Hydroponic crop production in smart greenhouses requires accurate nutrient monitoring and reliable control, especially in recirculating systems. This review critically examines sensing principles, data acquisition, control strategies, actuation, feedback, and system integration. Electrical conductivity (EC) and pH are widely used for dosing, but EC cannot quantify individual nutrient concentrations. Emerging technologies include ion-selective electrodes, solid contact and field effect sensors, optical spectroscopy, multi-sensor arrays, and Internet of Things platforms. Their deployment remains constrained by interference, drift, fouling, reference instability, calibration demands, and matrix effects. Control approaches range from threshold-based dosing and EC/pH feedback to proportional–integral–derivative, rule-based, ion-specific, and model-based strategies. Published ion-specific replenishment and hybrid EC–ion studies demonstrate feasibility under tested conditions. However, differences in nutrient formulations, study duration, and error definitions limit conclusions about commercial control accuracy. This review proposes an integrated framework linking sensing, decision making, actuation, and verification, with performance assessed at analytical, temporal, operational, and system/control levels. Future research should prioritize reliable multi-ion sensing, automated data quality checks, delivered dose verification, safe operation during faults, and communication between components. Validation should include complete crop cycles, maintenance, fault recovery, and independent sites. These requirements support evaluation of nutrient use efficiency, operational reliability, and scalability across crops and hydroponic systems under realistic production conditions.

Vertical farming requires precise monitoring and control of environmental conditions to support consistent year-round crop production and efficient resource utilization. However, multilayer cultivation creates spatial, vertical, and temporal variations in temperature, humidity, CO₂, airflow, and lighting, complicating the maintenance of uniform growing conditions. This review analyzed 70 recent studies on remote monitoring and control in smart vertical farms, focusing on environmental variability, sensing infrastructure, sensor-node placement, communication architectures, actuator operation, and control strategies. Studies were classified into five thematic areas: sensing and monitoring, automation and control, environmental and climate control, IoT and wireless communication, and CFD-based analysis. Recent research advances include the development of spatially distributed sensing networks for monitoring and the adoption of adaptive, data-driven, model-based, and hierarchical methods for control. Nevertheless, significant research gaps persist, such as the lack of standardized sensor-placement strategies, limited integration of actuator-level operational data, insufficient long-term commercial-scale validation, and limited transferability of monitoring and control frameworks across facility configurations. Many methods remain adapted from greenhouse systems rather than specifically designed for vertical farms. Addressing these gaps is essential for improving the reliability, energy efficiency, and scalability of smart vertical farm systems.