Smart Sensing Systems For Agricultural Plant Health Monitoring: Current State and Prospects

Abstract

ABSTRACT Timely and reliable assessment of plant health is essential for resilient and sustainable agriculture, yet diagnostic practice remains divided between accurate but laboratory‐bound assays and emerging field‐deployable technologies. Herein, we adopt a plant‐centric and systems‐level perspective to synthesize advances in smart sensing for plant health monitoring reported between 2000 and 2026. Rather than surveying individual devices in isolation, we organize the literature around how sensing technologies are fabricated, integrated, and translated into actionable agronomic insights. Our synthesis reveals a clear shift toward multimodal, minimally invasive sensing architectures that combine material and fabrication innovations with contact and non‐contact modalities spanning organ, canopy, and landscape scales. We find that the most impactful progress arises not from individual sensors alone, but from integrated pipelines that couple sensing hardware with edge intelligence, cross‐scale data fusion, and explainable analytics. Furthermore, persistent barriers, including calibration transfer, long‐term stability, power autonomy, dataset bias, and cybersecurity, continue to impede widespread adoption. Based on these findings, we outline design principles and research priorities needed to accelerate translation, emphasizing standardized validation against biological benchmarks, energy‐autonomous and environmentally responsible sensor systems, and artificial intelligence (AI) frameworks capable of robust generalization across crops and environments. Looking ahead, we argue that plant health monitoring will increasingly be defined by closed‐loop systems that directly link plant physiological or pathological signals to adaptive management, positioning smart sensing as a cornerstone of data‐driven and climate‐resilient agriculture.

Plant phenotyping relevance

植物の健康状態・生理・病理シグナルを対象とするスマートセンシング手法を、統合、検証、校正、データ解析の観点から体系的にレビューしており、植物フェノタイピング手法が中心である。

Code and data availability

The supplied blocks are from a review article synthesizing literature on smart sensing for plant health monitoring. No public phenotype/trait datasets, plant images, sensor data, author analysis code, trained models, or supplements containing such assets are mentioned. All referenced sensors, datasets, and tools belong

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