The droneONtrap project aims to provide a system for real-time and remote crop disease monitoring using traps installed in fields and occasional data collection from UAVs. The project involves two partners, MAVTech as the leader and FOS as a partner. The traps are designed to be low-maintenance, using batteries, solar panels, and wireless communication to send photos at programmed intervals. The project has demonstrated successful pest detection and handling of multiple clients simultaneously using the trap and server system, but further improvements are still needed.

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Gabriele Scarton
gabriele.scarton@fos.it
Gruppo FOS S.p.A.
NOI Techpark Südtirol/Alto Adige, Bolzano, 12th November 2021 – SFScon2021
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droneONtrap project:
Smart traps for remote field monitoring

2. 12th Nov 2021
#SFScon21
droneONtrap project
gabriele.scarton@fos.it
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Gruppo FOS
Multimodal System for
Personalized Post-Stroke
Rehabilitation
Today 13:00, this track
Open-source digital learning:
inRebus approach to gamification
Tomorrow 9:00, Community and education track

3. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
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The droneONtrap project

The project droneONtrap aims at providing a demonstrative system for
real-time and remote crop disease monitoring.

Partners:
 MAVTech, project leader
 FOS, project partner

Start Date: 05/05/2020

End Date: 30/11/2020
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Funded by DIVA project www.projectdiva.eu

4. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
4
Project goals

The system is composed by traps installed on fields for real-time and remote
daily status of a significant portion of crop and sporadic data collection using
UAV for complete analysis of the whole crop

5. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
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UAV system

Multispectral images captured by UAV
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droneONtrap project
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Traps goals

Easy to install - Plug & play system

No cables - Wireless real-time comunication

Non-invasive and fully integrated with current monitoring
activities (visual pest detection)

Low-maintenance – indipendent power supply system

Controlling by remote and mobile devices

Sending Photos at programmable intervals

7. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
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Trap design

Structure designed with CAD software

Electric system based on:
 Litium batteries and solar panels
 Computational unit
 Wireless comunication module
 Camera and sensors

Trap sheets

8. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
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Trap realization

Structure 3D printed @ NOI Makerspace
 Top container for IoT components
 Middle for weather protection
 Bottom for glued trap sheets

Off-the-shelf components
 Single board computer
 System on a chip microcontroller

9. 12th Nov 2021
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Configurations comparison
Single board computer

More powerful

Easy to use

Verified hardware: single
reliable source

Lot of sensors compatible
System on a chip microcontroller

Low energy consumption

Specific firmware

Open hardware: multiple
cheap sources

Small size

10. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
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Which is the best configuration?

Single board computer are simpler to set up and provide better
results, but costs and energy consumption are high

System on a chip microcontroller theoretically provides the perfect
solution for the task, but requires a lot of time to find/check a
reliable configuration based on specific hardware

11. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
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Data
From trap to costumer

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droneONtrap project
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Server goals

Receive data from traps

Process data

Make data available fast and simple

Manage different sources and users

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Receive data from traps

GSM communication
 Not fast but great coverage
and not expensive

VPN protected comunication

SSH and FTP server

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Process data

Initial phase - ImageJ
 Processing based on colors
 Morphological operations to
reduce noise from shadows
and other insects
 Human validation directly on
dashboard

Stable phase – AI model
 Computer vision algorythms
 Human validation directly on
dashboard

15. 12th Nov 2021
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droneONtrap project
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Data availability

Real-time processing
 inotify-tools

Database-centric structure
 MongoDB
 Non-relational model: flexibility to add any type of sensor

Real-time notification
 Telegram bot

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Different sources and users

Admin dashboard
 Managing users and fields
 Controls on config and scans
 Mobile friendly

17. 12th Nov 2021
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droneONtrap project
gabriele.scarton@fos.it
17
Conclusions

Large-scale
demonstration success
 Working trap configurations
 Successful pest detection
 Handling multiple client
simultaneously

Need more work
 Improve trap
configurations
 More data for AI
classifications

18. Thank you for your attention!
Questions?
Thank you for your attention!
Questions?
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Gabriele Scarton – Gruppo FOS S.p.A. - gabriele.scarton@fos.it