# Real-Time Anomaly Detection in Cold Chain Transportation Using IoT Technology
###### Abstract
[20] found that the average temperature of food products during transportation is around 12% higher than recommended. A temperature break of 2 h during the transportation of perishable food may result in shelf-life decay by 10 to 40% [21], and the loss of products can reach as much as 35% [22]. Hence, the incidence of temperature anomalies can significantly influence the quality of highly perishable products [21]. In conventional cold chain management systems, vehicles and warehouses are often equipped with thermometers and humidity sensors [23; 24]. However, this approach cannot dynamically communicate the information with remote users and can only display and record environmental information locally [25]. Additionally, it cannot determine the environmental conditions during vehicle switching, temporary storage, or truck loading, among other situations [25]. Typically, it also does not monitor the microcosmic environment in the boxes holding perishable food: only the macrocosmic environment in the warehouse or vehicles [25]. As a result, such systems cannot deliver continuous and real-time environmental information on perishable food. In this sense, real-time environmental monitoring and control are critical for the safety and quality of perishable food and for tracking and evaluating the levels of risk throughout the cold chain [19; 26; 27]. In recent years, Internet of Things (IoT) technologies have been increasingly applied in the food industry due to their promising potential for more efficient monitoring in real time [28; 29; 30]. The IoT environment enables smart devices equipped with wireless communication technologies, sensors and actuators to connect to the internet and share their data in real time [31; 32]. In the cold chain, IoT sensing technologies enable the automatic tracking and tracing of food items and surrounding conditions, resulting in transparent cold chain management [7; 33]. In addition, food quality deterioration can be monitored in a real-time manner. Because of the progress of microelectronics technology, the cost and power consumption of IoT sensors have dropped substantially during the past few years [34; 35; 36]. With appropriate configuration, it may be set up to monitor various environmental conditions connected to food safety and quality, including temperature, humidity, light, vibration, carbon dioxide, ethylene, and others [25; 37; 38]. The main benefit of using these technologies is the ability to provide operators with automatic alerts to take corrective actions on time and prevent food quality deterioration [21; 39]. In addition, IoT technology also enables supply chains to employ dynamic virtualisations in operational management procedures, which helps food organisations deal with perishable food products, unpredictable supply fluctuations, and strict food safety and sustainability requirements [40]. On the other hand, without real-time traceability systems, it is difficult to ensure that the food items are moved and maintained in stable specified environmental conditions along the cold chain [41]. Recent research discussed the development of cold chain monitoring systems using an online-decision-support system based on IoT technologies for fruits, vegetables, meat and fishery products [42; 43; 44; 45; 46; 47]. The proposed systems monitor environmental conditions in real time and provide alerts on whether the temperature, humidity, or other factors exceed the safety limit. The combination of monitoring and decision-making support systems also showed promising results in reducing transportation losses. Furthermore, by installing the monitoring system, losses due to quality degradation were decreased, enhancing the overall performance of the food supply chain. The studies also showed that the product categories in the cold chain in which these technologies can be applied are varied [42; 43; 44; 45; 46; 47].