Early

detection pipeline of leafhopper symptoms using drone-acquired multispectral data.

Timing

recommendation model for drone flights.

Automated

alert communication system.

AI4Leafhopper by InnovPlantProtect

InnovPlantProtect is a private non-profit association (collaborative laboratory -CoLab) founded in 2018. They develop bio-based products and technological tools. AI4Leafhopper is an Automatic Infestation Alert for Leafhopper using Drone Imagery. The experimental areas for AI4Leafhopper are located in João Portugal Ramos Vinhos SA (Estremoz) and Reynolds Wine Growers (Arronches).

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App iCountPests: Monitoring of pests on the palm of you hand. This mobile application offers the advantages of reducing the time spent on monitoring, creating a history of pests, democratizing access to technology, allowing for better pest management.

  • YOLOv5-based segmentation model
  • YOLOv9-based segmentation model
  • Predictive models for leafhopper infestations, measured as the progression of symptoms
  • Vegetation indices

Outcomes

  1. Developed a system for the automatic detection of vine-specific health assessment which includes two key models: vine detection and vine-vegetation segmentation.
  2. Integration capabilities provided by InPP AI4Leafhopper product and services, such as AI,drone mapping and pest monitoring, as well as the uniqueness of targeting the green leafhopper as pest.
  3. Open-source software for processing drone imagery is OK but not as complete as the proprietary software.

Challenges Faced

  • Technology adoption issue: Moving from traditional methods to digital solutions (AI,drones,webGIS) is challenging for many producers.
  • Knowledge gap: Providing adequate training and education to producers on the use of digital and automated systems.
  • Integration complexity: Seamlessly integrating new technologies with existing agricultural practices and systems. For instance,“paper based” data collection and conventional monitoring techniques.
  • Data security: Ensuring the privacy and security of data collected through digital technologies.
  • Regulatory: Complying with regulations related to the use of drones,AI/digital tools in agriculture.

Impact (Socio-economic & Environmental)

  • Forge partnerships with agricultural technology firms and local cooperatives to enhance market entry in Spain and Europe.
  • Training workshops or webinars for farmers to familiarize them with the technology and illustrate its benefits.
  • Seling anonymized data.
  • Consulting and integration services.