Greenhouse farming is essential in increasing domestic crop production in countries with limited resources and a harsh climate like Qatar. Smart greenhouse development is even more important to overcome these limitations and achieve high levels of food security. While the main aim of greenhouses is to offer an appropriate environment for high-yield production while protecting crops from adverse climate conditions, smart greenhouses provide precise regulation and control of the microclimate variables by utilizing the latest control techniques, advanced metering and communication infrastructures, and smart management systems thus providing the optimal environment for crop development. However, due to the development of information technology, greenhouses are undergoing a big transformation. In fact, the new generation of greenhouses has gone from simple constructions to sophisticated factories that drive agricultural production at the minimum possible cost. The main objective of this paper is to present a comprehensive understanding framework of the actual greenhouse development in Qatar, so as to be able to support the transition to sustainable precision agriculture. Qatar’s greenhouse market is a dynamic sector, and it is expected to mark double-digit growth by 2025. Thus, this study may offer effective supporting information to decision and policy makers, professionals, and end-users in introducing new technologies and taking advantage of monitoring techniques, artificial intelligence, and communication infrastructure in the agriculture sector by adopting smart greenhouses, consequently enhancing the Food-Energy-Water Nexus resilience and sustainable development. Furthermore, an analysis of the actual agriculture situation in Qatar is provided by examining its potential development regarding the existing drivers and barriers. Finally, the study presents the policy measures already implemented in Qatar and analyses the future development of the local greenhouse sector in terms of sustainability and resource-saving perspective and its penetration into Qatar’s economy.

This paper presents a novel high-level centralized control scheme for a smart network of greenhouses integrated microgrid (NGIM) forming a smart small power grid in the context of smart grids. The main purpose is to present an innovative control strategy-based coordinated model predictive control (MPC) that considers fluctuations of stochastic renewable sources as well as weather conditions. A comprehensive finite-horizon scheduling optimization model is formulated to optimally control the operation of the NGIM, which integrates both forecasts and newly updated information collected from the available sensors at the network level. The model can be implemented as a supervisory control and energy management system for the NGIM to manipulate the indoor climate and optimize the crop production. The cooperation is reached through a bidirectional communication infrastructure, where a master central controller is available at the network level and is in charge of coordinating and managing various control signals. An MPC-based algorithm is used for the future operation scheduling of all subsystems available in the NGIM. The MPC strategy is tested through a case study where the influences of climate data on the operation of the NGIM are analyzed via numerical results.

This systematic review synthesizes passive and passive-first cooling strategies for greenhouses in hot–arid climates, organizing evidence across four domains: Airflow & Ventilation, Shading & Radiative Control, Thermal Storage & Ground Coupling, and Structural Design & Geometry. Drawing on the project corpus, we analyze 10–13 distinct techniques including ridge and side natural ventilation, windcatchers and solar chimneys, external shade nets, NIR-selective and transparent radiative-cooling films, and dynamic PV shading; earth-to-air heat exchangers (EAHE/GAHT), rock-bed sensible storage, phase-change materials (PCMs), and sunken or buried envelopes; as well as roof slope and shape, span number, and orientation. Across studies, cooling outcomes are reported as peak or daytime indoor air temperature reductions, defined relative either to outdoor conditions or to a control greenhouse, with the reference frame and temporal aggregation specified in the synthesis. Typical outcomes include ≈3–7 °C daytime reduction for optimized ventilation, ≈2–4 °C for shading and spectral covers while preserving PAR, ≈5–7 °C intake cooling for EAHE with winter pre-heating, and up to ≈14 °C peak attenuation for rock-bed storage under favorable conditions. Structural choices consistently amplify these effects by sustaining pressure head and limiting thermal heterogeneity. Performance is strongly context-dependent—governed by wind regime, diurnal amplitude, dust and UV exposure, and crop-specific light and temperature thresholds—and the most robust results arise from stacked, site-specific designs that combine skin-level radiative rejection, buoyancy-supportive geometry, and ground or latent buffering with minimal active backup. Smart controllers that modulate vents, shading, and targeted fogging or fans based on VPD or temperature differentials improve stability and reduce water and energy use by engaging actuation only when passive capacity is exceeded. We recommend standardized composite metrics encompassing temperature moderation, humidity stability, PAR availability, and water and energy use per unit yield to enable fair cross-study comparison, multi-season validation, and policy adoption. Collectively, the synthesized techniques provide a practical palette for improved greenhouse climate management under hot and arid conditions.