A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics

Using smart data analytics and IoT-driven sensor networks to enhance precision agriculture, the paper provides a whole framework for real-time Crop Monitoring and yield optimization. Using IoT-Driven Sensor Networks (CM-IoT-SN), Crop Monitoring aims to provide farmers practical data for maximizing yields and improving crop condition. Many times, existing precision agricultural technologies suffer from flaws such as poor data granularity, delayed feedback, and the difficulty to provide real-time monitoring across large agricultural fields. These weaknesses lower crop productivity and lead to less than perfect decision-making. To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. Results reveal that this approach not only increases crop productivity however additionally reduces resource waste, therefore providing a sustainable substitute for modern agriculture.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-05-23
DOI
https://doi.org/10.1051/shsconf/202521601044/pdf
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics

Springer Link (Chiba Institute of Technology)
Smart Agriculture and AI
article

A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics

article en

Abstract

Using smart data analytics and IoT-driven sensor networks to enhance precision agriculture, the paper provides a whole framework for real-time Crop Monitoring and yield optimization. Using IoT-Driven Sensor Networks (CM-IoT-SN), Crop Monitoring aims to provide farmers practical data for maximizing yields and improving crop condition. Many times, existing precision agricultural technologies suffer from flaws such as poor data granularity, delayed feedback, and the difficulty to provide real-time monitoring across large agricultural fields. These weaknesses lower crop productivity and lead to less than perfect decision-making. To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. Results reveal that this approach not only increases crop productivity however additionally reduces resource waste, therefore providing a sustainable substitute for modern agriculture.

Springer Link (Chiba Institute of Technology)
Zero hunger
Openalex Percentile: Top 27%
Smart Agriculture and AI
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A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS