Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art

This article presents the current state-of-the-art research on applying artificial intelligence (AI) technology in smart greenhouses to optimize crop yields, water, and fertilizer use efficiency, reduce pest disease, enhance agricultural sustainability. The key technologies of interest were robotic systems for pesticide application, irrigation, harvesting, bio-inspired algorithms automation greenhouse processes, energy management, machine path planning operation UAVs (unmanned aerial vehicles), resolution scheduling problems, image signal processing disease diagnosis. Additionally, review investigated cost benefits various energy-management AI-based energy-saving technologies, integration photovoltaics dynamic pricing based real-time time-of-use metrics, LoRa, Wi-Fi, Bluetooth, ZigBee, mobile, RFID (radiofrequency identification) technologies. established that commercially viable AI agriculture had increased exponentially. For example, irrigation soil application enabled farmers realize higher returns investment gross above cost, resource efficiency. Similarly, detection techniques led early diagnosis powdery mildew. precise robots was supported by light imaging, detection, ranging (LIDAR) optical electro-optical cameras place traditional GPS (geographic positioning systems) which are prone errors. However, critical challenges remained unresolved, including disparities between development (R&D) innovations commercialization, use, tradeoff accuracy computational speeds, gaps Global North South. In general, value this is it surveys literature maturity level offers a picture how far have successfully been applied what can be done their usability.