The convergence of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) has strengthened smart greenhouse management by enabling continuous environmental monitoring, automated control, and more informed use of agricultural resources. This review examines and synthesises research on IoT- and WSN-enabled greenhouse systems published between 2015 and 2026. Peer-reviewed studies retrieved mainly from IEEE Xplore and Google Scholar were analysed across sensing technologies, system architecture, communication methods, network topology, control approaches, cloud–edge computing, energy management, and performance assessment. The reviewed studies show that achieving strong performance in one area often requires compromises elsewhere, particularly among communication range, energy demand, reliability, scalability, latency, computational capacity, and cost. ZigBee is particularly suitable for low-power, short-range mesh networks, whereas LoRa better supports wider-area deployments. Clustered and hybrid network structures offer favourable scalability and reliability, while cloud–edge architectures combine scalable analytics with rapid local processing. Intelligent control improves prediction, adaptability, and resource use, whereas renewable energy and intelligent energy management can reduce reliance on conventional power sources. Practical deployment, however, remains constrained by sensor reliability, energy limitations, communication instability, interoperability, cybersecurity risks, and limited long-term validation. Future studies should place greater emphasis on energy-autonomous systems, edge intelligence, secure and interoperable architectures, digital twins, adaptive autonomous control, and realistic evaluation of emerging communication technologies for greenhouse applications. Overall, future smart greenhouses are likely to depend increasingly on integrated architectures that combine energy efficiency, adaptive control, reliable connectivity, and security to support sustainable operation.