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A Comprehensive Review on Food Waste Reduction Based on IoT and Big Data Technologies

Author

Listed:
  • Sahar Ahmadzadeh

    (Business and Management Research Institute (BMRI), University of Bedfordshire, Vicarage St., Luton LU1 3JU, UK)

  • Tahmina Ajmal

    (Research Institute of Smart Cities (RISC), University of Bedfordshire, Park Square, Luton LU1 3JU, UK)

  • Ramakrishnan Ramanathan

    (Essex Business School, University of Essex, Southend Campus, Elmer Approach, Southend-On-Sea, Essex SS1 1LW, UK)

  • Yanqing Duan

    (Business and Management Research Institute (BMRI), University of Bedfordshire, Vicarage St., Luton LU1 3JU, UK)

Abstract

Food waste reduction, as a major application area of the Internet of Things (IoT) and big data technologies, has become one of the most pressing issues. In recent years, there has been an unprecedented increase in food waste, which has had a negative impact on economic growth in many countries. Food waste has also caused serious environmental problems. Agricultural production, post-harvest handling, and storage, as well as food processing, distribution, and consumption, can all lead to food wastage. This wastage is primarily caused by inefficiencies in the food supply chain and a lack of information at each stage of the food cycle. In order to minimize such effects, the Internet of Things, big data-based systems, and various management models are used to reduce food waste in food supply chains. This paper provides a comprehensive review of IoT and big data-based food waste management models, algorithms, and technologies with the aim of improving resource efficiency and highlights the key challenges and opportunities for future research.

Suggested Citation

  • Sahar Ahmadzadeh & Tahmina Ajmal & Ramakrishnan Ramanathan & Yanqing Duan, 2023. "A Comprehensive Review on Food Waste Reduction Based on IoT and Big Data Technologies," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3482-:d:1067935
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    References listed on IDEAS

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    1. Yinsheng Yang & Gang Yuan & Jiaxiang Cai & Silin Wei, 2021. "Forecasting of Disassembly Waste Generation under Uncertainties Using Digital Twinning-Based Hidden Markov Model," Sustainability, MDPI, vol. 13(10), pages 1-15, May.
    2. Rana Muhammad Adnan & Abolfazl Jaafari & Aadhityaa Mohanavelu & Ozgur Kisi & Ahmed Elbeltagi, 2021. "Novel Ensemble Forecasting of Streamflow Using Locally Weighted Learning Algorithm," Sustainability, MDPI, vol. 13(11), pages 1-19, May.
    3. Tammara Soma & Belinda Li & Virginia Maclaren, 2020. "Food Waste Reduction: A Test of Three Consumer Awareness Interventions," Sustainability, MDPI, vol. 12(3), pages 1-19, January.
    4. Ali Chalak & Chaza Abou-Daher & Mohamad G. Abiad, 2018. "Generation of food waste in the hospitality and food retail and wholesale sectors: lessons from developed economies," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(5), pages 1279-1290, October.
    5. Garre, Alberto & Ruiz, Mari Carmen & Hontoria, Eloy, 2020. "Application of Machine Learning to support production planning of a food industry in the context of waste generation under uncertainty," Operations Research Perspectives, Elsevier, vol. 7(C).
    6. Jessica Rossi & Augusto Bianchini & Patricia Guarnieri, 2020. "Circular Economy Model Enhanced by Intelligent Assets from Industry 4.0: The Proposition of an Innovative Tool to Analyze Case Studies," Sustainability, MDPI, vol. 12(17), pages 1-22, September.
    7. Bhanage Vinayak & Han Soo Lee & Shirishkumar Gedem, 2021. "Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
    8. Lisa Cherry & Darren Mollendor & Bill Eisenstein & Terri S. Hogue & Katharyn Peterman & John E. McCray, 2019. "Predicting Parcel-Scale Redevelopment Using Linear and Logistic Regression—the Berkeley Neighborhood Denver, Colorado Case Study," Sustainability, MDPI, vol. 11(7), pages 1-16, March.
    9. William A. Belson, 1959. "Matching and Prediction on the Principle of Biological Classification," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 8(2), pages 65-75, June.
    10. Amevi Acakpovi & Alfred Tettey Ternor & Nana Yaw Asabere & Patrick Adjei & Abdul-Shakud Iddrisu, 2020. "Time Series Prediction of Electricity Demand Using Adaptive Neuro-Fuzzy Inference Systems," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-14, August.
    11. Silvia Coderoni & Maria Angela Perito, 2020. "Sustainable consumption in the circular economy. An analysis of consumers’ purchase intentions for waste-to-value food," Post-Print hal-03385002, HAL.
    12. Hsu-Yang Kung & Ting-Huan Kuo & Chi-Hua Chen & Pei-Yu Tsai, 2016. "Accuracy Analysis Mechanism for Agriculture Data Using the Ensemble Neural Network Method," Sustainability, MDPI, vol. 8(8), pages 1-11, August.
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