Smart cold chains for food systems: IoT monitoring, predictive analytics, and emerging technologies

Effective cold chain management is essential for maintaining the safety, nutritional quality, and sensory attributes of perishable food products throughout storage, transportation, and distribution. Conventional cold chain systems often rely on manual inspections and intermittent data logging, which limit real-time deviation detection, leading to increased spoilage and significant food losses. The rapid advancement of the Internet of Things (IoT) has enabled intelligent cold chain systems capable of continuous monitoring, real-time data transmission, and predictive quality management. A systematic literature search was conducted in Scopus using PRISMA-based screening, which initially returned 451 records, of which 318 were excluded due to topic irrelevance, non-English publications, and other criteria. Ultimately, 87 articles were included in the final synthesis. The results identified key technological components such as sensor networks and cloud computing, highlighting emerging innovations including biosensors and nano-enabled materials. The integration of predictive analytics with IoT sensor data facilitates dynamic shelf-life estimation, anomaly detection, and automated quality management across food supply chains, culminating in a noticeable shift towards predictive analytics and blockchain technologies over recent years.