From passive to self-aware packs: Flexible Sensor-AI integration powering intelligent, sustainable food packaging

文献类型： 外文期刊

第一作者： Hou, Hongwei

作者： Hou, Hongwei;Chen, Huan;Fu, Yaning;Mu, Wenjun;Zhang, Jingbin;Jia, Zhixin;Yang, Xinting

作者机构：

关键词： Smart food packaging; Flexible sensors; Artificial intelligence; Shelf-life prediction; Human-computer interaction AI

期刊名称：TRENDS IN FOOD SCIENCE & TECHNOLOGY （ 影响因子：15.4； 五年影响因子：18.4 ）

ISSN： 0924-2244

年卷期： 2025 年 164 卷

页码：

收录情况： SCI

摘要： Background The global agri-food sector faces persistent challenges in ensuring food quality, safety, and sustainability. Conventional packaging functions as a passive barrier, incapable of monitoring physicochemical or microbiological changes in real time. This limitation necessitates reliance on conservative expiration dates, thereby contributing to significant food waste. Smart interactive packaging addresses these issues by detecting and communicating the dynamic conditions of food products. Scope and approach This review critically assesses flexible sensor materials, including conductive polymers and carbon-based nanomaterials, as well as their integration with wireless communication systems and energy-harvesting technologies. It also evaluates machine learning-driven artificial intelligence (AI) methodologies for freshness scoring and shelf-life prediction. Practical implementations are reviewed through case studies involving sensor patches, embedded films, logistics optimization, and consumer interfaces. Key findings and conclusions Flexible sensors enable millimeter-scale monitoring of temperature, humidity, gases, pH, and microbial metabolites, while roll-to-roll printing supports scalable integration into packaging. AI-driven pipelines process multimodal sensor data to generate freshness scores, estimate shelf life, and detect anomalies. These systems employ regression and tree-based models as well as convolutional and recurrent neural networks enhanced by explainable AI techniques. Demonstrations of sensor patches, embedded films, and AI-driven logistics have achieved spoilage reductions. Despite these advances, challenges remained in addressing sensor drift, achieving energy autonomy-systems capable of operating independently through on-board energy harvesting and management, ensuring material circularity, and meeting regulatory requirements. Future efforts should focus on integrating self-healing materials, improved energy harvesting, biodegradable electronics, and human-computer interaction to realize sustainable autonomous smart packaging systems.

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