Artificial intelligence and food security: swarm intelligence of AgriTech drones for smart AgriFood operations

Abstract

The Sustainable Development Goals (SDGs) present the emerging need to explore new ways of AgriFood production and food security as ultimate targets for feeding future generations. The study adopts a Design Science methodology and proposes Artificial Intelligence (AI) techniques as a solution to food security problems. Specifically, the proposed artefact presents the collective use of Agricultural Technology (AgriTech) drones inspired by the biomimetic ways of bird swarms. The design (artefact) appears here as a solution for supporting farming operations in inaccessible land, so as unmanned aerial devices contribute and improve the productivity of farming areas with limited capacity. The proposed design is developed through a scenario of drone swarms applying AI techniques to address food security issues. The study concludes by presenting a research agenda and the sectoral challenges triggered by the applications of AI in Agriculture.

Understanding the influential and mediating role of cultural enablers of AI integration to supply chain

“…Since its establishment as a relatively unknown academic discipline in the 1950s (Haenlein and Kaplan 2019;Lohr 2016), AI technologies have become a focal point of discussion in contemporary business (Dubey et al 2019;Sivarajah et al 2017;Spanaki et al 2020). International Data Corporation (IDC) predicts that global spending on AI will be nearly $98 Billion in 2023, more than double the $37.5 billion that was spent in 2019.…”

“…Anecdotal evidence indicates that AI can fundamentally reshape existing operational practices and tasks (Dubey et al 2019;Wamba-Taguimdje et al 2020;Wamba et al 2018) and that applications of AI will play an influential role in rebuilding and reconfiguring global operations and SC (Baryannis et al 2019b;Dwivedi 2019;Koh, Orzes, and Jia 2019;Queiroz et al 2019;Roscoe, Cousins, and Handfield 2019). Indeed, recent studies on AI have deepened our understanding of AI in the contexts of OSCM yet, scaling AI usage could encounter significant bottlenecks that remain under studied (Spanaki et al 2020). For example, failure to scale up from pilot implementations of AI applications can result in unclear business value as managers fail to estimate the potential impact of the pilot on the manufacturing processes and define success criteria accurately (Dogru and Keskin 2020).…”

“…optimisation and utilisation), to order delivery (i.e. logistics and route planning) ( Baryannis, Dani, and Antoniou 2019a;Ben-Daya, Hassini, and Bahroun 2019;Calatayud, Mangan, and Christopher 2019;Kamble and Gunasekaran 2020;Ivanov, Dolgui, and Sokolov 2019;Spanaki et al 2020). For example, AI is being used for vendor matching and strategic sourcing.…”

“…Fifth, numerous calls to action have been made for increased rigorous research on the influence of AI on SC performance (Baryannis, Dani, and Antoniou 2019a;Ben-Daya, Hassini, and Bahroun 2019;Calatayud, Mangan, and Christopher 2019;Dubey et al 2019;Sivarajah et al 2017;Spanaki et al 2020).…”

Circular and Lean Food Supply Chains

“…Since the industrial revolution in the 18th century, human society has undergone tremendous changes with the development of science and technology. In this process, the production technology is progressing rapidly, the scale of production is expanding constantly, and the production efficiency is advancing rapidly [5][6][7]. However, the progress of society and science and technology not only brings great economic benefits to people, but also has a tremendous impact on the environment.…”