# Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art
## 2 Artificial Intelligence Technologies for Smart Greenhouses  
### Historical Background of AI and ICTs in Agriculture  
Using AI and ICT in precision agriculture is not a new phenomenon. [PERSON] et al. [33] traced the use of ICTs in precision agriculture back to the 20 th century. In 1958, psychologist [PERSON] first formulated and proposed artificial neural networks as mathematical models of artificial intelligence whose mathematical structure attempted to mimic the functionality of biological neurons [34]. More specifically, in this first work, the well-known mathematical simulant of Perceptron, which is the first structure of the artificial neural network, was successfully employed to simulate how the human brain processes optical data and learns to recognize objects. The first structure of Perceptron is the main basis and architecture of the neural networks that have been extensively used in precision agriculture and other disciplines. Perception marked a historic key point in artificial intelligence research and commercial adoption with the coining of a phrase that embodied an entire field within AI. AI techniques have developed because of the complexity of the technological era, where a plethora of complex problems with a strongly non-linear nature cannot be solved using classical deterministic techniques, such as regression analysis and least-squared methods. Despite their novelty, it took four decades (until the early 1990s) for artificial neural net  
Figure 2: PRISMA diagram. works to be used widely in medical applications [35; 36; 37; 38; 39; 40; 41; 42], computational engineering [43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53], and precision agriculture. The historical analysis of ICTs in agriculture by [PERSON] et al. [33; 43; 44; 45; 46; 47; 48; 49; 51; 53] aligns with the broader trends in the global demand for AI, ML, and IoT, as noted by [PERSON] et al. [33]. On the downside, the true potential of AI and ICTs has not been fully exploited. The observation was validated by the fact that the transition of ICT technologies from computing to agriculture was delayed, considering the field of artificial intelligence was first proposed in 1955 and expanded in subsequent years [8]. During the early phases of precision agriculture, the key focus was improving crop yields and productivity by monitoring soil nutrients. However, the scope of precision agriculture has broadened to encompass artificial pollination using robot bees, autonomous operation of farm equipment, and optimization of different agricultural processes using bio-inspired algorithms [1; 54; 55]. The technology patterns demonstrate a peak in AL technologies from 2016 onwards. The convergence of new technologies in precision agriculture ushered in the Industry 4.0 revolution and the Internet of Plants (IoP) [56] (see Figure 3). The figure demonstrates how the availability of digital sensors and IoT can be used to collect environmental data, such as light, temperature, humidity, nutrition, and water, and then be stored in a cloud-based server, which can supply information for various farm work operations. However, there is growing criticism of AI technologies in agriculture due to their higher energy demand, high initial capital outlay, and variable accuracy [17]. These concerns have been discounted in view of the immense benefits of AI systems, including better crop yields, lower labor costs, and improved efficiency [57]. The current scope of AI and IoT in smart greenhouses encompasses artificial lighting using LEDs [58], air ventilation, water and nutrition pumps, plant nutrition, humidity control, moisture control, and temperature control subsystems with a unique combination  
Figure 3: Core attributes and the link between IoP and IoT [56]. of sensors and controls with distinct attributes [13]. The impact of weeds, pests, diseases, and water stress on crop yields validated the broadening scope of AI in precision agriculture. [PERSON] et al.