ESA Technology Transfer Success Story - Space at home: using space heritage to increase efficiency and automation in the home [Aug/2022]
Slovenian firm SkyLabs developed its spectroscopy technology, supported by ESA, into an AI-supported miniature textile composition and colour recognition apparatus that can be integrated into IoT-connected home appliances, such as washing machines. An innovative visible and shortwave infrared optical payload called NANOimager, originally developed for Earth Observation applications, is being adapted to provide quick, accurate textile composition and colour recognition capabilities for use in smart, adaptable home appliances.
Recordings from the sensors feed into the machine recognition algorithm, linked to a pre-trained machine recognition model, which identifies the textiles from a database. The optimal parameters for the laundry programme, such as temperature, water usage, spin speed and time, are then automatically selected. Testing to date shows over 95% accuracy under the strictest performance metric (successfully identifying the primary and secondary textile composition of a garment in the correct order).
The global market for smart washing machines was valued at around €7bn in 2020 and is expected to grow to over €23bn by 2026. Even limited penetration of this market for SkyLabs could make a substantial impact on their business. Slovenian manufacturer Gorenje produces 800,000 washing machines each year and foresees AI-enabled machines being core to the future of their industry, to the extent that all of their new machines could have this technology integrated within ten years.
Automatic programme selection would simplify the laundry process and provide enhanced user choice and experience. In being able to identify a garment which does not fit a selected cycle, such as silks in a cotton wash or a red sock in a white’s wash, damage to clothing can be prevented, saving consumers’ time and money, as well as giving consumer’s confidence that well-loved items will not be damaged. By automatically recognising the composition and characteristics of a load, this technology can guarantee clean clothing with the optimal amount of energy and water use. This is a clear benefit to users, but could also generate environmental benefits, as consumers buy fewer new items of clothing to replace damaged items.
With 10% of global greenhouse gas emissions resulting from clothing and footwear production and 2,700 litres of water needed to produce a single t-shirt, these benefits are potentially substantial.
The full case study report can be accessed in the restricted area here (please log in before).
The infographics can be accessed in the restricted area here (please log in before).
This initiative is led by ESA's Technology Transfer and Patent Management Unit (TTPO) in ESA's Directorate for Commercialisation, Industry & Procurement. The Unit is guiding start-ups, entrepreneurs and European businesses in developing spin-offs for ESA's space technologies. More recent successful transfers can be accessed at: Technology Transfer - Funded Projects. For more information, please contact firstname.lastname@example.org.