Chungsan Lee

Bio: Chungsan Lee is an academic researcher from Kangwon National University. The author has contributed to research in topics: Parking guidance and information & Wireless sensor network. The author has an hindex of 3, co-authored 6 publications receiving 52 citations.

Smart parking system for Internet of Things

Abstract: In this paper, we propose a smart parking system detecting and finding the parked location of a consumer's vehicle. Using ultrasonic and magnetic sensor, the proposed system detects vehicles in indoor and outdoor parking fields, accurately. Wireless sensor motes support a vehicle location service in parking lots using BLE.

Smart Parking System Using Ultrasonic Sensor and Bluetooth Communication in Internet of Things

Abstract: IoT (Internet of Things) technologies have largely contributed to our smart living environment. The smart parking system is one of the prominent services that IoT supports. To identify the parked vehicles, the previous parking system use special identifying devices, the RFID tags carried by the users, and the high quality camera to recognize the vehicle license numbers. However, the previous methods cause cost inefficiency and unfriendly usages. To address these problems, we propose a smart parking system based on ultrasonic sensors and Bluetooth communication. The proposed system decides the available slots by using the sensor motes located in the parking spaces. Also it recognizes the location of the parked vehicle using Bluetooth RSSI between a Smartphone and the sensor motes. In addition, based on these converging technologies, it can support the parked routes of vehicles for users. To evaluate the implemented smart parking system, we applied the RSSI transform equations and the recognition rate for parked vehicles. As a result, the accurate rate of transformed distances could be measured.

The smart shoes providing the gait information on IoT

Abstract: This paper proposes the smart shoes system classifying a normal, out-toeing, and in-toeing gait to provide the gait information to customer. It measures and analyzes the gait posture using the distribution of pressure sensors on the insole. It sends the gait information to the smartphone application using a BLE communication. The experiment was performed to test the accuracy of proposed system. Finally, this paper showed that proposed system can measure the accurate gait posture.

Smart umbrella for safety directions on Internet of Things

Abstract: The smart umbrella not only blocks a rain but also provides a variety of services to customers. Existing smart umbrellas have various features such as giving an alarm for raining and a loss prevention. In this paper, we propose new smart umbrella that guides the way to the destination on rainy days, collaborating with smartphone based on the IoT environment. It prevents to safety accident which occurs due to operating the smartphone for navigating. Also, it provides a convenience to customer according to self-navigating.

MinT: Middleware for coope rative interactions of things

Abstract: This paper proposes an integrated middleware platform providing a development environment to use numerous types of sensors and network devices. Using proposed API, developers can easily develop IoT Application. Furthermore, they operate not only most of IoT device platform low and high process but also two or more network protocols.

Data Fusion and IoT for Smart Ubiquitous Environments: A Survey

Abstract: The Internet of Things (IoT) is set to become one of the key technological developments of our times provided we are able to realize its full potential. The number of objects connected to IoT is expected to reach 50 billion by 2020 due to the massive influx of diverse objects emerging progressively. IoT, hence, is expected to be a major producer of big data. Sharing and collaboration of data and other resources would be the key for enabling sustainable ubiquitous environments, such as smart cities and societies. A timely fusion and analysis of big data, acquired from IoT and other sources, to enable highly efficient, reliable, and accurate decision making and management of ubiquitous environments would be a grand future challenge. Computational intelligence would play a key role in this challenge. A number of surveys exist on data fusion. However, these are mainly focused on specific application areas or classifications. The aim of this paper is to review literature on data fusion for IoT with a particular focus on mathematical methods (including probabilistic methods, artificial intelligence, and theory of belief) and specific IoT environments (distributed, heterogeneous, nonlinear, and object tracking environments). The opportunities and challenges for each of the mathematical methods and environments are given. Future developments, including emerging areas that would intrinsically benefit from data fusion and IoT, autonomous vehicles, deep learning for data fusion, and smart cities, are discussed.

A navigation and reservation based smart parking platform using genetic optimization for smart cities

Abstract: With the development of technology, smart devices are becoming more common in everyday life. The development of devices that can connect to the Internet and transmit data has been a source of inspiration for smart city designs. The common problem in our cities is the difficulty of finding free parking slots. The parking problem causes traffic to congest and people who go to work are looking for a place. In this study, a navigation and reservation based parking proposal system was developed for smart cities. The proposed method involves the development of small devices that send data to the internet using the internet of things (IoT) technology. The free parking space closest to the current location is found by genetic algorithm. The proposed method is tested for different scenarios and accurate results are obtained.

A Review of Internet of Things Technologies for Ambient Assisted Living Environments

Abstract: The internet of things (IoT) aims to extend the internet to real-world objects, connecting smart and sensing devices into a global network infrastructure by connecting physical and virtual objects. The IoT has the potential to increase the quality of life of inhabitants and users of intelligent ambient assisted living (AAL) environments. The paper overviews and discusses the IoT technologies and their foreseen impacts and challenges for the AAL domain. The results of this review are summarized as the IoT based gerontechnology acceptance model for the assisted living domain. The model focuses on the acceptance of new technologies by older people and underscores the need for the adoption of the IoT for the AAL domain.

Smart mobility: A survey

Abstract: Internet of Things (IoT) describes a world where everyday objects are always connected to the Internet, allowing them to communicate and interact with each other. By connecting these everyday objects to the Internet and making them available everywhere at any time, IoT allows to remotely monitor, manage, and gather status information about them and their surrounding environment. IoT is a revolutionary concept that brought new experiences to everyday life and enabled Smart City initiatives all over the world. These initiatives are using a combination of technology paired with physical infrastructure and services, to improve people's quality of life. One of the high-priority domain to support the Smart City's vision is the field of Smart Mobility. This paper reviews the current IoT approaches and concepts related to Smart Cities and Smart Mobility. In addition, it analyzes distinct features and numerous applications covering both Intelligent Transportation and Real Time Traffic Management Systems.

Vacant Parking Slot Detection in the Around View Image Based on Deep Learning

Abstract: Due to the complex visual environment, such as lighting variations, shadows, and limitations of vision, the accuracy of vacant parking slot detection for the park assist system (PAS) with a standalone around view monitor (AVM) needs to be improved. To address this problem, we propose a vacant parking slot detection method based on deep learning, namely VPS-Net. VPS-Net converts the vacant parking slot detection into a two-step problem, including parking slot detection and occupancy classification. In the parking slot detection stage, we propose a parking slot detection method based on YOLOv3, which combines the classification of the parking slot with the localization of marking points so that various parking slots can be directly inferred using geometric cues. In the occupancy classification stage, we design a customized network whose size of convolution kernel and number of layers are adjusted according to the characteristics of the parking slot. Experiments show that VPS-Net can detect various vacant parking slots with a precision rate of 99.63% and a recall rate of 99.31% in the ps2.0 dataset, and has a satisfying generalizability in the PSV dataset. By introducing a multi-object detection network and a classification network, VPS-Net can detect various vacant parking slots robustly.