• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.27-38
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• 2019

Sensors collect information for Internet of Things (IoT)-based services. However, indoor construction sites have a poor communication environment and many interfering elements that make it difficult to collect sensor information. In this study, a network was constructed between a Bluetooth Low Energy (BLE)-based IoT device based on a serverless IoT framework and a router. This experimental environment was applied to large- and small-scale indoor construction sites. Experiments were performed to test the communication performance of BLE-based IoT devices and routers at indoor construction sites. An analysis of the received signal strength indication (RSSI) graph patterns collected from the communication between the BLE-based IoT devices and routers for different testbed site situation revealed areas with good communication performance and poor communication performance due to interfering factors. The results confirmed that structural components of the building as well as the materials, equipment, and temporary facilities used in indoor construction interfere with the communication performance. Construction project managers will require improved technical knowledge of IoT, such as optimizing the router placement and matching communication between the router and workers, to improve the communication performance for large-scale indoor construction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1049-1052
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• 2009

This paper develop a intelligent personal emergency call system using the wireless sensor network to resolve that a portable problem of established emergency call system. The proposed system is composed of a transmitter nodes for individuals, routing nodes for multihop communications, and a server part. The transmitters for patients are monitored for both low battery and operational status. The transmitters provide location of the person activating an emergency call using RSSI. The efficacy of the proposed system is verified by means of experiments. Experimental results are presented that show the effectiveness.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.456-457
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• 2021

Recently, in order to more accurately provide indoor location-based services, technologies using Wi-Fi fingerprints and deep learning are being studied. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. When using an RNN model for indoor positioning, the collected training data must be continuous sequential data. However, the Wi-Fi fingerprint data collected to determine specific location information cannot be used as training data for an RNN model because only RSSI for a specific location is recorded. This paper proposes a region clustering technique for sequential input data generation of RNN models based on Wi-Fi fingerprint data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.640-642
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• 2021

In order to collect a lot of data clearly and efficiently, it is essential to know the locations of the current facilities and analyze the movement data. The current location collection technology can collect data using a GPS (Global Positioning System) sensor, but in the case of GPS, it has strong straightness and low diffraction and reflectivity, making it difficult to position indoors. It is impossible to measure the distance between the server and the client because the signal sensitivity cannot be received. This paper implements an indoor positioning system using beacons and scanners in Raspberry Pi 3 B+. It controls Advertise Mode and Connection Mode at the same time using the scanner algorithm.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1022-1030
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• 2006

The location awareness is an important part of many ubiquitous computing systems, but a perfect location system does not exist yet in spite of many researches. Among various location tracking systems, we choose the RFID system due to its wide applications. However, the sensed RSSI signal is too sensitive to the direction of a RFID reader antenna, the orientation of a RFID tag, the human interference, and the propagation media situation. So, the existing location tracking method in spite of using the particle filter is not working well. To overcome this shortcoming, we suggest a robust location tracking method with a double layered structure, where the first layer coarsely estimates a tag's location in the block level using a regression technique or the SVM classifier and the second layer precisely computes the tag's location, velocity and direction using the particle filter technique. Its layered structure improves the location tracking performance by restricting the moving degree of hidden variables. Many extensive experiments show that the proposed location tracking method is so precise and robust to be a good choice for implementing the location estimation of a person or an object in the ubiquitous computing. We also validate the usefulness of the proposed location tracking method by implementing it for a real-time people monitoring system in a noisy and complicate workplace.

• 전자공학회논문지 IE
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• v.49 no.1
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• pp.12-17
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• 2012

Fast development of ubiquitous technology prompted the broadening of the related application area. Application of ubiquitous techniques and system into the construction sites may give us many benefits. There are always a lot of hazard situations in construction sites, and the falling is known to have the high accident rate. To prevent the falling, there has been a lot of efforts including safety education and use of safety gears. In this study, we designed, fabricated and tested a system that can monitor the worker's safety and location informations in real time by using the wireless technology of TOA and RSSI. We used ATmegal28 that is popular in the industrial equipments as MCU and NanoPan 5357 module from Nanotron and CC2500 chipset from TI for radio circuits. We also used 3-axis accelerometer and pressure MEMS sensors to obtain the environmental information, and therefore to aquire the informations of the worker's movement and altitude. We used Labview software from National Instrument to monitor and control the system. We developed the system to send the warning alarms to the server operator and the workers when the workers in the danger zone did not wear the safety hook.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1087-1096
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• 2011

Vehicular Ad Hoc Network(VANET) using wireless network is offering the communications between vehicle and vehicle(V2V) or vehicle and infrastructure(V2I). VANET is being actively researched from industry field and university because of the rapid developments of the industry and vehicular automation. Information, collected from VANET, of velocity, acceleration, condition of road and environments provides various services related with safe drive to the drivers, so security over network is the inevitable factor. For the secure message authentication, a number of authentication proposals have been proposed. Among of them, a scheme, proposed by Jung, applying database search algorithm, Bloom filter, to RAISE scheme, is efficient authentication algorithm in a dense space. However, k-anonymity used for obtaining the accurate vehicular identification in the paper has a weak point. Whenever requesting the righteous identification, all hash value of messages are calculated. For this reason, as the number of car increases, a amount of hash operation increases exponentially. Moreover the paper does not provide a complete key exchange algorithm while the hand-over operation. In this paper, we use a Received Signal Strength Indicator(RSSI) based velocity and distance estimation algorithm to localize the identification and provide the secure and efficient algorithm in which the problem of hand-over algorithm is corrected.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.409-414
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• 2010

The applications based on geographical location are increasing rapidly in wireless sensor networks (WSN). Recently, various localization algorithms have been proposed but the majority of algorithms rely on the specific hardware to measure the distance from the signal sources. In this paper, we propose the Weighted Multiple Rings Localization(WMRL). We assume that each deployed anchor node may periodically emit the successive beacon signals of the different power level. Then, the beacon signals form the concentric rings depending on their emitted power level, theoretically. The proposed algorithm defines the different weighting factor based on the ratio of each radius of ring. Also, If a sensor node may listen, it can find the innermost ring of the propagated signal for each anchor node. Based on this information, the location of a sensor node is derived by a weighted sum of coordinates of the surrounding anchor nodes. Our proposed algorithm is fully distributed and does not require any additional hardwares and the unreliable distance indications such as RSSI and LQI. Nevertheless, the simulation results show that the WMRL with two rings twice outperforms centroid algorithm. In the case of WMRL with three rings, the accuracy is approximately equal to WCL(Weighted Centroid Localization).

• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.61-64
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• 2000

In this paper, we design up-down converter for asynchronous IMT-2000 base station using W-CDMA(Wideband Code Division Multiple Access) technology. This up-down converter(UDC) has AGC (Automatic Gain Control), TPTL(Transmitting Power Tracing Loop), RSSI(Received Signal Strength Indicator) function. And for the cell control of BS(Base Station), breathing, blossoming, wilting function also available. This UDC has diversity structure for better performance.