Hyunhak Kim

Escaping from ancient Rome! Applications and challenges for designing smart cities

From ancient Europe, the renaissance and industrialisation eras, to the modern times, urban planning paradigms have evolved in many ways, advancing the environments where people live in. Nevertheless, the recent development of wireless and wired communication network technologies and low-power miniature sensors for various application domains provide us with another chance of revolutionising cities by making them smarter. Smart cities, propelled by a city-scale infrastructure, where information provided from different application systems integrate together, will initiate the development of new applications that can benefit our everyday lives. This article presents an overview of representative applications that consist a smart city with their respective challenges and application requirements. Furthermore, we share our experiences obtained from designing and deploying examples of such smart systems in multiple application domains and summarise the remaining challenges for making the vision of designing smart cities a reality. Copyright

ReLiSCE: Utilizing Resource-Limited Sensors for Office Activity Context Extraction

The capability to extract human activity context in a room environment can be used as meaningful feedback for various wireless indoor application systems. Being able to do so with easily installable resource-limited sensing components can even further increase the systems applicability for various purposes. This paper introduces our efforts to design a system consisting of heterogeneous low-cost, resource-limited, wireless sensing platforms for accurately extracting the human activity context from an indoor environment. Specifically, we introduce Resource Limited Sensor-based activity Context Extraction (ReLiSCE), a system consisting of microphone array, passive infra-red (PIR), and illumination sensors that effectively detect the activities that occur in an office (meeting room) environment. The signal processing schemes used in ReLiSCE are designed so that their size and complexity is suitable for the resource limitations that many embedded computing platforms introduce. Using empirical evaluations with a prototype system, we show that despite the simplicity of its data processing schemes, ReLiSCE successfully classifies human activity states in various meeting scenarios. Furthermore, we show that high accuracy is achieved by combining results from heterogeneous sensors. We foresee this paper as a sub-system that interconnects with various application systems for autonomously configuring peoples everyday living environments in a more comfortable and energy-efficient manner.

Multitiered and Distributed WSAN for Cooperative Indoors Environment Management

For the past decade, wireless sensor networks have focused primarily on data collection. As a result the network topology for these systems was usually heavily centralized. However, for these networks to form a full system, the introduction of proper actuation units and decision-making intelligence is inevitable. Such a new wireless sensor and actuator network system enables new architectural research issues that have not been previously studied. In this work, we introduce the DWSAN system architecture, which effectively combines both sensor and actuation hardware devices to a single network and manages this network so that the actuation decisions are made in a distributed manner and the topology of the network maintains a multitier architecture. Our intensive set of evaluations reveal that, compared to the centralized approach that has been used in most wireless sensor network systems until now, when actuation units are introduced to the system, the DWSAN architecture reduces the transmission load of the network and the actuation decision-making latency by close to twofold and threefold, respectively. Furthermore, we show that this benefit naturally leads to better scalability of the system, making it suitable for various sensing applications in different environments.

Interface design from pipeline safety unit to roadside subsidence risk index system

A sinkhole is occurring in urban area all over the world frequently, in fact, it is a roadside subsidence in geological terminology, which can harm property and safety of government and many people. To detect the roadside subsidence earlier, we monitor the aged or damaged underground infrastructures, report the sensed the values to analyzing system, and draw out the risk index of the roadside subsidence in that area. In this paper, we shows interface design in order to show important features of the leakage detection unit and underlying concepts of the roadside subsidence risk index system.

Projecting household-scale utility usage: a case study using a long-term dataset

The deployment of advanced metering infrastructures allows suppliers and consumers to better understand the utility supply and usage chain. Data from these systems are typically used to analyse utility usage in a large scale, but when observed at smaller scales, we can enable a number of interesting new application. In this work we use utility usage data collected from 300 households over three years and perform detailed analysis to understand per-household utility usage patterns. We show that per-household utility usage data introduces high variances and low correlations among different households even if they are co-located in similar geographical regions. Using our findings, we introduce AUUP, an adaptive utility usage prediction scheme that combines the output from different existing forecasting schemes to adaptively make smart small-scale utility usage predictions. Our evaluations show that AUUP effectively reduces the prediction errors of artificial neural networks, LMS and Kalman filter-based AR model prediction schemes.

Retrieval of the Extreme Values under Deadline Constraints in Wireless Sensor Networks

We consider a problem of retrieving the extreme value among sensed data under deadline constraints in wireless sensor networks with potential applications to alarm systems. The sensed data is mapped to a score which we adopt as a unified measure of the relative urgency of the data. The objective is to retrieve the data with the maximum score. We propose fully distributed schemes for contention based medium access and data combining. The proposed medium access scheme uses a randomized back-off which is controlled based on the score of the data to be transmitted. Data combining techniques are proposed to further suppress unnecessary traffic and reduce contention. The key observation is that one should aggressively prioritize packets with high score, up to an extent that does not incur excessive contention in channel access. Designed to capture such aspect, the proposed scheme is shown to substantially decrease the latency of the retrieval.

Molecular beam epitaxy growth of InP-based lattice-matched high electron mobility transistor structures having a modified quantum-well profile due to AlxGayIn1 − x − yAs(x + y = 0.47−8) buffer layer

Abstract The quaternary compound, Al x Ga y In 1 − x − y As ( x + y = 0.47−8) lattice-matched to InP substrates was realized as a buffer layer in an InP-based lattice-matched high electron mobility transistors. The band gap energy of this quaternary compound buffer layer was linearly decreased from E g = 1.54 eV for Al 0.48 Ga y =0 In 0.52 As to E g = 0.82 eV for Al x =0 Ga 0.47 In 0.53 As by varying Al and Ga mole fraction simultaneously. A self-consistent analysis revealed, one, that this buffer layer modified the quantum-well structure into a triangular-shaped conduction-band profile and, two, the disappearance of the quantum-well in valance-band profile. By forming a triangular-shaped conduction-band quantumwell, carrier wave functions drifted farther apart from the heterointerface, leading to the reduction of ionized impurity scattering. Disappearance of holes in a valance band also contributed to the reduction of the hole and electron recombination scattering. A high electron mobility of 11 338 cm 2 /V s with two-dimensional electron gas density of 2.5 × 10 12 /cm 2 was achieved at room temperature. The high electron mobility was believed to have resulted from the modified triangular-shape quantum well in which the ionized impurity ion scattering was suppressed. We believe that we have achieved the highest room temperature value of electron mobility time with two-dimensional electron gas concentration that was 2.83 × 10 16 /cm 2 to date for InP-based lattice-matched high electron mobility transistors system. PL measurement showed some evidences of a high-quality epitaxial growth.