Integrating IoT sensors and machine learning for sustainable precision agroecology: enhancing crop resilience and resource efficiency through data-driven strategies, challenges, and future prospects

Integrating IoT sensors and machine learning for sustainable precision agroecology: enhancing crop resilience and resource efficiency through data-driven strategies, challenges, and future prospects

Abstract The integration of Internet of Things (IoT) sensors and Machine Learning (ML) technologies has transformed precision agriculture by enabling data-driven, adaptive, and efficient farming practices. IoT sensors provide continuous, high-resolution monitoring of critical agricultural parameters...

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Bibliographic Details
Main Authors: Val Hyginus Udoka Eze, Esther Chidinma Eze, George Uwadiegwu Alaneme, Pius Erheyovwe BUBU, Ezekiel Oluwaseun Ejiofor Nnadi, Michael Ben Okon
Format: Article
Language:English
Published: Springer 2025-05-01
Series:Discover Agriculture
Subjects:
Precision Agriculture
IoT Sensors
Machine Learning
Sustainable Farming
Data-Driven Decision-Making
Online Access:https://doi.org/10.1007/s44279-025-00247-y
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https://doi.org/10.1007/s44279-025-00247-y

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