# Real-Time Anomaly Detection in Cold Chain Transportation Using IoT Technology
## 2 Literature Review
### Iot Monitoring Systems  
In recent years, various IoT sensor systems have been developed and deployed to monitor the environmental parameters of perishable food and detect anomalies in real time. Table 1 presents some examples of systems proposed in the literature. \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Authors** & **Year** & **Product** & **Parameters Monitored** & **Communication** & **Real-Time** & **Aleriting** & **Trip** \\  & & & & & **Monitoring App** & **System** & **Detection** \\ \hline [PERSON] et al. [55] & 2010 & Perishable products & T, RH, V, GPS & RFID, GPRS & ✓ & ✓ & ✓ & ✗ \\ [PERSON] et al. [48] & 2012 & Cod & T & WSN & ✗ & ✗ & ✗ \\ [PERSON] et al. [56] & 2014 & Perishable products & T & 2G & ✗ & ✓ & ✗ \\ [PERSON] et al. [19] & 2014 & Banana & T, RH, CO\({}_{2}\) & ZigBee & ✗ & ✗ & ✗ \\ [PERSON] et al. [57] & 2015 & Chilled lamb products & T & GSM/GPRS & ✓ & ✗ & ✗ \\ [PERSON] et al. [58] & 2016 & Fish (tilapia) & T & ZigBee & ✓ & ✗ & ✗ \\ [PERSON] et al. [59] & 2017 & Banana & T, RH, CO\({}_{2}\) & GSM cellular & ✗ & ✗ & ✗ \\ [PERSON] et al. [60] & 2017 & Table grapes & T, RH, VOC & GPRS & ✗ & ✗ & ✗ \\ [PERSON] et al. [61] & 2017 & Kimchi & T, RH, GPS & WiFi & ✓ & ✗ & ✗ \\ [PERSON] et al. [62] & 2017 & Blackberry & T, RH, CO\({}_{2}\), LI & RFID and WiFi & ✗ & ✓ & ✗ \\ [PERSON] et al. [7] & 2018 & Meat and seafood & T, RH, LI & Bluetooth, Wi-Fi and \(3G/4G\) & ✓ & ✓ & ✗ \\ [PERSON] et al. [45] & 2018 & Holly & T, RH, CO\({}_{2}\), C\({}_{2}\)H\({}_{4}\) & & ✓ & ✓ & ✓ & ✗ \\ [PERSON] et al. [63] & 2018 & Peach & T, RH, O\({}_{2}\), CO\({}_{2}\), C\({}_{2}\)H\({}_{4}\) & & ✗ & ✓ & ✗ \\ [PERSON] et al. [64] & 2018 & Meals & T & WSN, Bluetooth and \(3G/4G\) & ✗ & ✗ & ✗ \\ [PERSON] et al. [47] & 2018 & Fruit & T, RH & GPRS (3G, 4G, LTE) & ✓ & ✗ & ✗ \\ [PERSON] et al. [65] & 2019 & Perishable products & T & RFID & ✗ & ✗ & ✗ \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Real-time food quality monitoring systems found in the literature. As shown in Table 1, there are a significant number of the studies which present a real-time monitoring interface to visualise the live data of environmental parameters in cold chain transportation. Some articles such as that of [PERSON] et al. [70] used a smartphone-based approach (Android App) for data visualisation, which while effective limits users of the software to a mobile device with limited screen size. Others such as [PERSON] et al. offered desktop-based visualisation by developing a Windows application for real-time monitoring [58]. The drawback of these solutions, however, is firstly the limiting convenience factor of being restricted to a personal computer to access the data, and secondly, the operating system compatibility restrictions imposed by Windows-based applications. The third type of interface observed in the literature is employed by authors such as [PERSON] et al. [61], who developed a web dashboard allowing for monitoring on multiple devices. However, the existing studies remain limited in presenting a mechanism to alert the personnel in the case of broaching safety thresholds of environmental parameters. Only a few studies mentioned the presence of early warning systems. The first noted occurrence of real-time parameter monitoring with an alerting system implemented is found in the work of [PERSON] et al. [55]. In this research, the authors propose a rule-based system for alerting during the transportation of perishable products in containers. Nonetheless, the notification system in this work is limited to an alert within a bespoke Windows application. [PERSON] et al. [56] proposed a temperature monitoring and alerting system for perishable goods based on Radio Field Identification (RFID) technology. In this work, the alerts were only delivered to either the RFID device or the mobile phone once the RFID tag on the product had been scanned. [PERSON] et al.