• Journal of Electrical Engineering and Technology
• /
• v.4 no.1
• /
• pp.131-134
• /
• 2009

We have proposed an indoor positioning system for moving objects and/for the blind or visually impaired to play various sports. [ for a blind or visually impaired playing various sports.] This system consists of a wireless heart rate monitor, wireless sensor network and / 4 ultrasound satellites [ configuration with four ultrasound satellite modules) at the corners of the room. This system provides / the real-time measurement of the location and heart rate of the person in the room[ non-invasive measurement method of the heart rate and the location of a person in real time ], and will help the [a] blind or visually impaired enjoy sports more easily.

• Journal of the Korea Computer Graphics Society
• /
• v.27 no.3
• /
• pp.31-42
• /
• 2021

We propose a deep learning-based method that can estimate an appropriate lighting of both indoor and outdoor images. The method consists of two networks: Crop-to-PanoLDR network and LDR-to-HDR network. The Crop-to-PanoLDR network predicts a low dynamic range (LDR) environment map from a single partially observed normal field of view image, and the LDR-to-HDR network transforms the predicted LDR image into a high dynamic range (HDR) environment map which includes the high intensity light information. The HDR environment map generated through this process is applied when rendering virtual objects in the given image. The direction of the estimated light along with ambient light illuminating the virtual object is examined to verify the effectiveness of the proposed method. For this, the results from our method are compared with those from the methods that consider either indoor images or outdoor images only. In addition, the effect of the loss function, which plays the role of classifying images into indoor or outdoor was tested and verified. Finally, a user test was conducted to compare the quality of the environment map created in this study with those created by existing research.

• Journal of KIISE
• /
• v.44 no.7
• /
• pp.733-741
• /
• 2017

LPWAN(Low Power Wide Area Network) technology is M2M (Machine to Machine) networking technology for the Internet of Things. The technology is designed to support low-power, long-distance and low-speed communications that are typical of LoRaWAN(Long Range Wide Area Network). To exchange inter-object information using a LoRaWAN, the link performances for various environments must be known. however, active performance analysis research that is based on an empirical environment is nonexistent. Therefore, this paper empirically evaluates the performance of the LoRa (Long Range) link, a physical communication technology of the LoRaWAN for various variables that may affect the link quality in indoor and outdoor environments. To achieve this, a physical performance monitoring system was designed and implemented. A communication experiment environment was subsequently constructed based on the indoor and outdoor conditions. The SNR(Signal to Noise Ratio), RSSI(Received Signal Strength Indication), and the PDR(Packet Delivery Ratio) were evaluated.

• Journal of KIISE:Computing Practices and Letters
• /
• v.12 no.1
• /
• pp.56-65
• /
• 2006

Recently the study on service robots has been proliferated in many fields, and there are active developments for indoor services such as supporting for elderly people. It is important for robot to recognize objects and situations appropriately for effective and accurate service. Conventional object recognition methods have been based on the pre-defined geometric models, but they have limitations in indoor environments with uncertain situation such as the target objects are occluded by other ones. In this paper we propose a Bayesian network model to reason the probability of target objects for effective detection. We model the relationships between objects by activities, which are applied to non-static environments more flexibly. Overall structure is constructed by combining common-cause structures which are the units making relationship between objects, and it makes design process more efficient. We test the performance of two Bayesian networks for verifying the proposed Bayesian network model through experiments, resulting in accuracy of $86.5\%$ and $89.6\%$ respectively.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.4
• /
• pp.847-856
• /
• 2013

This paper presents an AP placement technique considering indoor location-awareness and examines its performance. The proposed AP placement technique is addressed from three performance metrics: location-awareness and AP-based wireless network performance as well as its cost. The proposed AP placement technique consists of meta-heuristic algorithms that yield a near optimal AP configuration for given performance metrics, and deterministic algorithms that improve the fast convergence of the near optimal AP configuration. The performance of the AP placement technique presented in this paper is measured under the environments simulating indoor space, and numerical results obtained by experimental evaluation yield the fast convergence of a near-optimal solution to a given performance metric.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.1
• /
• pp.364-369
• /
• 2012

Location information is a critical element of ubiquitous computing. Cricket is an indoor location-based system that transmits radio and ultrasonic signals in regular intervals to calculate the distance between nodes. However, the amount of signal interference and collisions increases in proportion with the number of nodes, losing the accuracy of the location-based system. This study proposes an algorithm based on the 802.15.2 MAC protocol for the wireless sensor network to reduce signal interference and collision by employing node numbers and the frequency reuse approach used in mobile telecommunication. We analyzed the performance of our algorithm. The obtained results showed that the algorithm is an effective for throughput and energy compared to the Cricket system.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.16 no.4
• /
• pp.1-7
• /
• 2020

Over the past few years, Wi-Fi signal based indoor positioning system (IPS) has been researched extensively because of its low expenses of infrastructure deployment. There are two major aspects of location-related information contained in Wi-Fi signals. One is channel state information (CSI), and one is received signal strength indicator (RSSI). Compared to the RSSI, the CSI has been widely utilized because it is able to reveal fine-grained information related to locations. However, the conventional IPS that employs a single access point (AP) does not exhibit decent performance especially in the environment of non-line-of-sight (NLOS) situations due to the reliability degeneration of signals caused by multipath fading effect. In order to address this problem, in this paper, we propose a novel method that utilizes multiple APs instead of a single AP to enhance the robustness of the IPS. In our proposed method, a hybrid neural network is applied to the CSIs collected from multiple APs. By relying more on the fingerprint constructed by the CSI collected from an AP that is less affected by the NLOS, we find that the performance of the IPS is significantly improved.

• International Journal of Computer Science & Network Security
• /
• v.22 no.12
• /
• pp.171-177
• /
• 2022

The number of people who own indoor plants is growing today, but as a result of their busy lifestyles-such as work or travel-as well as a lack of enthusiasm in caring for their plants, their plants wither. The use of an irrigation control system with a surveillance camera can assist such folks in taking care of their plants. Such a device can assist in remotely watering plants at predetermined times and checking on the health of the plants. The proprietors would be able to live comfortably without feeling bad thanks to this change. Internet access is required for this technology in order to monitor the plants and control the watering through apps. A sensor is installed in the soil to monitor soil humidity and send data to the microcontroller for irrigation, allowing the owner to schedule irrigation as they see fit and keep an eye on their plants all day. With the use of a remote irrigation control system, the plants will grow properly and be irrigated with the proper amount of water, and the owners will be so glad and delighted to watch their plants. Knowing the time and quantity of water are vital parts of the plant growth.

• Journal of IKEEE
• /
• v.27 no.4
• /
• pp.439-449
• /
• 2023

In an era marked by the increasing use of drones and the growing demand for indoor surveillance, the development of a robust application for detecting and tracking both drones and humans within indoor spaces becomes imperative. This study presents an innovative application that uses FMCW radar to detect human and drone motions from the cloud point. At the outset, the DBSCAN (Density-based Spatial Clustering of Applications with Noise) algorithm is utilized to categorize cloud points into distinct groups, each representing the objects present in the tracking area. Notably, this algorithm demonstrates remarkable efficiency, particularly in clustering drone point clouds, achieving an impressive accuracy of up to 92.8%. Subsequently, the clusters are discerned and classified into either humans or drones by employing a deep learning model. A trio of models, including Deep Neural Network (DNN), Residual Network (ResNet), and Long Short-Term Memory (LSTM), are applied, and the outcomes reveal that the ResNet model achieves the highest accuracy. It attains an impressive 98.62% accuracy for identifying drone clusters and a noteworthy 96.75% accuracy for human clusters.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.2
• /
• pp.125-130
• /
• 2013

Compared to OWR (One-Way Ranging) method that requires precise network time synchronization, TWR (Two-Way Ranging) method has advantages in building an indoor WPAN (Wireless Personal Area Network) location system with lower cost. However, clock offsets of nodes in WPAN system should be eliminated or compensated to improve location accuracy of the TWR method. Because conventional clock offset elimination methods requires multiple TWR transactions to reduce clock offset, they produce network traffic burden instead. This paper presents a clock offset estimation method that can reduce clock offset error with a single TWR transaction. After relative clock offsets of sensor nodes are estimated, clock offsets of mobile tags are estimated using a single TWR communication. Simulation results show that location accuracy of the proposed method is almost similar to the conventional clock offset elimination method, while its network traffic is about a half of the conventional method.