The Impact of AI and Robotics on the sustainability of Vertical Farming
Vertical farming has been a promising solution to global challenges, resource scarcity, environmental degradation, and food security. This review looks at artificial intelligence (AI) and Robotics as transformative elements for improving the environmental and economic sustainability of vertical farming. On the other hand, precision irrigation for smart irrigation, energy-efficient lighting, and climate control systems made possible with AI-driven optimization allow for a huge reduction in resources like water, energy, and land usage for instance. Automating laborious chores for example, planting, harvesting, and maintenance, robotics help to decrease operation costs and raise production efficiency. AI systems also help to reduce environmental impacts thanks to process optimization for the delivery of nutrients and reduced use of pesticides using improved pest detection and management technologies. Renewable energy sources are integrated to increase vertical farming operations’ sustainability further, and life cycle assessments show the potential for energy use to be balanced with sustainable practices. High initial costs, technological barriers, and concerns about energy consumption present challenges, but technological advances in AI and robotics, as well as support in public policy, provide a way out. This review highlights the need for further research, investment, and collaboration to make the most of the combined potential of AI and robotics to transform vertical farming into an essential element of sustainable agriculture to create and grow food for an ever-increasing global population without using up precious environmental resources.
Authors
- Ruqia Syed
- Roshdy S. Youssif
- Angela Joe
- Yunpeng Zhang (ORCID: https://orcid.org/0000-0003-0823-1594)
- Jian Cao (ORCID: https://orcid.org/0000-0002-0036-9436)
- Pei Baolei
Institutions
- Huaiyin Institute of Technology (CN)
Publication Details
- Journal
- Journal of agriculture and biology.
- Published
- 2025-03-27
- DOI
- https://doi.org/10.55627/agribiol.003.01.1198
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.75
Funders
- Huaiyin Institute of Technology