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Agrivoltaic systems (APV) require monitoring infrastructures capable of collecting data from spatially heterogeneous crops across heterogeneous microclimatic conditions. Despite this need, the smart-monitoring dimension of APV research remains weakly structured. This scoping review examines how sensing architectures, spatial deployment strategies, acquisition workflows, and analytical outputs are reported in the literature, with the aim of supporting more reproducible and scalable monitoring systems for both research and production contexts. Following the PRISMA-ScR framework, 51 studies retrieved from Scopus and IEEE Xplore were analyzed and grouped into four thematic domains: microclimatic, agronomic, physiological, and proximal or remote sensing. The evidence shows that APV literature is more mature in defining which variables should be measured than in documenting how monitoring systems are implemented and scaled. In particular, information on node distribution and density, deployment logic, acquisition intervals, telemetry, calibration, storage continuity, and data-to-decision workflows proved to be still uneven. To address this gap, the review proposes a layered interpretation of APV monitoring systems focusing on field context, sensing design, spatial deployment, acquisition, analytics, and modeling, together with a minimum set of sensor-system descriptors for future studies. An economic-complexity framework is also introduced to classify monitoring strategies into three operational levels according to information depth, implementation burden, and scalability. This review reframes APV monitoring from a variable-centered to a system-architecture perspective, providing practical guidance for designing more scalable and goal-oriented smart monitoring systems.
Domenico et al. (Thu,) studied this question.