Abstract
Targeting the three major obstacles—information fragmentation, delayed risk response, and ambiguous accountability—in food cold chain safety governance, this study constructs an integrated cold chain safety traceability and monitoring system centered on artificial intelligence technology and incorporating the Internet of Things and blockchain. On the basis of a comprehensive risk analysis of the entire food cold chain process, and drawing on theoretical frameworks including supply chain resilience theory, information asymmetry theory, HACCP, and ISO 22000 food safety standards, this study designs a system architecture organized around five functional modules: multi-source data collection and traceability, dynamic food quality assessment, risk prediction and early warning, intelligent scheduling optimization, and blockchain-based trusted evidence storage. This study then proposes a collaborative operational architecture encompassing perception, assessment, prediction, decision-making, and evidence storage, which enables multi-source data fusion, dynamic quality evaluation, and risk warning. This advances the transformation of cold chain safety governance from a reactive post-incident accountability model to a proactive prevention and control model of pre-incident warning and in-process monitoring, while clarifying the functional positioning of artificial intelligence technology in cold chain safety governance.
Publication Date
7-13-2026
First Page
67
Last Page
74
DOI
10.13652/j.spjx.1003.5788.2026.60123
Recommended Citation
Xiaoqing, ZENG; Yuyue, ZHANG; Wenqing, XIE; and Jianhua, ZHOU
(2026)
"An AI-driven safety traceability and monitoring system for food cold chain,"
Food and Machinery: Vol. 42:
Iss.
6, Article 9.
DOI: 10.13652/j.spjx.1003.5788.2026.60123
Available at:
https://www.ifoodmm.cn/journal/vol42/iss6/9
References
[1] FAO (Food and Agriculture Organization of the United Nations ).The state of food and agriculture:moving forward on food loss and waste reduction [R].Rome:FAO,2019:5.
[2] ZHANG Y,ZOU Y F,LIU L Q,et al.A digital twin-driven dynamic shelf life approach for mitigating food loss across fruit supply chains [J].Journal of Stored Products Research,2026,117:103016.
[3] 市场监管总局,教育部,工业和信息化部,等.关于加强预制菜食品安全监管促进产业高质量发展的通知 (国市监食生发〔2024〕27号) [EB/OL ].(2024 -03-18) [2025 -12-28].https://www.gov.cn/zhengce/zhengceku/ 202403 /content_ 6940808.htm.State Administration for Market Regulation,Ministry of Education,Ministry of Industry and Information Technology,et al.Notice on strengthening food safety supervision of prepared dishes and promoting high-quality industrial development (No.27 [2024 ] of the State Administration for Market Regulation ) [EB/OL ].(2024 -03-18) [2025 -12-28].https://www.gov.cn/zhengce/zhengceku/ 202403 /content_ 6940808.htm.
[4] 陈俊,刘会阁.食品工程中利用人工智能技术的冷链物流温度预测模型构建 [J].中外食品工业,2025 (5):29-31.CHEN J,LIU H G.Construction of a cold chain logistics temperature prediction model using artificial intelligence technology in food engineering [J].Global Food Industry,2025(5):29-31.
[5] LI S Y,ZHOU Y P,ZHANG Y J,et al.An overview of artificial intelligence applications in food cold chain transportation [C]// Proceedings of the 2023 5th International Conference on Robotics Systems and Automation Engineering.United Kingdom:ACM,2023:34-40.
[6] 郑根让.农产品冷链物流中基于时空网络的 AI温湿度异常预|警与调度技术 [J].自动化与仪器仪表,2026 (2):97-101.ZHENG G R.AI temperature and humidity anomaly early warning and dispatching technology based on spatio-temporal network in agricultural product cold chain logistics [J].Automation & Instrumentation,2026 (2):97-101.
[7] LAVELLE J,RUANE B.Gartner identifies top trends in supply chain technology for 2024:interplay between humans and machines is a key theme driving multiple trends [EB/OL ].(2024 -03-20) [2026 -05-11].https://www.gartner.com/en/newsroom/press-rel eases/ 2024 -03-20-gartner-identifies-top-trends-in-supply-chain-technology-for- 2024.
[8] MONTEIRO J,BARATA J.Digital twin-enabled regional food supply chain:a review and research agenda [J].Journal of Industrial Information Integration,2025,45:100851.
[9] 阮俊虎,孙元威.人工智能赋能农业产业链供应链韧性提升：逻辑、挑战与路径 [J].南京农业大学学报 (社会科学版 ),2026,26(1):24-37.RUAN J H,SUN Y W.Enhancing agricultural industry chain and supply chain resilience through artificial intelligence empowerment:logic,challenges and paths [J].Journal of Nanjing Agricultural University (Social Sciences Edition ),2026,26(1):24-37.
[10] REGATTIERI A,GAMBERI M,MANZINI R.Traceability of food products:general framework and experimental evidence[J].Journal of Food Engineering,2007,81(2):347-356.
[11] 曾小青,彭越,王琪.物联网加区块链的食品安全追溯系统研究 [J].食品与机械,2018,34(9):100-105.ZENG X Q,PENG Y,WANG Q.Research on food safety traceability system based on IoT and blockchain technology [J].Food & Machinery,2018,34(9):100-105.
[12] RUIZ-GARCIA L,LUNADEI L.The role of RFID in agriculture:applications,limitations and challenges [J].Computers and Electronics in Agriculture,2011,79(1):42-50.
[13] 韩彬,冷冬梅,徐毓谦,等.肉品冷链物流监控技术研究进展[J].食品工业科技,2025,46(3):19-30.HAN B,LENG D M,XU Y Q,et al.Research progress in monitoring technology of cold chain logistics for meat products[J].Science and Technology of Food Industry,2025,46(3):19-30.
[14] JEDERMANN R,NICOMETO M,UYSAL I,et al.Reducing food losses by intelligent food logistics [J].Philosophical Transactions of the Royal Society A:Mathematical,Physical and Engineering Sciences,2014,372(2017 ):20130302.
[15] 吴铭峰.基于人工智能技术的船舶冷链物流监控系统 [J].舰船科学技术,2021,43(2):196-198.WU M F.Design of ship cold chain logistics monitoring system based on artificial intelligence technology [J].Ship Science and Technology,2021,43(2):196-198.
[16] 周春华,吴霞云.食品经营企业行政责任主体双罚制分离构想[J].食品与机械,2024,40(8):70-75,98.ZHOU C H,WU X Y.The concept of separation of double punishment system for the main body of administrative responsibility of food business enterprises [J].Food & Machinery,2024,40(8):70-75,98.
[17] DUMAN E,AYDOĞAN E.Enhancing traceability and reliability in cold chain logistics through hyperledger fabric and IoT [J].Applied Sciences,2025,15(22):12149.
[18] MISHRA A,KUNDU T,KAPOOR R,et al.Blockchain adoption in cross-border cold supply chains:cost,efficiency and trust [J].Transportation Research Part E:Logistics and Transportation Review,2025,201:104236.
[19] VASILEIOU M,KYRGIAKOS L S,KLEISIARI C,et al.Digital transformation of food supply chain management using blockchain:a systematic literature review towards food safety and traceability [J/OL ].Business & Information Systems Engineering.(2025 -06-12) [2025 -12-29].https://doi.org/10.1007 /s12599 -025-00948 -0.
[20] PARK J W,JU Y M,KIM Y G,et al.50% reduction in energy consumption in an actual cold storage facility using a deep reinforcement learning-based control algorithm [J].Applied Energy,2023,352:121996.
[21] HAN J W,BADÍA-MELIS R,YANG X T,et al.CFD simulation of airflow and heat transfer during forced-air precooling of apples [J].Journal of Food Process Engineering,2017,40(2):e12390.
[22] CHEN J,GE S L,CHONG H Y,et al.Multi-objective optimisation of container with food cold chain using multimodal transport under uncertainties in network structure and ad-hoc situations [J].Promet - Traffic&Transportation,2025,37(5):1 376-1 392.
[23] SHI Y H,LIN Y,LIM M K,et al.An intelligent green scheduling system for sustainable cold chain logistics [J].Expert Systems with Applications,2022,209:118378.
[24] WASI A T,ISLAM M S,AKIB A R,et al.Graph neural networks in supply chain analytics and optimization:concepts,perspectives,dataset and benchmarks [EB/OL ].(2024 -11-13)
[2025 -12-06].https://arxiv.org/abs/ 2411.08550.
[25] 李鑫,朱磊,张媛,等.基于注意力时间卷积网络的香蕉新鲜度识别与剩余货架期预测 [J].食品与机械,2024,40(11):153-159.LI X,ZHU L,ZHANG Y,et al.Freshness recognition and remaining shelf life prediction of banana based on attention temporal convolutional network [J].Food & Machinery,2024,40(11):153-159.
[26] CHAUDHARY R K,NEUPANE A,WANG Z L,et al.Mango quality assessment using near-infrared spectroscopy and hyperspectral imaging:a systematic review [J].Agronomy,2025,15(10):2 271.
[27] RAHMAN M M,SHIBATA M,NAKAZAWA N,et al.Non-destructive approach for the prediction of pH in frozen fish meat using fluorescence fingerprints in tandem with chemometrics [J].Fishes,2022,7(6):364.
[28] CUI L G,CHEN Y C,DENG J,et al.A novel attLSTM framework combining the attention mechanism and bidirectional LSTM for demand forecasting [J].Expert Systems with Applications,2024,254:124409.
[29] CHRISTOPHER M,PECK H.Building the resilient supply chain [J].The International Journal of Logistics Management,2004,15(2):1-14.
[30] 冯燕芳,陈永平.技术赋能下生鲜农产品冷链物流质量提升途径研究 [J].价格理论与实践,2024 (4):72-76,224.FENG Y F,CHEN Y P.Research on ways of quality improvement of cold chain logistics for fresh agricultural products by technology empowerment [J].Price (Theory & Practice ),2024 (4):72-76,224.
[31] LEE H L.The triple-a supply chain [J].Harvard Business Review,2004,82(10):102-112.
[32] PATEL A S,BRAHMBHATT M N,BARIYA A R,et al.Blockchain technology in food safety and traceability concern to livestock products [J].Heliyon,2023,9(6):e16526.
[33] AKERLOF G A.The market for "lemons":quality uncertainty and the market mechanism [J].The Quarterly Journal of Economics,1970,84(3):488.
[34] QIAN J P,YU Q Y,JIANG L,et al.Food cold chain management improvement:a conjoint analysis on COVID- 19 and food cold chain systems [J].Food Control,2022,137:108940.
[35] YU W B,OUYANG Z W,ZHANG Y F,et al.Research progress on the artificial intelligence applications in food safety and quality management [J].Trends in Food Science & Technology,2025,156:104855.
[36] 沙蓓蓓.人工智能视角下双渠道供应链的创新驱动因素研究[J].食品研究与开发,2020,41(7):9.SHA B B.Research on innovation-driven factors of dual-channel supply chain from the perspective of artificial intelligence [J].Food Research and Development,2020,41(7):9.
[37] 傅卫卫.食品安全法律监管的逻辑演进与路径创新 [J].食品与机械,2026,42(1):259-260.FU W W.The logical evolution and path innovation of legal regulation on food safety [J].Food & Machinery,2026,42(1):259-260.
[38] NGUYEN T T B,LI D.A systematic literature review of food safety management system implementation in global supply chains [J].British Food Journal,2022,124(10):3 014-3 031.
[39] BENEFO E O,KARANTH S,PRADHAN A K.Applications of advanced data analytic techniques in food safety and risk assessment [J].Current Opinion in Food Science,2022,48:100937.
[40] PINDI M.Revolutionizing cold chain logistics:leveraging IoT and AI for enhanced food safety and waste reduction [J].World Journal of Advanced Research and Reviews,2025,26(2):1 412-1 424.
[41] ZHANG P F,LI T R,WANG G Q,et al.Multi-source information fusion based on rough set theory:a review [J].Information Fusion,2021,68:85-117.
[42] ADADE S Y S,LIN H,JOHNSON N A N,et al.Advanced food contaminant detection through multi-source data fusion:strategies,applications,and future perspectives [J].Trends in Food Science & Technology,2025,156:104851.
