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April 21, 2026Scientific ReportsOpen Access

AI-driven hybrid framework for enhanced pest detection and resource optimization using graph networks and deep reinforcement learning

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Authors

BSBasu Dev ShivahareGSGambhir SinghRNRahat Naz

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Overview

Demonstrates enhanced pest detection and resource optimization in agriculture, suggesting a new AI-driven framework.

Key Points

  • The research aims to develop an AI-driven framework for improved pest detection and resource management in agriculture.
  • Introduced a framework combining Graph Convolutional Networks, AutoML, and Deep Reinforcement Learning.
  • Utilized datasets from IoT Smart Farm and Precision Agriculture for testing performance.
  • Implemented spatial and temporal data analysis for dynamic optimization of resources and pest control.
  • Stability in yield improved by 21.7% compared to baseline strategies.
  • Accuracy in crop health assessment improved by 96.8%.
  • Accuracy in pest detection improved by 95.3%.

Cite This Study

Shivahare et al. (2026) studied this question.

synapsesocial.com/papers/69e713fdcb99343efc98d62bhttps://doi.org/10.1038/s41598-026-47987-5
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