Abstract
Since customer attention is increasing due to growing customer health awareness, it is important for the perishable food supply chain to monitor food quality and safety. This study proposes a real-time monitoring system that utilizes smartphone-based sensors and a big data platform. Firstly, we develop a smartphone-based sensor to gather temperature, humidity, GPS, and image data. The IoT-generated sensor on the smartphone has characteristics such as a large amount of storage, an unstructured format, and continuous data generation. Thus, in this study, we propose an effective big data platform design to handle IoT-generated sensor data. Furthermore, the abnormal sensor data generated by failed sensors is called outliers and may arise in real cases. The proposed system utilizes outlier detection based on statistical and clustering approaches to filter out the outlier data. The proposed system was evaluated for system and gateway performance and tested on the kimchi supply chain in Korea. The results showed that the proposed system is capable of processing a massive input/output of sensor data efficiently when the number of sensors and clients increases. The current commercial smartphones are sufficiently capable of combining their normal operations with simultaneous performance as gateways for transmitting sensor data to the server. In addition, the outlier detection based on the 3-sigma and DBSCAN were used to successfully detect/classify outlier data as separate from normal sensor data. This study is expected to help those who are responsible for developing the real-time monitoring system and implementing critical strategies related to the perishable supply chain.
Highlights
The usage of Internet of Things (IoT) sensors has greatly increased due to being cheaper, smaller, less power-consuming, and easier to use
Aloi et al (2017) explained that smartphones may be used as a flexible gateway to collect and forward data received from different sensors/IoT devices to the internet [2]
The sensors will be exposed to a huge number of environmental conditions, and, as such, this study utilizes a Not Only SQL (NoSQL) database to handle the big data of the IoT sensors
Summary
The usage of Internet of Things (IoT) sensors has greatly increased due to being cheaper, smaller, less power-consuming, and easier to use. Previous research [12] utilized the camera as well as the temperature and humidity sensors in the smartphone to collect information on agricultural events from rural farmers. This study proposes a real-time monitoring system that utilizes the temperature, humidity, GPS, and camera sensors in smartphones to gather data on the environmental conditions of perishable food during transportation and storage. The sensors will be exposed to a huge number of environmental conditions (temperature, humidity, GPS, and image sensor data), and, as such, this study utilizes a NoSQL database to handle the big data of the IoT sensors. The integration of these technologies (smartphone-based sensors, a NoSQL database, and outlier detection methods) should ensure the quality and safety of the agricultural food products throughout the supply chain
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