identifying potentially dangerous items.

Anomaly detection identified unusual movements, such as illegal waste dumping during the night, while face and license plate blurring maintained individual privacy during the trial.

Using these reports, the City of Melbourne can better understand the correlation between illegal waste-dumping activities and compactor downtime, to keep maintenance teams better informed and minimize issues.

It also allows them to swiftly address waste dumping activities before they become a hazard, viewing locations in real-time to observe any obstructions to service vehicle access, and adapting their schedule to reduce unnecessary visits and minimize their carbon footprint.

By understanding patterns of compactor usage and waste dumping activities, the city of Melbourne is also able to patrol the area more effectively, while developing an ongoing campaign to better inform and educate the community.

Related:  Tokyu Hands trialled unmanned smart retail pilot
Tags: Artificial IntelligenceNokiawaste disposal
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Asia’s ONLY dedicated IoT publication

The race to harness the power of Internet of Things (IoT) is here. FutureIoT is dedicated to individuals, as well as public and private organizations looking to tap the potential of IoT to transform the way we live, work and do business. FutureIoT is the dedicated media that provides the single source of truth about IoT, the technology, its application and regulation, originating from Asia. << Read more >>

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Standardisation and tech are keys to unlocking growth in Asia's supply chains

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