## 5 New Technologies in Greenhouses
### Automation of Greenhouse
This system, which improves the traditional hydroponic method, includes the use of robots to monitor and control elements important for healthy plant growth. The integration of automatic control and monitoring technology via smartphone allows growers to maintain ideal pH levels and other critical factors efficiently and user-friendly. The application of these robots in greenhouses guarantees an optimized growing environment, promoting more robust and consistent plant growth, in addition to facilitating the management of essential parameters. Management software integrates all automated systems into a centralized platform, allowing real-time control and data analysis. These platforms use artificial intelligence algorithms to analyze collected data and provide insights into greenhouse performance. Managers can monitor all aspects of the operation and make informed decisions to optimize cultivation and resources [287]. The study by [PERSON] et al. [288] evaluates the effectiveness of integrated soil and crop management practices with the aim of improving productivity and environmental outcomes in an intensive greenhouse tomato system in the Yangtze River Basin, China. The results indicate that the integrated soil-crop system management treatment led to a significant increase in fruit yields, ranging from 13.4% to 37.3% compared to other traditional practices. Furthermore, this integrated approach has resulted in lower greenhouse gas emissions, highlighting its benefits not only for agricultural productivity but also for environmental sustainability. Internet of Things (IoT) devices enable communication between sensors and control systems, providing remote monitoring and control of the greenhouse. These devices collect data in real-time and transmit it to a central platform, facilitating the integrated management of the greenhouse environment [177]. The article by [PERSON] et al. [289] proposesthe StrawberryTalk platform, an innovative Internet of Things (IoT) solution for image-based disease detection in strawberries. The platform uses wall-mounted monitoring cameras that capture images of plants and eliminate blurred photos caused by wind, significantly improving accuracy in disease detection. With this technology, the system can identify all infected plants with high accuracy, providing an effective method for monitoring the health of strawberry crops and facilitating early intervention to control the spread of disease. Artificial intelligence (AI) algorithms analyze sensor data to predict future conditions and automatically adjust control systems. AI can be used to predict irrigation needs, adjust lighting, and control climate based on historical data and weather patterns [266]. The study of [PERSON] et al. [290] proposes an intelligent system for frost prediction in greenhouses, integrating Internet of Things (IoT) technologies and hybrid Artificial Intelligence (AI) methods. Artificial Neural Networks (ANN) and a fuzzy control system are used to predict indoor temperatures and trigger water pump output levels for anti-frost irrigation control. The system consists of a climatological station equipped with ANN and fuzzy associative memory (FAM) for ecological irrigation control. ANNs provide an indoor temperature prediction with an efficiency greater than 90%, validated by the coefficient of variance (\(R^{2}\)) analysis method. This intelligent system significantly improves frost forecasting and irrigation management in greenhouses, ensuring an ideal environment for plant growth. Drones equipped with cameras and sensors monitor large areas of greenhouses, providing a detailed view of the state of plants and the environment. These drones capture images and data that are analyzed to detect problems such as pests or diseases [285]. The article discusses the use of hexarotor drones in greenhouse environments, exploring their application possibilities. Drones, or unmanned aerial vehicles (UAVs), are increasingly used for direct or indirect data collection. GPS navigation cannot be applied indoors.