Network Operation and Management System for Korean fir Ecosystem Monitoring Using Wireless Sensor Network

Lee, Kyeseon; Ryu, Jae Hong; Kim, Nae-Soo

doi:10.2991/ssemse-15.2015.311

Cited by 3 publications

(4 citation statements)

References 2 publications

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“…The display data transmission cycle is programmed to send a message once per second. The following conversion factors are used: Voltage = (ADC Value/1023.0) * 5000 (5000 mV because the drive voltage of the Micom is 5 V); amps = (Voltage-ACS offset (1.65 V))/mV per amp (6.6 mV/A) [19]. After the output of the current sensor is converted to a 10-bit value by the ADC, this is then converted to current using the 6.6 mV/A scale factor.…”

Section: Design and Developmentmentioning

confidence: 99%

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Battery Balancing Algorithm for an Agricultural Drone Using a State-of-Charge-Based Fuzzy Controller

Kim¹,

Lee

2020

Applied Sciences

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In this paper, we propose an intelligent battery control system that incorporates an active balancing technique and a fuzzy controller to manage and extend the life of an agricultural drone battery efficiently. The control system includes the following key features: A battery pack balancing algorithm based on a bidirectional DC/DC converter; a cell balancing system to prevent overcharge/discharge and ensure equal control of the cell voltages; and a monitoring system and wireless link to track the real-time status of the battery, temperature, and acceleration while the drone is in operation. Each battery pack consists of six lithium polymer batteries, one fuzzy controller per cell, and supports active balancing using the developed balancing technique. The capacity of each of the battery packs in the system is 11,000 mAh, and two can be combined to provide a total capacity of 22,000 mAh.

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Section: Design and Developmentmentioning

confidence: 99%

Section: Design and Developmentmentioning

confidence: 99%

Battery Balancing Algorithm for an Agricultural Drone Using a State-of-Charge-Based Fuzzy Controller

Kim¹,

Lee

2020

Applied Sciences

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“…The Network operation & management server as Fig. 8 is largely composed of network management, operation mode control, user input management, the main screen management, and event data management functions [7]. · Main Screen Management: it is located in the center as wallpaper with configuration images of wild vegetation community habitats and sensor network topology.…”

Section: Network Operation and Management Server For Wild Vegetatimentioning

confidence: 99%

Study on IoT based wild vegetation community ecological monitoring system

Kim

Lee

Ryu

2015

2015 Seventh International Conference on Ubiquitous and Future Networks

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This paper presents a study on the Internet of Things based low-power wireless sensor networks for remote monitoring of wildlife ecosystem due to climate change. Especially, it is targeting the wild vegetation communities ecological monitoring. First, this paper is presented the platform concept that can effectively monitor, analyze and predict the ecosystem changes based on Internet of Things technology. Based on this, this paper is proposed the required sensors and system architecture of lowpower wireless sensor networks based on Internet of Things for the wild vegetation community ecological monitoring. In addition, the design and implementation results for the main components of the system are shown. Finally, it shows the operating results of test-bed which was applied to real wild trees, using the developed prototype.

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“…It provides a smart phone-based client application App. There is also access to move the manager, providing Android as the default OS [4]. Detailed functional configuration is shown in Figure 5 below.…”

Section: System Constructionmentioning

confidence: 99%