PlantVillage NURU: Pest and Disease Monitoring Using Artificial Intellingence
PlantVillage NURU: Pest and Disease Monitoring Using  Artificial Intellingence
Technische Spezifikation
Technologiereifegrad
TRL 9
Farm Scale-Typen
Big scale, Small scale
Produktionssysteme
Offenes Feld
Techniktypen
Diagnose- und Erkennungstechniken, Monitoring Techniken
Anwendungsbereiche
Sonstige
Name der Firma
CGIAR
Herkunftsland
Vereinigte Staaten
Contact Person
dph14@psu.edu; J.LEGG@cgiar.org
Besondere Anforderung
Notwendigkeit einer besonderen Agrarlandschaft
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Beschreibung

This project expects to radically transform pest and disease monitoring by using artificial intelligence (AI), advanced sensor technology and crowdsourcing capable of connecting the global agricultural community to help smallholder farmers. It aims to increase the effectiveness of farm-level advice by leveraging three critical advances:

  1. The democratization of AI thanks to open access platforms such as Google’s TensorFlow.
  2. The miniaturization of technology allows affordable deployment.
  3. The development of massive communication and money exchange platforms such as M-Pesa that allow rural extension to scale as a viable economic model enabling last mile delivery in local languages.
Für mehr Informationen
Verwendete Pflanzen
  • Paprika
  • Mais
  • Kartoffel
Kulturen möglich
  • Paprika
  • Rosenkohl
  • Blumenkohl
  • Gurke
  • Kopfkohle
  • Porree
  • Salat
  • Zwiebel
  • Tomate
Verwendete Länder
  • Many
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Kostendetails

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Fallbeispiele/ Zusätzliche Informationen

The team annotated more than 200,000 cassava plant images, identifying and classifying diseases to train a machine learning model.

Arbeitsweise

Cloud based