Jan 20, 2025 · Section 2 provides a review of related studies that explore the application of AI and remote sensing technologies in agriculture, with a focus on pest and disease detection systems.

These studies highlight the integration of climate data, remote sensing, and machine learning techniques in predicting insect pest outbreaks, contributing to more effective pest...

Jul 3, 2025 · To explore this question, we selected articles based on their relevance to specific research questions, with emphasis on recent peer-reviewed studies that applied AI technologies to real-world …

To identify recent advances and SOTA on digital tools used for pest detection and prediction with the focus on quarantine diseases, a literature review of pest detection and prediction tools was done.

We then examine practical applications in India and worldwide, showing how AI-enabled drones improve pest forecasting and crop protection. The benefits improved yields, resource efficiency, and faster …

Significant studies have demonstrated the potential of remote sensing to detect damage caused by insects and ML-based models in predicting pest outbreaks and optimizing pesticide use.

Dec 6, 2024 · By scanning entire regions, remote sensing systems can detect emerging outbreaks (like locust swarms) much faster than ground reports, informing regional management strategies.

icial intelligence (AI) technology into pest and disease monitoring and control has emerged as a new solution. With its robust data processing and analytical capabilities, AI can achieve early identifica.

In this paper, artificial intelligence (AI) is used for the integration of machine learning (ML), deep learning (DL) and remote sensing technologies in order to increase precision pest prediction and control.

Remote Sensing of Forest Insect Disturbances: Current State and Future Directions (Senf et al., 2017): This review discusses the use of remote sensing in mapping and understanding insect outbreak …