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Sustainable Sensing in Future Factories

Reference number
Coordinator Uppsala universitet - Institutionen för informationsteknologi, datalogi
Funding from Vinnova SEK 499 115
Project duration November 2018 - November 2019
Status Completed

Purpose and goal

To enable factories of the future around the vision of Industry 4.0 collection of large scale data at factories is essential. This is to enable the use of various machine learning tools and techniques, as an example, condition-based monitoring. There has been interest in various machine learning tools, however, sensors have been largely ignored. Presently sensors employed in factories are bulky and require a lot of maintenance due to the use of batteries and external power. The goal of this project was to design battery-free sensor platform to enable large-scale collection of data.

Expected results and effects

One reasons for large form factor and sparse deployment of sensors in factories is the use of big batteries. This is necessary as sensor platforms use of conventional transceivers which are energy expensive. We have used our world-beating expertise in backscatter communication to design sensor platforms that can measure light, temperature etc. and transmit these wirelessly while operating without batteries. Our sensor platform are in the form factor of stickers. This can enable deployment of such sensors at massive scale within factories enabling large scale data collection.

Planned approach and implementation

We have made significant progress and designed battery-free platforms that can measure and wirelessly communicate light or temperature. These works have been presented/demonstrated at flagship venues. We have improved underlying communication mechanism significantly with TunnelScatter, which was presented at highest-ranking venues in area. We have attracted interest from a significant industrial organisation and worked on intellectual property issues. We have made significant progress towards this vision which we intend to continue to develop over the next several years.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 11 November 2021

Reference number 2018-04305

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