tracking cows in extensive fields with drones · 2019. 7. 15. · with drones gentore feasibility...
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This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Tracking cows in extensive fields with drones GenTore feasibility study of novel technology in beef systemsSander Mücher, Jappe Franke, Henk Kramer and Ben Loke Breed4Food SEMINAR, “Scientific developments in tracking and monitoring animals in groups”,
4 July 2019, Zodiac, Wageningen Campus
Contact: Sander Mücher, Wageningen Environmental Research (Alterra)Tel: +31 (0) 317 481607, email: [email protected]
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Main Objective
• Feasibility study will show how theuse of location information of tracking devices and image information from drones can beused to measure cow movementpatterns as proxies for efficiency andresilience in rangeland beef production systems.
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Objective Noldus
• To develop and test sensor fusion techniques to combine information from diverse inputs (GPS and accelerometer data) to create a proxy for behaviours of the cattle.
• This all will be embedded in Noldus TrackLab analysis software to enable users to visualize and analyse the information.
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Objective WENR
• WENR will use fixed wing and multirotor drones with mounted cameras (e.g. RGB, video, multispectral, LiDAR) to detect, locate, identify and characterize cattle.
• WENR has in collaboration WU a UAV (Unmanned Airborne Vehicle) Facility since 2012 with RPAS Operator Certificate (ROC) approved by Dutch Aviation Authorities in April 2015.
• Pilots will be implemented at various locations:– Wageningen Campus (WR, CARUS) – 2018, 2019– Juchowo farm, Poland (FSK) -2019– Extensive beef production system in France (IDELE) - 2020
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Characteristics to be measured
Characteristics to be measured
Field reference (Noldus & WR)
Drones (WR) Analyse
Automatic detection of location and animal
counting
Cow tracker (SODAQ) with gps enaccelometer. Data stored SD cardSelected cows with their own cow
tracker
RGB photographs + video+thermalimagery (visually and by machine
learning)
measuring standard deviation in distance between GPS locations and
locations derived from aerial photographs
Standing or walking, lying
Cow tracker (SODAQ) with gps enaccelometer. Data stored SD card.Selected cows with their own cow
tracker
RGB photographs multi temporal + video (visually and by machine
learning)
Comparing false and positive observations from drone compared
with field observations
Individual cow identification
Cow tracker with unique ID From photos (visually)Comparing false and positive
observations from drone compared with field observations
Height and weightHeight, weight and size
characteristics measured by farm for each cow
Determine from photos size (length, size) + height ? + weight indication ?
measuring standard deviation between drone and field
observations
Cow detection Cow location Cow identification Cow characterization
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Machine Learning
• Machine Learning options– Detection– Counting– Identify– Poses
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Annotation with LabelImg
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Machine Learning; cow detection
Accuracy 95.0%
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Location: inaccuracies in GPS trackers will/must improve
Inaccuracy GPS trackers ~ 4m
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Machine Learning; cow Identification
Accuracy 56.0%
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Poses: Standing or walking, lying
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This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Using LiDAR RiCopter for height and weight
http://common-test.services.geodesk.nl/storymaps/potree/vecht04.html
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Using LiDAR RiCopter for cattle
http://common-test.services.geodesk.nl/storymaps/potree/v16/Caruskoein_20190522.html
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Using LiDAR RiCopter for height and weight
http://common-test.services.geodesk.nl/storymaps/potree/v16/Caruskoein_20190522.html
CARUS LiDAR experiment 22 May 2019
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Primitive Matching and Measurements in CloudCompare
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This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Machine Learning on drone imagery; results so far for cattle
• Detection– Works well; 85% - 95% accuracy
• Counting– Bit more difficult; Animal movement off image frame
and between frames can cause multiple counts. – higher altitude images (less detail) give better results
• Identification– ~56% accuracy; – more annotation needed in lower altitude images (more detail)
• Standing or walking, lying– In progress
• Height and weight– In progress
This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 727213
Contact: Sander Mücher, Wageningen Environmental Research (Alterra)Tel: +31 (0) 317 481607, email: [email protected]