Knowledge Update

Emerging Application of Artificial Intelligence in Global Food Security

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Introduction

Food security is a broad term used to describe an individual’s ability to have unrestricted access to an adequate quantity of nutritious and safe food. This food should meet the individual’s dietary and energy needs for an active and healthy life. Globally, the population of those within the food-insecure category has potentially nearly doubled in 2020 (FAO, 2020). This has continued to threaten the public health system and decrease human capital development. Adequate sustainable remedies for food insecurity must be put in place to attain a stable and reliable future (FAO, 2017). To achieve the sustainable development goal of a world free of hunger and malnutrition, emerging technologies must be incorporated to provide solutions to the global food crises. Artificial intelligence (AI) plays a vital role in stabilizing food security through massive data generation and utilization. Though at the budding stage of development and public adoption, the challenges that trail the application of AI have begun to be addressed.

Current Trend of Artificial Intelligence in Global Food Security

AI technologies allow the simulation of human intelligence in machines, capable of thinking, performing tasks intelligently, and acting rationally as humans. Of recent, AI technologies are known to demonstrate various human attributes such as creativity, emotion, sensing, perception, and even a good sense of judgment (Schuetz and Venkatesh, 2020; Benbya et al., 2021). The current trend and advances in technology have given rise to the use of AI in combating global food insecurity to protect approximately 800 million people globally from the scourge of hunger (Kunze, 2021). With the advent of AI technology, scientists and farmers can increase food security by accessing real-time soil conditions and implementing the necessary strategies for correcting nutrient deficiencies.

In addition, food scarcity can be averted through the use of AI as a massive amount of data is gathered and used to forecast developing situations affecting food supply (Gregory et al., 2020). This technology provides relevant information that will stabilize food supply, enhance rapid response time to price fluctuations, drought, disease outbreaks, poor weather conditions for food development, optimization of irrigation, and other global crop issues (Blasco et al., 2002; Chung et al., 2016; Chang and Lin, 2018; Talaviya et al., 2020). AI technology can improve the working conditions of farmers in rural communities by giving them access to technology and education awareness. It as well, increased crop yield that will in turn improve the economic conditions of the people. AI robotics and AI-enhanced drones have been implicated in crop planting, harvesting, farm fumigation, inspection, and security of workers (Arvind et al., 2017; Ahirwar et al., 2019). Despite the immense opportunities through AI technologies, the cognitive and rational framework of the technology, actual workers, and computer programmers are still required.

Challenges and Way Forward to the Use of AI Technology

Food security has been faced with significant difficulties like pandemics, social and military conflicts, drought, disease outbreaks, climate change, extreme weather conditions, the density of groundwater, and food wastage. Large-scale scientific interventions are currently underway to enhance the robustness and applicability of AI in global food security. Through this, adequate data which are quite difficult to gather will have real-time applicability in decision and policymaking. Though training and acquiring this technology can be expensive, the skills learned will add value and mobilize people out of extreme hunger and poverty. For global and rapid adoption by farmers, this technology could be programmed to be user-friendly and affordable to farmers.

Conclusion

There is a need to mitigate the current rise in global hunger through the use of emerging technologies. AI robotics and AI-enhanced drones can be improved to curtail the challenges mitigating global food security. Not only do these technologies improve food availability, but could be used to reduce human labor, monitor soil conditions, and correct nutrient deficiencies. Besides, farmers can utilize this technology to control pesticides and herbicides, enhance rapid response time to price changes, monitor and control plant disease outbreaks, forecast and mitigate food scarcity, and stabilize food supply.

References

Ahirwar, S., Swarnkar, R., Bhukya, S., Namwade, G. (2019). Application of drones in agriculture. Int. J. Curr. Microbiol. App. Sci., 8 (1), pp. 2500-2505.

Arvind, G., Athira, V.G., Haripriya, H., Rani, R.A. and Aravind, S. (2017). Automated irrigation with advanced seed germination and pest control. 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), 10.1109/tiar.2017.8273687

Benbya, H., Pachidi, S. and Jarvenpaa, S.L. (2021). Artificial Intelligence in Organizations: Implications for Information Systems Research. Journal of the Association for Information Systems 22(2), 1-25.

Blasco, J., Aleixos, N., Roger, J.M. Rabatel, G. and Molto, E. (2002). Robotic weed control using machine vision. Biosyst. Eng., 83 (2), 149-157.

Chang, C.L. and Lin, K.M. (2018). Smart agricultural machine with a computer vision-based weeding and variable-rate irrigation scheme. Robotics, 7, p. 38, DOI: 10.3390/robotics7030038

Chung, S., Choi, M., Lee, K., Kim, Y., Hong, S., Li, M. (2016). Sensing Technologies for Grain Crop Yield Monitoring Systems: a review. Journal of Biosystems Engineering 41 (4) (2016), pp. 408-417

Food and Agriculture Organization of the United Nations (FAO) (2017). The State of Food and Agriculture Leveraging Food Systems for Inclusive Rural Transformation 978-92-5-109873-8 (2017), pp. 1-181

Food and Agriculture Organization of the United Nations (FAO) (2020). Food-based dietary guidelines. In: Food and Agriculture Organization of the United Nations [online]. Rome. [Cited 28 April 2020]. www.fao.org/nutrition/ education/food-dietary-guidelines

Gregory, R. W., Henfridsson, O., Kaganer, E., & Kyriakou, H. (2020). The role of artificial intelligence and data network effects for creating user value. Academy of Management Review, 30(4), 13-47.

Kunze, Z. (2021). How Implementing AI Increases Food Security. The Borgen Project. [Accessed 19 April, 2022] https://borgenproject.org/ai-increases-food-security/

Schuetz, S. & Venkatesh, V. (2020). The Rise of Human Machines: How Cognitive Computing Systems Challenge Assumptions of User-System Interaction. Journal of the Association for Information Systems, 21(2), 460-482.

Talaviya, T., Shah, D., Patel, N., Yagnik, H. and Shah, M. (2020). Implementation of artificial intelligence in agriculture for optimization of irrigation and application of pesticides and herbicides. Artificial Intelligence in Agriculture, 4, 58-73.

 

Miracle Uwa Livinus is a Lecturer II in the Department of Biochemistry, School of Science and Information Studies at Skyline University Nigeria. He has M.Sc in Nutritional Biochemistry from Nasarawa State University.

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