Sensors (Jan 2024)

Real-Time AI-Assisted Push-Broom Hyperspectral System for Precision Agriculture

  • Igor Neri,
  • Silvia Caponi,
  • Francesco Bonacci,
  • Giacomo Clementi,
  • Francesco Cottone,
  • Luca Gammaitoni,
  • Simone Figorilli,
  • Luciano Ortenzi,
  • Simone Aisa,
  • Federico Pallottino,
  • Maurizio Mattarelli

DOI
https://doi.org/10.3390/s24020344
Journal volume & issue
Vol. 24, no. 2
p. 344

Abstract

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In the ever-evolving landscape of modern agriculture, the integration of advanced technologies has become indispensable for optimizing crop management and ensuring sustainable food production. This paper presents the development and implementation of a real-time AI-assisted push-broom hyperspectral system for plant identification. The push-broom hyperspectral technique, coupled with artificial intelligence, offers unprecedented detail and accuracy in crop monitoring. This paper details the design and construction of the spectrometer, including optical assembly and system integration. The real-time acquisition and classification system, utilizing an embedded computing solution, is also described. The calibration and resolution analysis demonstrates the accuracy of the system in capturing spectral data. As a test, the system was applied to the classification of plant leaves. The AI algorithm based on neural networks allows for the continuous analysis of hyperspectral data relative up to 720 ground positions at 50 fps.

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