Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring (Hardcover)

Haikuan Feng

ISBN 10: 372586814X / ISBN 13: 9783725868148

Published by Mdpi AG, 2026

About this Item

Hardcover. The integration of optical sensors and machine learning (ML) technologies has transformed agricultural monitoring, delivering precise, real-time insights into crop health, growth patterns, and environmental interactions. These sensors-spanning multispectral, hyperspectral, and RGB cameras-capture intricate spectral signatures that detect subtle physiological shifts in crops. When paired with ML algorithms, the resulting data streams yield actionable intelligence, informing key decisions in precision agriculture, yield forecasting, and disease control.This Reprint of the second edition of the Special Issue entitled "Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring" builds upon the foundational research established by prior studies in the field. Featuring 17 original research articles, this collection tackles key methodological challenges, including data imbalance, improved model transferability, and the fusion of multisensor data for resilient monitoring. Together, these works highlight the advancing capabilities of optical sensors in acquiring high-resolution, multidimensional datasets, which ML models exploit for advanced pattern recognition and predictive modeling. Beyond refining current approaches, the studies within this Reprint pave the way for emerging innovations, such as edge computing and AI-powered automation in agricultural ecosystems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9783725868148

Bibliographic Details

• Title: Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring (Hardcover)
• Publisher: Mdpi AG
• Publication Date: 2026
• Language: English
• ISBN 10: 372586814X
• ISBN 13: 9783725868148
• Binding: Hardcover
• Condition: new

About this title

Synopsis

The integration of optical sensors and machine learning (ML) technologies has transformed agricultural monitoring, delivering precise, real-time insights into crop health, growth patterns, and environmental interactions. These sensors-spanning multispectral, hyperspectral, and RGB cameras-capture intricate spectral signatures that detect subtle physiological shifts in crops. When paired with ML algorithms, the resulting data streams yield actionable intelligence, informing key decisions in precision agriculture, yield forecasting, and disease control.

This Reprint of the second edition of the Special Issue entitled "Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring" builds upon the foundational research established by prior studies in the field. Featuring 17 original research articles, this collection tackles key methodological challenges, including data imbalance, improved model transferability, and the fusion of multisensor data for resilient monitoring. Together, these works highlight the advancing capabilities of optical sensors in acquiring high-resolution, multidimensional datasets, which ML models exploit for advanced pattern recognition and predictive modeling. Beyond refining current approaches, the studies within this Reprint pave the way for emerging innovations, such as edge computing and AI-powered automation in agricultural ecosystems.