Adaptive Artificial Intelligence Technology for the Food Industry
Published 03 April, 2024
In recent years, the food and beverage industries have been rapidly adopting AI to meet the demand and supply. High speed, reliability and informed decision-making are some of the advantages of employing AI tools and software in the global food industry. Various fields of AI such as machine learning, image recognition and machine vision enable the food industry in achieving better results.
In the agricultural sector, AI is used to advance the traditional farming practices starting from sowing to providing necessary market insight. Once the raw materials are obtained, AI is used in the food processing industry for supply chain management, quality control and waste management. The optical sensing technologies in AI can be used to sort and package food products. Furthermore, the increasing attention on sanitation practices in food industries will only fuel the adoption of AI to monitor health and hygiene protocols.
The integration of AI in production processes extends beyond automation; it includes leveraging customer data to refine tastes and preferences. This data can be useful in developing new flavours and increasing the variety of food products. Artificial neural networks are particularly advantageous for supply chain optimisation. For the retail food sector, AI can help in transportation and inventory management and in reducing waste. Apart from that, it also plays a major role in food recommendation engines, chatbots and apps for food ordering and delivery and self-ordering kits and robotics service in restaurants.
At the management level, AI and machine learning algorithms can analyse key trends and forecast the market. AI’s capability to deliver automated yet efficient services is crucial to meet customer satisfaction. In the future, AI can be implemented more widely in smart farming with hyperspectral cameras.
To capitalize on AI’s potential in the food industry, there is a need to develop cost-efficient models and user-friendly algorithms. Hence, more research should be undertaken to analyse and understand AI's challenges and create more affordable models for adoption.
Related topics of interest include but are not limited to
- Management of food safety using AI
- Role of robotics in the food industry
- Applications of AI in the agricultural sector
- Prospects of AI for food processing industries
- Trends in an expert system for the global food industry
- Impact of AI on workforce management in the food industry
- Global investments affecting the application of AI in the food industry
- Effects of implying computer vision in agriculture
- AI for transportation and waste management in the food industry
- Industry 4.0 and its influence in the food industry
Important deadlines:
Submission close: August 30 2024
Publication date: March 2025
Submission instructions:
Please read the Guide for Authors before submitting. All articles should be submitted online; please select SI: Artificial Intelligence.
Special Issue Editors
- Mohammad Nishat Akhtar
School of Aerospace Engineering, Universiti Sains Malaysia, Malaysia.
Email: iresearchertech2023@gmail.com
- Muhammad Rafiq Khan Kakar
Department of Architecture, Wood and Civil Engineering, Bern University of Applied Sciences (BFH), Switzerland.
Email: muhammad.kakar@bfh.ch
- Associate Professor Asha Crastaa
Department of Mathematics, Centre for Advanced Learning, Mangalore Institute of Technology & Engineering, India.
Email: hodmat@mite.ac.in
Target journals:
Animal Nutrition， Food Physics， Grain & Oil Science and Technology，The Crop Journal
