About this Research Topic
In order to deliver prompt, high-quality services tailored to individual customer needs, the food industry relies on flexibility and productivity, as well as sustainability.
Digital solutions are designed to support this process through the digital transformation of production, buildings, and infrastructure, and facilitate the transition to Industry 5.0. Implementation of digital solutions to agriculture and food production allows to fit both goals of cost-effective and sustainable development of this industry in terms of climate-friendliness and food security. Food production is understood to have a big digitalization potential worldwide today.
Our aim is to collate research on digital twins and other intelligent solutions for the food industry. These tools enable the prediction and simulation of food-processing objects using various AI technologies and information sources. Driving AI services to the food industry will make the process of food manufacturing more adaptive to society, climate, and market needs, improve the efficiency and productivity of the whole process, and mitigate the environmental damage from agriculture and food consumption.
This research will boost the rapid digitization and scientific advancement of the food industry while ensuring the safety and effectiveness of global food production.
We encourage submissions that address crop model simulation for climate change response and food security, as well as other applications. Potential areas of focus include, but are not limited to:
• Overview of digital tools for simulation in the food industry.
• Methods and tools for data harvesting and acquisition in the food industry.
• Models of processes and objects in the food industry.
• Solutions and implementations of digital transformation in the food industry, including agricultural IoT.
• Digitalization of agriculture, food processing, food logistics, and distribution.
• Digital tools to increase the productivity of food systems, mitigate the impact, and improve their adaptation to climate change, as well as to measure the synergies and trade-offs between these three aims.
• Algorithms and methods for crop simulation.
• Harvest parameters control and prediction.
• Decision-making services for agriculture.
Digital solutions are designed to support this process through the digital transformation of production, buildings, and infrastructure, and facilitate the transition to Industry 5.0. Implementation of digital solutions to agriculture and food production allows to fit both goals of cost-effective and sustainable development of this industry in terms of climate-friendliness and food security. Food production is understood to have a big digitalization potential worldwide today.
Our aim is to collate research on digital twins and other intelligent solutions for the food industry. These tools enable the prediction and simulation of food-processing objects using various AI technologies and information sources. Driving AI services to the food industry will make the process of food manufacturing more adaptive to society, climate, and market needs, improve the efficiency and productivity of the whole process, and mitigate the environmental damage from agriculture and food consumption.
This research will boost the rapid digitization and scientific advancement of the food industry while ensuring the safety and effectiveness of global food production.
We encourage submissions that address crop model simulation for climate change response and food security, as well as other applications. Potential areas of focus include, but are not limited to:
• Overview of digital tools for simulation in the food industry.
• Methods and tools for data harvesting and acquisition in the food industry.
• Models of processes and objects in the food industry.
• Solutions and implementations of digital transformation in the food industry, including agricultural IoT.
• Digitalization of agriculture, food processing, food logistics, and distribution.
• Digital tools to increase the productivity of food systems, mitigate the impact, and improve their adaptation to climate change, as well as to measure the synergies and trade-offs between these three aims.
• Algorithms and methods for crop simulation.
• Harvest parameters control and prediction.
• Decision-making services for agriculture.
Keywords: Adaptation, Digital model, Simulation tools, Digital twin, Industry 4.0, Artificial intelligence
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
