A modern approach to precision farming

1. Автоматические
беспилотные летающие
роботы “Karlsson”
Karlsson autonomous
unmanned aerial robots
Leading edge aerial monitoring
solutions in agriculture

2. Overview: A modern approach for precision farming
Traditional Farming Precision Agriculture
● Specific properties of the field are not
taken into account when agricultural
activities are being conducted
● Inefficient use of natural resources and
fertilizers
● Lack of an accurate data about the
state of the soil
● Excessive usage of fuel due to
inefficient machinery routing
● Accounts for the specific terrain
features and soil properties
● Continuous monitoring of the soil
state
● Accurate distribution of fertilizers
according to the data collected
about the soil
● Avoiding harmful environmental
effects by systematic soil treatment

3. Overview: modern farming challenges, solutions and
results
● Inefficient use of fertilizers
● Absence of customized
approach to soil and crop
treatment
● Large workforce and
machinery involved in
agriculture production
Main challenges
● Monitoring of NDVI spectra
leading to targeted
application of fertilizers
● Thermal maps creation -
spatial data collection
system
● Continuous monitoring
leading to aggregation of
soil data and crop
treatment effects
Solution
● Optimized usage of
agricultural consumables
● Increase in crop yields
● Improvement in quality of
agricultural products
● Reduced environmental
effects
● Additional data for
agricultural management
Results
Objectives of precision farming: ● increase crop yields
● cost-effective use of fertilizers
● reduce environmental damage

4. Application of aerial monitoring: key technologies
Terrain feature
detection
NDVI pattern
surveying
30% increase in
crop yields
20% reduction in
fertilizers cost
20% increase in
net profit
Precise agricultural
machinery routing
Crops monitoring
● Data
aggregation
● Anomaly
detection

5. Market size
USA
≈ 2 100 000 farms
Total Revenue ≈ $374 billion
Agriculture Monitoring Market ≈ $2 billion

6. Consistent scheduled fields
monitoring
Vegetation index map with a 5 cm
per pixel resolution
Control over the general state of
fields
Import of data to a specialized
software packages
Data driven actions:
● Calculated routing for autopilots
● Automated crops planting
● Targeted fertilization

7. Karlsson Automated UAV network
Main goal: full autonomy and independence from humans.
Solution: autonomous wireless charging stations, mission control center,
client system.
UAVs and charging
station network
Mission control
Telemetry and data
3G/4G networks
Cloud servers
UAV generated data
used for various
purposes
Mission control center

8. Max altitude 3000 m
Flight speed 0-65 km/h
Flight time 15-35 min
Max wind speed 25 m/s
Payload (up to 1.5 kg):
Camera Sony NEX-7 with diff. filters
Thermal camera FLIR Tau 640х480
Videocamera GoPro HERO4 FullHD
Technology platform: UAV and charging station
Autonomous wireless charging station with up to 500 W power

9. Karlsson Project team
Position Education
Dmitry Korolev CEO / Co-founder MS in Physics MSU
Andrey Grunin CBDO / Co-founder MS in Physics MSU
Pavel Kapralov CTO / Co-founder PhD in Physics, MSU
Ilya Mukha Design Engineer MS in Physics MSU
Nikita Ushakov Business Development MS in Industrial Engineering, Columbia University
Alexander Solovyev Computer Vision Engineer MS in Computer Science BMSTU
Alexey Dolinenko Embedded Systems Engineer MS in Engineering PGTU
Vadim Stukalov Back End Engineer MS in Computer Science BelGU
Vladimir Khodakov Front End Engineer MS DonNACEA

10. Phone number: +1 (206) 973-99-58
+7 (926) 270-59-96
Email: info@karlssonproject.com
Website: karlssonproject.com
Youtube: youtube.com/karlssonproject
Vimeo: vimeo.com/karlssonproject