Your browser doesn't support javascript. This means that the content or functionality of our website will be limited or unavailable. If you need more information about Vinnova, please contact us.

ECSEL 2017 RIA aFarCloud Imagimob

Reference number
Coordinator Imagimob AB
Funding from Vinnova SEK 1 896 882
Project duration September 2018 - December 2021
Status Completed

Purpose and goal

Within agriculture, fewer and fewer people need to do more work, and the farmer needs decision-making support to be able to control seed, irrigation, fertilization, spraying and animal holding. Within aFarCloud, a cloud platform has been developed for the collection, processing and visualization of data. Imagimob has integrated a solution for activity measurement for animals and agricultural equipment, where motion data is processed sensor-near, and sent to the cloud for visualization. We hold an automated process for data collection, and training of neural networks

Expected results and effects

We have developed an equivalent for livestock of a sports tracking bracelet, which works over long distances. Tests of the services we have developed show that the animals´ activity and movement patterns can be predicted with high probability, and give an indication of an animal´s well-being over time. This can provide savings for the animal farmer, who by being able to continuously monitor the animals, can see long-term effects of following a meat or dairy cow for longer periods to be able to early detect hidden underlying ailments and prevent infection spreading to the rest of the herd.

Planned approach and implementation

The work has undergone several phases; collection, training of AI models, deployment, testing and lastly feedback and hence new iterations. Data collection from tractors and other fixed assets has been straight-forward, while data from animals is more demanding, often in combinations of monitored collection (video), supplemented with unattended methods. Exchange of knowledge and harmonization between partners working groups´ methods also allowed other actors to be able to use our tools for analysis of their own data, whereby economies of scale have been achieved in the project.

External links

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

Last updated 21 January 2022

Reference number 2018-01577

Page statistics