05 - Solar panel detection

Automatic Detection of Solar Energy Systems using Deep Convolutional Neural Networks

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The Swiss renewable energy statistics estimate the use of solar energy on the basis of market surveys. To validate these statistics, existing solar installations are to be identified and quantified fully automatically using deep learning algorithms based on aerial photographs. Thanks to this method, the current inventory of installed solar systems can be determined more precisely. Crossed with weather forecast data, the energy output of the installed photovoltaik could be predicted. In addition, the results would allow to plan and evaluate the implementation of the Energy Strategy 2050.


Analysing Swisstopo Aerial photographs with the help of artificial intelligence to either:

· Calculate solar wattage of individual houses and a whole city depending on weather > predictive modeling maybe as an app

· Identify (large) roofs that don’t have solar panels yet installed although their geometric potential is great maybe as a webapp / webgis


Event finished

01.09.2021 13:45

Event started

31.08.2021 09:00

Edited content

15.07.2021 17:56 ~ Maud

Joined the team

23.01.2021 15:25 ~ Maud

Challenge posted

23.01.2021 15:25 ~ Maud
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