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Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics

Author

Listed:
  • Saurabh Sharma

    (Department of Basic and Applied Sciences, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

  • Vijay Kumar Gahlawat

    (Department of Basic and Applied Sciences, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

  • Kumar Rahul

    (Department of Basic and Applied Sciences, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

  • Rahul S Mor

    (Department of Food Engineering, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

  • Mohit Malik

    (Department of Basic and Applied Sciences, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

Abstract

The agri-food sector is an endless source of expansion for nourishing a vast population, but there is a considerable need to develop high-standard procedures through intelligent and innovative technologies, such as artificial intelligence (AI) and big data. This paper addresses the research concerning AI and big data analytics in the food industry, including machine learning, artificial neural networks (ANNs), and various algorithms. Logistics, supply chain, marketing, and production patterns are covered along with food sub-sector applications for artificial intelligence techniques. It is found that utilization of AI techniques and the intelligent optimization algorithm also leads to significant process and production management. Thus, digital technologies are a boon for the food industry, where AI and big data have enabled us to achieve optimum results in realtime.

Suggested Citation

  • Saurabh Sharma & Vijay Kumar Gahlawat & Kumar Rahul & Rahul S Mor & Mohit Malik, 2021. "Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics," Logistics, MDPI, vol. 5(4), pages 1-16, September.
    • Handle: RePEc:gam:jlogis:v:5:y:2021:i:4:p:66-:d:643932
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    References listed on IDEAS

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    Cited by:

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    2. El Bhilat, El Mehdi & El Jaouhari, Asmae & Hamidi, L. Saadia, 2024. "Assessing the influence of artificial intelligence on agri-food supply chain performance: the mediating effect of distribution network efficiency," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Ioan Mihail Savaniu & Alexandru-Polifron Chiriță & Oana Tonciu & Magdalena Culcea & Ancuta Neagu, 2023. "Neural-Network-Based Time Control for Microwave Oven Heating of Food Products Distributed by a Solar-Powered Vending Machine with Energy Management Considerations," Energies, MDPI, vol. 16(19), pages 1-22, October.
    4. Andreea-Alina CORNEA, 2023. "Big Data in Food Industry: A Technical Summary of Modern Approaches Used in Data Extraction," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 27(2), pages 25-35.
    5. Ramakrishnan Ramanathan & Yanqing Duan & Tahmina Ajmal & Katarzyna Pelc & James Gillespie & Sahar Ahmadzadeh & Joan Condell & Imke Hermens & Usha Ramanathan, 2023. "Motivations and Challenges for Food Companies in Using IoT Sensors for Reducing Food Waste: Some Insights and a Road Map for the Future," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    6. Johannes Hangl & Viktoria Joy Behrens & Simon Krause, 2022. "Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study," Logistics, MDPI, vol. 6(3), pages 1-22, September.
    7. Mohit Malik & Vijay Kumar Gahlawat & Rahul S Mor & Vijay Dahiya & Mukheshwar Yadav, 2022. "Application of Optimization Techniques in the Dairy Supply Chain: A Systematic Review," Logistics, MDPI, vol. 6(4), pages 1-16, October.

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