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A Study on Adaptive QoS Control System based on MQTT for Reducing Network Traffic
Sung-Jin Kim,Kyoung-Woo Cho,Myung-Eui Lee,Chang-Heon Oh 한국정보통신학회 2017 2016 INTERNATIONAL CONFERENCE Vol.9 No.1
Recently, MQTT application protocol which ensures connectivity and real-time of large number of nodes in the IoT Environment has been paid attention. MQTT provides three QoS level to ensure reliability of message delivery. However, traffics transmitted and received from MQTT broker server increases depending on QoS level setting of publisher. Traffic increase degrades network environment and causes problem of packet loss and delay. In this paper, we analyze traffics transmitted and received between publisher and MQTT broker server, and proposes system which controls QoS level by sending adaptive QoS control message to publisher. It decreases network traffics by controlling publisher"s QoS level according to traffic changes.
Development of a Mobile Integrated Control App for Smart Fish Farms based on the IoT
Kyoo Jae Shin 대한전자공학회 2020 IEIE Transactions on Smart Processing & Computing Vol.9 No.2
This paper is about the development of a mobile app for integrated control and real-time monitoring of smart fish farms based on the Internet of Things (IoT). The important role of this project is to control water processing in a recirculating, smart fish farm. The proposed smart fish farm consists of two water tanks, a balancing tank, and a recirculating aquaculture system (RAS). In this aquaculture, the water flow process is regulated by the proportional integral derivative (PID) controller along with water-level ultrasonic sensors, water temperature sensors, and dissolved oxygen (DO) and potential hydrogen (pH) sensors. Remote control and the real-time monitoring are performed by using the Message Queue Telemetry Transport (MQTT) protocol, with the measured big data stored in lab servers. This designed aquaculture system operates in manual mode, automatic mode, and in remote mode by using a mobile device. To verify the performance of the designed system, field tests were conducted in the Future Creative Technology Research Institute of the Busan University of Foreign Studies and at Jangsucheon Ltd. of Gangwhado Island. Based on the experimental results, it satisfies the required performance of a smart fish farm.
이승신,오염덕 대한전기학회 2024 전기학회논문지 Vol.73 No.3
In this study, we propose a big data railway safety platform architecture by applying communication and database technologies and platform architectures used in many industries for real-time failure and anomaly detection of railway operations. There have been studies on big data architecture in data collection, communication, storage, and analysis areas. However, previous studies have not addressed the design of big data architecture for the safe operation of railways specifically. Therefore, in this study, in order to collect, store, and analyze data that may occur in railway operations, we designed an architecture that can be implemented by using currently available technologies from the perspective of the entire data life cycle. In particular, a combination of MQTT and Kafka was proposed as a message and event broker for the railway safety platform architecture, and MongoDB was ultimately proposed as a NoSQL database. In addition, the application model of the big data railway safety platform was presented using the designed architecture, and YOLOv5, an object detection algorithm, was used to conduct an experiment on how image data from railroad tracks can be used in anomaly detection of railway operations. The neural network trained with YOLOv5 can accurately classify eight rail components of the railway and also classify the abnormal states of the eight components relatively accurately. In subsequent research, we plan to implement this architecture as a real big data platform to expand anomaly detection experiments on railroad tracks.