• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.375-384
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• 2020

Today's robots consist of many hardware and software subsystems, depending on the functions needed for specific tasks. Integration of subsystems can require a great deal of effort, as both the communication method and protocol of the subsystem can vary. This paper proposes an expandable robotic system in which all subsystems are integrated under Robot Operation System (ROS) framework. To achieve this, the paper presents a software library, ROS_M, developed to implement the TCP/IP-based ROS communication protocol in different control environments such as MCU and RT kernel based embedded system. Then, all the subsystem including hardware can use ROS protocol consistently for communication, which makes adding new software or hardware subsystems to the robotic system easier. A latency measurement experiment reveals that the system built for loop control can be used in a soft real-time environment. Finally, an expandable mobile manipulator robot is introduced as an application of the proposed system. This robot consists of four subsystems that operate in different control environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.495-498
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• 2008

This paper describes design of a real-time, wearable reflectance pulse oximetry which is based Wireless Sensor Network. For the purpose of continuously monitoring vital signs of a human, wearable reflectance pulse oximetry is built into a wrist type that can be obtained $SpO_2$ value of patient unobtrusively. This designed $SpO_2$ module is based on a low-power 8 bit ATmega128L microcontroller operating in 3V. Low power operating $SpO_2$ module was integrated to wireless sensor node for user's health monitoring. This paper is focused on the successful integration of all these components into wearable reflectance pulse oximetry and evaluates its ability to measure patient' $SpO_2$ value. Information from this sensor was wirelessly transmitted to a base-station for storage and display purposes.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.458-463
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• 2015

This paper suggests detection system for the movement of patient on bed based on IEEE802.15.4 by using pressure pad and guard sensor. The system is designed to detect ordinary activities of patients on bed as well as patients' falling from the bed while sleeping at night. The node that is installed at bed sends data to gather when the pressure pad and sensor of guard detect patients' activities and falling. These data sent to gather are transmitted to monitor at help desk by TCP/IP communication. To remove unnecessary data that occurred due to switch chattering during tossing and turning, timer of MCU is used. Also, Communication module can change transmission power to apply this system to various environments of hospital room. Therefore, the nurse can take care of patients on bed in real time with data about patients' conditions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.6 s.360
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• pp.1-8
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• 2007

In wireless sensor network which uses limited battery, power consumption is very important factor for the survivality of the system. By using low-power communication to reduce power consumption, error rate is increased in typical conditions. This paper analyzes power consumption of specific error control coding (ECC) implementations. With identical link quality, ECC provides coding gain which save the power for transmission at the cost of computing power. In sensor node, transmit power is higher than computing power of Micro Controller Unit (MCU). In this paper, Viterbi algerian is applied to the low-transmit-power sensor networks in terms of network power consumption. Practically, Viterbi algorithm presents 20% of reduction of re-transmission in compared with Auto Repeat Request (ARQ) system. Furthermore, it is observed that network power consumption is decreased by almost 18%.

• Journal of Korean Society of Rural Planning
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• v.25 no.2
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• pp.15-21
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• 2019

The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.459-465
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• 2022

This paper reports a method to use a wireless sensor network deployed in the field to real-time monitor soil moisture, warning when the moisture level reaches a specific value, and wirelessly controlling an additional device (LED or water supply system, etc.). In addition, we report all processes related to wireless irrigation system, including field deployment of sensors, real-time monitoring using a smartphone, data calibration, and control of additional devices deployed in the field by smartphone. A commercially available open-source Internet of Things (IoT) platform, NodeMCU, was used, which was combined with a 9V battery, LED and soil humidity sensor to be integrated into a portable prototype. The IoT-based soil humidity sensor prototype deployed in the field was installed next to a tree for on-site demonstration for the measurement of soil humidity in real-time for about 30 hours, and the measured data was successfully transmitted to a smartphone via Wifi. The measurement data were automatically transmitted via e-mail in the form of a text file, stored on the web, followed by analyses and calibrations. The user can check the humidity of the soil real-time through a personal smartphone. When the humidity of a soil reached a specific value, an additional device, an LED device, placed in the field was successfully controlled through the smartphone. This LED can be easily replaced by other electronic devices such as water supplies, which can also be controlled by smartphones. These results show that farmers can not only monitor the condition of the field real-time through a sensor monitoring system manufactured simply at a low cost but also control additional devices such as irrigation facilities from a distance, thereby reducing unnecessary energy consumption and helping improve agricultural productivity.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.13-18
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• 2014

Sensor nodes are used for monitoring and collecting the environmental data via wireless sensor network. The wireless sensor network with various sensor nodes draws attention as a key technology in ubiquitous computing. Sensor nodes has very small memory capacity and limited power resource. Thus, it is essential to have energy efficient strategy for the sensor nodes. Since the sensor nodes are operating on the same frequency bands with ISM frequency bands, the interference by the devices operating on the ISM band degrades the quality of communication integrity. In this paper, the convolutional code is proposed instead of ARQ for the error control for the sensor network. The proposed convolutional code was implemented and the BER performance is measured. For the fixed transmitting powers of -19.2 dBm and -25dBm, the BER with various communication distances are measured. The packet loss rate and the retransmission rate are calculated from the measured BER. It is shown that the porposed method obtained about 9~12% and 12-19% reduction in retransmission rate for -19.2 dBm and -25 dBm respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1170-1181
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• 2012

Wireless Sensor Networks(WSNs) are used in diverse applications. In general, sensor nodes that are easily deployed on specific areas have many resource constrains such as battery power, memory sizes, MCUs, RFs and so on. Hence, first of all, the efficient energy consumption is strongly required in WSNs. In terms of event states, event-driven deliverly model (i.e. surveillance and reconnaissance applications) has several characteristics. On the basis of such a model, clustering algorithms can be mostly used to manage sensor nodes' energy efficiently owing to the advantages of data aggregations. Since a specific node collects packets from its child nodes in a network topology and aggregates them into one packet to relay them once, amount of transmitted packets to a sink node can be reduced. However, most clustering algorithms have been designed without considering can be reduced. However, most clustering algorithms have been designed without considering characteristics of event-driven deliverly model, which results in some problems. In this paper, we propose enhanced clustering algorithms regarding with both targets' movement and energy efficiency in order for applications of surveillance and reconnaissance. These algorithms form some clusters to contend locally between nodes, which have already detected certain targets, by using a method which called CHEW (Cluster Head Election Window). Therefore, our proposed algorithms enable to reduce not only the cost of cluster maintenance, but also energy consumption. In conclusion, we analyze traces of the clusters' movements according to targets' locations, evaluate the traces' results and we compare our algorithms with others through simulations. Finally, we verify our algorithms use power energy efficiently.