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10 posts tagged with "conference"

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· One min read

Abstract

Current technology such as Bluetooth Low Energy (BLE) provides an efficient way for Real-Time Location System (RTLS). This study proposes a BLE-based Real-Time Location System that utilizes Smartphone and NoSQL database as gateway and data storage respectively. Firstly, we develop a smartphone-based tracking app to gather the location of employees. Secondly, the generated sensor data from gateway is then stored into NoSQL MongoDB. The proposed system was tested for monitoring the movement of employees in the workplace. The results showed that commercial versions of the BLE-based device and the proposed system are sufficiently efficient for RTLS. Furthermore, proposed system is capable of processing a massive input/output of sensor data efficiently when the number of BLE-based devices and users increases.

Published in: BDIOT 2018 Proceedings of the 2018 2nd International Conference on Big Data and Internet of Things, ACM New York, NY, USA ©2018
DOI: 10.1145/3289430.3289470

· One min read

Abstract

Now days, customer’s health awareness is of extreme significance. Food can become contaminated at any point during production, distribution and preparation. Therefore, it is of key importance for the perishable food supply chain to monitor the food quality and safety. Traceability system offers complete food information and therefore, it guarantees food quality and safety. The current study postulates a low cost IoT-based traceability system that utilized RFID and smartphone-based sensors. The RFID handheld reader based on smartphone is utilized to track and trace product information. In addition the smartphone-based sensor is used to measure temperature, humidity, and location (based on GPS sensor) during storage and transportation. The proposed system was verified for kimchi supply chain in Korea, and revealed significant benefits to managers as well as customers by providing the real-time location as well as complete temperature and humidity history. The results displayed that compared to the traditional methods, the proposed system is capable of tracking products as well as processing an immense input of sensor data efficiently and effectively.

· One min read

Abstract

To make manufacturers more competitive, there is a need to integrate advanced computing and cyber-physical systems to take advantage of the current technologies. With the advent of smart sensors such as IoT technologies (1), collecting data has become a simple task, but the question remains if these devices or data provide the right information for the right purpose at the right time. Data is not useful unless it is processed in a way that provides context and meaning that can be understood by the right personnel. Just connecting sensors to a machine or connecting a machine to another machine will not give users the insights needed to make better decisions. Thus, in this paper we proposed the real time monitoring system that utilized machine learning algorithm to predict the quality of product based on sensor data that was gathered by IoT device and showed the result in real time.

Published in: KSMTE Annual Autumn Conference 2017
Link: http://www.dbpia.co.kr/Journal/ArticleDetail/NODE07285510