# Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art
## 2 Artificial Intelligence Technologies for Smart Greenhouses
### Robotics and Algorithms for Precision Agriculture and Smart Greenhouses
#### 2.4.1 Role of AI Technologies and Biological Pesticide Compounds in IPM
Current research does not provide clear-cut reasons why biological agents have not outpaced chemical control agents in the market. On the one hand, [PERSON] et al. attributed the phenomenon to risk aversion among farmers coupled with an unfavorable marketing environment for biological pesticides in China [121]. On the other hand, the low adoption was linked to the variable effectiveness of the biological control agents relative to chemical pesticides, and the longer duration needed to secure financial returns following years of R&D investment [123]. The operational challenges highlighted by leading biological pesticide manufacturers supported this narrative. From another dimension, the limited uptake of biological pesticides could be linked to adopting a wide range of complementary interventions, including crop diversification and growing advocacy for pesticide-free agriculture [124,125]. Statistics compiled by the EU confirmed that farmers were assimilating pesticide-free agriculture policies; this was evident from the consistent reduction in the level of pesticide dependence--the most notable improvement was observed in the Czech Republic, where pesticide use reduced by 38% between 2011 and 2020. A similar downward trend was observed in Denmark, Portugal, and Romania, with each country recording a 20% drop in pesticide demand [120]. The pesticide use patterns documented by [120] were in agreement with [PERSON] et al. [80], who documented a marginal change in pesticide use from the 1990s to the late 2000s as a result of the stringent regulatory measures imposed by the EU, including Directive 2009/128/CE. A contrary trend was observed in Latvia and Austria, where pesticide demand increased by 77% and 61%, respectively. In contrast to the statistics provided by Eurostat [120], [PERSON] noted that EU farmers were locked into pesticide use [126], creating an eternal lose-lose situation for all stakeholders. The lose-lose situation was evident from the declining genetic diversity, impaired crop yields due to lower insect-assisted pollination, and the destruction of local ecosystems. The contrasting observations about pesticide use and the rates and barriers to biopesticide market entry affirm the complexity of phasing out chemical pesticides from the market. On a positive note, the scenario is forecasted to change with the gradual introduction of AI technologies in pest management. [PERSON] et al. deployed cloud-based solutions and CNN networks to target red spider, flax budworm, cicadellidae, aphids, and flea beetles [14]. Early detection of pesticides usingAI technologies would facilitate timely responses using AI and IoT infrastructure. The observations made by [PERSON] et al. [14] were corroborated by [PERSON] et al., who integrated both AI and IoT systems in developing a new and intelligent system of IPM (see Figure 5). The IPM system shown in Figure 5 shows the use of sensors and image data during the data collection phase, which are then stored in a database and processed within the same server, using analytics to provide useful outputs, such as hotspot detection and other models that can aid decision-making on the farm. The system was > 90% effective in managing thrips and whitfely [57]. In both cases, intelligent IPM techniques had the potential to reduce pesticide usage, resulting in significant cost savings. However, the short-term investment costs are a major impediment [121, 123]. The observations made by [60, 62] reflect the broader concerns about the future of AI in agriculture highlighted by [PERSON] et al. [6]. However, in the latter case, the researchers argued the challenge might be addressed by developing affordable interventions in open-source platforms to ensure higher penetration among farmers. The proponents of intelligent IPM coupled with biopesticides argue that there were immediate short-term benefits. For example, the crop yield was higher with intelligent and biological IPM compared to traditional chemical pesticides [116].