Heat Waste Monitoring

What does Skyai do?

At Skyai, we combine multiple remote sensing products with global temperature readings from climate observation centers. This provides useful data sets that we use to create models through machine learning techniques. These models are able to translate the raw information into accurate heat maps, with which we can visualise thermal emission sources and wells.

To correctly model heat emissions, Skyai uses several parameters to improve on the accuracy of the data. Parameters such as the atmosphere, surface emissivity and other heat influencers are used by our algorithms to minimize noise in the thermal data.


“Space heating is the largest source of energy usage for residential homes and offices. On average, 68% of energy used within residences is used for space heating.”

– European Commission, 2016

Heat waste monitoring

By combining our data with external sources, such as land use and building CO2 emission, we create an accurate view of a specific area. Through this we enable rank indexing, creating the possibility of comparing regions of interest (ROIs) with similar areas. Our data regarding heat waste equips sustainability decision makers with the necessary tools and insights to monitor, predict and discover potential energy savings from heat sources. This data is refreshed twice a month, which enables us to detect changes frequently.

Skyai’s heat waste monitoring is meant to give long term actionable insights for clients ranging from local businesses to national governments. With its spatial resolution of 30 meters, it is possible to provide reports of large, as well as smaller areas like industrial zones or entire cities.

“Industry leaks enough heat into the air and water to meet the EU’s entire residential and services heat demands”

– European Commission, 2016

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