# Applications of Artificial Intelligence in Fire Safety of Agricultural Structures
## 2 Fire Safety in Agricultural Structures/Farms
### Future Prospects of AI in Agricultural Structures and Beyond  
Despite the limitations, it is anticipated that the future prospects of AI technologies in the prevention of fires in agricultural structures would be augmented by the global system for mobile (GSM), smart message service (SMS) [64], emerging networks such as 5G and beyond 5G, and unmanned aerial monitoring vehicles [65] for wide-area coverage, especially in smart cities [66]. In addition, AI and other technologies could mediate compliance with sustainable development goals in smart ecosystems/cities [67], megaprotets [68], distributed energy systems in the Internet of Things smart grid (IoT-SG) [69],Agriculture 4.0 [70], society 5.0 [54], and optimization of underground spaces [71] and fuel load design [72]. The accuracy of the fused sensors would be enhanced by the progress made in materials science and engineering. For example, [PERSON] et al. reported the successful development of precise and ultralow energy consumption graphene-based smoke sensors coated with ceramic microparticles [73]. The graphene-based sensors could prove useful in areas prone to fires, given the high thermal stability of carbon. Beyond AI and related technologies, the risk of fires could be offset by CO\({}_{2}\) sequestration using microalgae from agricultural biomass [70] to generate recycled water and biomass extracts to be used in industries. The recycled wastewater could be used in automatic fire extinguishers. Alternatively, such processes would help mitigate the adverse greenhouse effects associated with agricultural activities and mitigate global warming. The need to safely manage/recycle excess CO\({}_{2}\) generated from farms is critical because high CO\({}_{2}\) concentration elevates the risk of fire. In particular, consistent flow of CO\({}_{2}\) has been proven to generate significant static energy, which can cause a fire in the presence of pyrolysis gases [74]. This claim is supported by the fire hazard associated with animal manure [75]. From an agricultural point of view, [PERSON] et al. [76] note that intelligent technologies might prove useful in the development of realistic strategies for rearing and improvement of poultry and livestock. This is critical considering that advanced economies had resorted to the destruction of natural ecosystems, including the Amazon and the Mediterranean mountains [77], for livestock production [78]. The destruction of natural forests elevated the prevalence of forest fires [66; 78]. The intelligent information drawn from the farm-based system could complement sensors for fire safety. The need to develop and deploy AI solutions to mitigate the destruction of natural forests to create space for agriculture is supported by data models, which showed that activities impacted the mental and psychological wellbeing of communities living close to the forests. This translated to poor academic performance in China and human capital development in the future [79]. In contrast to [PERSON] [79], [PERSON] and [PERSON] [80] claimed that the burning of natural ecosystems to support agriculture impacts the chemical profile of the soils. For example, chemical analyses noted there was reduced calcium, nitrogen, and organic matter content and high phosphorous content. The soil analysis findings are in agreement with [PERSON] et al. 's [81] research on the effects of wildfires on ecosystems. Even though there are promising future prospects across different sectors, [PERSON] et al. [82] caution on the risks associated with embodied artificial intelligence on health and safety. There is a need to balance between automation benefits and the unforeseen hazards associated with intelligent technologies. Moreover, there will be a need to develop standards for Building Intelligence Quotient (BIQ) KPIs based on temperature control, security systems, HVAC systems, and lighting control [83].