Building the “Uber” of Machine Learning
HSAT has won another award, this time from the Norwegian Space Agency
HSAT is building a solution to collect data, from around the world, using mobile devices and local resources. This is best described as the “Uberfication of data collection”
This work will create the world’s largest crop database as well as transform how data is obtained for machine learning
Ground Truth
To build a machine learning model normally requires large amounts of known data to train the model. This is known as the “Ground Truth”
Currently it is very expensive to survey thousands of fields. Collecting crop data for a single country takes many months and costs £50,000+
HSAT expects to reduce the cost by 90%, decrease the time from months to days.
Uberfication and Data Collection
HSAT’s solution is to work with local resources, combing mobile apps and satellite data to rapidly build up Ground Truth. HSAT aims to survey over 50,000 fields and have a team of over 1,000 collecting data around the world – by the end of 2022.
Data and Big Data
The data being collected will help the understanding of crops and help monitor the impact of climate change.
However, the scale of data is slow large that this “big data” will allow entire new insights from seeing how countries are changing their food production to better understanding logistics and food security.