"Greenspector" is now "The Greenspect Project"


We got inspired seeing many new posters and product designs on how environmental friendly and sustainable a product or company is. Especially the energy company RWE has set up many billboards with statements about their superior renewable energy production. We sought for a digital solution that does not need additional technical devices as these would require additional resources and thus be counterproductive in tackling environmental challenges.

What it does

To tackle the discrepancy between environmental sustainability claims and actual sustainability performance, we developed an app to inform private and business users about the company´s background using objective indices and metrics retrieved from several sources. The user of the app may then give feedback to the provided results whithin the app, which can potentially be fed back to the companies so they can evaluate their recognition in public and business.

How we built it

We searched for reliable accessible sources providing sustainability data about companies. Simultaneously we developed an artificial intelligence recognizing company logos in pictures taken with smartphones. We also started to develop the app itself, where the background information of the companies will be displayed.

Challenges we ran into

We were too few people to work on all the tasks we originally aimed for because our team got reduced from 6 to 4. Furthermore, copyright limitations had to be circumvented.

Accomplishments that we are proud of

We got a feasible product idea where we generated a product outline for. Very good sources for future implementation could be identified. A company logo recognition could be established using artificial intelligence based on tensorflow.

What we learned

We improved on project planning, app programming and learned a lot about open sources about company emissions and metrics as well as sustainable initiatives in general.

What's next for CLI05_Greenspector

Official permissions for certain source data have to be acquired. With the access to these data repositories, content can be implemented to our app. Furthermore, a neuronal network has to be trained with company logos for logo recognition and the app layout has to be created.

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