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Climate variability increasingly affects agricultural systems, intensifying the need for high-resolution and continuous environmental monitoring. This paper proposes an innovative IoT-based architecture designed to capture climate-driven variability through integrated multi-parameter sensing, hybrid low-power communication and data processing. Unlike existing solutions that focus on isolated measurements or controlled environments, the system combines atmospheric and soil parameters into a unified data pipeline and computes a real-time composite climate-stress index. The architecture incorporates long-range wireless communication for field-scale deployments, a cloud-based ingestion and storage workflow optimized for environmental time-series, and interactive dashboards for real-time exploration. Experimental validation across two agricultural sites over a six-month period demonstrates the system’s ability to detect compound climatic anomalies such as sustained high humidity and reduced radiation, highlighting its utility for climate-aware agricultural decision-making. The integrated design and real-time risk modelling differentiate the proposed system from existing monitoring platforms and enhance its relevance for climate agricultural management.
Pintilie et al. (Fri,) studied this question.