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Crowdsourced Data Helps Cities Fight Litter

To combat its litter problem, the city of Memphis is turning to data. Over four evaluation sessions this year, 10 researchers will monitor whether litter-prevention methods are working as part of the City Fingerprint Project, a three-city initiative to study litter-related pain points and use data to drive solutions.

For the project, citizen science researchers take a photo of litter items with the company’s Researcher app, which geocodes. Later in the process, the images are assigned a tag to identify them. As data is collected by volunteers, cities can see what kind of litter is showing up where.

Cities participating have the additional ability to overlay different datasets – of population density or commercial corridors, for example – to learn where the litter could be coming from so that we can make better intervention and messaging strategies.

The work will expand on a platform that applies machine learning to photos of litter to develop a baseline of litter composition, such as material, object and brand. The project will look at litter pile up in various sections of the city and compare what it looks like in, say, school zones vs. transportation hubs to give cities a better sense of what litter is most problematic and where.

Memphis has provided several datasets to Litterati on traffic, transit stops and other geospatial data to overlay on their data collection. It is really about getting a better understanding of where our pain points are, what the materials are in those pain points, and what kind of connections there could be to these other sets of data that we are about to be able to evaluate with this platform to help drive better decision-making.

Data on litter composition is crucial, a campaign aimed at creating a zero net waste circular economy. That informs about potential source-reduction campaigns that could potentially run within the city or neighbourhood. There are a lot of different strategies and intervention methods to test out by having this data now.

The primary benefit is to learn how to solve a city’s litter problem. What’s more, cities could use the national data for inspiration. It’s always useful to understand what the city is facing and how that compares to other cities. That can motivate more people to get involved. For instance, Memphis has used the app since 2020 to encourage residents to pick up trash through several challenges, such as the Earth Day 30 Days Straight.

As reported by OpenGov Asia, the Florida Department of Transportation (FDOT) is developing a connected vehicle data exchange platform (DEP) to help analyse real-time road conditions and communicate travel information to drivers. FDOT tapped Southwest Research Institute (SwRI) to develop a cloud-based vehicle-to-everything (V2X) DEP as part of the department’s Connected and Automated Vehicles (CAV) Initiative. The US$ 8 million project is expected to take four years.

The V2X DEP is intended to encompass the FDOT’s operational, development and planned CAV project corridors and networks. The system plans to ingest data from CAV devices and intelligent transportation systems, to assist with decision-making by FDOT and stakeholders in the auto industry, research, traffic engineering and other transportation areas.

Data has to travel along with a backhaul to a Florida DOT traffic management centre, and then from there, it’s got to travel over the public internet to reach this cloud-hosted data-processing platform. At that point, the data is going to be consolidated, duplication is going to be removed and personally, identifiable information is going to be stripped out to ensure anonymity for the travelling public.

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