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.