Sustainable AI-based production agriculture: Exploring AI applications and implications in agricultural practices

Abstract

In general, agriculture plays a crucial role in human survival as a primary source of food, alongside other sources such as fishing. Unfortunately, global warming and other environmental issues, particularly in less privileged nations, hamper the Agricultural sector. It is estimated that a range of 720 to 811 million individuals experienced food insecurity. Today's agriculture faced significant difficulties and obstacles, as do the surveillance and monitoring systems (climate, energy, water, fields, works, cost, fertilizers, diseases, etc.). The COVID-19 pandemic has exacerbated the susceptibilities and insufficiencies inherent in worldwide food systems. Current agricultural practices tend to prioritize productivity and profitability over environmental conservation and long-term sustainability. To establish sustainable agriculture capable of meeting the needs of a projected ten billion people in the next 30 years, substantial structural and automation changes are required. However, these obstacles can be overcome by employing smart technologies and advancing Artificial Intelligence (AI) in agricultural operations. AI is believed to contribute to global sustainability goals in multiple sectors, particularly in the incorporation of renewable energy. It is anticipated that AI will revitalize both existing and new agricultural fields by retrofitting, installing and integrating automatic devices and instruments. This paper presents a comprehensive review of the most promising and novel applications of AI in the agriculture industry. Furthermore, the role of AI in the transition to sustainability and precision agriculture is investigated.