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

被引:14
作者
Ahmadzadeh, Sahar [1 ]
Ajmal, Tahmina [2 ]
Ramanathan, Ramakrishnan [3 ]
Duan, Yanqing [1 ]
机构
[1] Univ Bedfordshire, Business & Management Res Inst BMRI, Vicarage St, Luton LU1 3JU, England
[2] Univ Bedfordshire, Res Inst Smart Cities RISC, Pk Sq, Luton LU1 3JU, England
[3] Univ Essex, Essex Business Sch, Southend Campus,Elmer Approach, Southend On Sea SS1 1LW, England
关键词
IoT sensors; food waste reduction; big data; communication technologies; supply chain; DATA ANALYTICS; NEURAL-NETWORK; CHALLENGES; MANAGEMENT; REGRESSION; CLASSIFICATION; OPPORTUNITIES; ARCHITECTURE; PREDICTION; FRAMEWORK;
D O I
10.3390/su15043482
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:19
相关论文
共 119 条
  • [1] The internet of things in the food supply chain: adoption challenges
    Aamer, Ammar Mohamed
    Al-Awlaqi, Mohammed Ali
    Affia, Ifadhila
    Arumsari, Silvia
    Mandahawi, Nabeel
    [J]. BENCHMARKING-AN INTERNATIONAL JOURNAL, 2021, 28 (08) : 2521 - 2541
  • [2] Time Series Prediction of Electricity Demand Using Adaptive Neuro-Fuzzy Inference Systems
    Acakpovi, Amevi
    Ternor, Alfred Tettey
    Asabere, Nana Yaw
    Adjei, Patrick
    Iddrisu, Abdul-Shakud
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020
  • [3] Novel Ensemble Forecasting of Streamflow Using Locally Weighted Learning Algorithm
    Adnan, Rana Muhammad
    Jaafari, Abolfazl
    Mohanavelu, Aadhityaa
    Kisi, Ozgur
    Elbeltagi, Ahmed
    [J]. SUSTAINABILITY, 2021, 13 (11)
  • [4] Ahmed S. R., 2021, Rev. geintec-gestao inovacao e tecnologias, V11, P1200
  • [5] Applications of big data to smart cities
    Al Nuaimi, Eiman
    Al Neyadi, Hind
    Mohamed, Nader
    Al-Jaroodi, Jameela
    [J]. JOURNAL OF INTERNET SERVICES AND APPLICATIONS, 2015, 6 : 1 - 15
  • [6] Albawi S, 2017, I C ENG TECHNOL
  • [7] Framework for evaluating risks in food supply chain: Implications in food wastage reduction
    Ali, Syed Mithun
    Moktadir, Md. Abdul
    Kabir, Golam
    Chakma, Jewel
    Rumi, Md. Jalal Uddin
    Islam, Md. Tawhidul
    [J]. JOURNAL OF CLEANER PRODUCTION, 2019, 228 : 786 - 800
  • [8] Detection of cherry tree branches with full foliage in planar architecture for automated sweet-cherry harvesting
    Amatya, Suraj
    Karkee, Manoj
    Gongal, Aleana
    Zhang, Qin
    Whiting, Matthew D.
    [J]. BIOSYSTEMS ENGINEERING, 2016, 146 : 3 - 15
  • [9] Challenges and Opportunities of Waste Management in IoT-Enabled Smart Cities: A Survey
    Anagnostopoulos, Theodoros
    Zaslavsky, Arkady
    Kolomvatsos, Kostas
    Medvedev, Alexey
    Amirian, Pouria
    Morley, Jeremy
    Hadjieftymiades, Stathes
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING, 2017, 2 (03): : 275 - 289
  • [10] Sustainable food waste management model for Bangladesh
    Ananno, Anan Ashrabi
    Masud, Mahadi Hasan
    Chowdhury, Sami Ahbab
    Dabnichki, Peter
    Ahmed, Nufile
    Arefin, Amit Md. Estiaque
    [J]. SUSTAINABLE PRODUCTION AND CONSUMPTION, 2021, 27 (27) : 35 - 51