• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.5A
• /
• pp.466-473
• /
• 2010

Several protocols which are based on tree topology to guarantee the important metrics such as energy efficiency in sensor networks have been proposed. However, studies on the effect of topologies in sensor networks, where base node has a high mobility, are very few. In this paper, we propose a minimum Wiener index tree as a suitable topology to the wireless sensor networks with high mobile base node. The minimum Wiener index spanning tree problem which aims to find a tree with minimum Wiener index from a given weighted graph was proved to be NP-hard. We designed a branch and bound algorithm for this problem. To evaluate the performance of proposed tree, the comparisons with minimum spanning tree in terms of transmission distance, energy consumption during one round, and network lifetime was performed by simulations. Our proposed tree outperformed in transmission distance and energy efficiency but underperformed in lifetime.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2014.04a
• /
• pp.141-144
• /
• 2014

In urban spaces surrounded by buildings, trees could disperse sound energy, which affect sound level distribution and street canyon reverberation. Therefore, this paper examines the amount of scattered sound energy from a tree in open field by means of a reverberation time (RT). Five trees of different species and crown sizes were considered. The influential factors include crown size and shape, foliage condition, and source-receiver distance. The results show that RT is proportionally increased with the increase of tree crown sizes, which is the most determining factor. The maximum RT measured was 0.34 sec at 4000 Hz for the studied trees in leaf. The presence of leaves increased RT at high frequencies, typically by 0.14 sec at 4000 Hz. With increasing source-receiver distance within 40 m, RT was slightly changed.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.26 no.3
• /
• pp.104-117
• /
• 1998

Rising concern about climate change has evoked interest in the potential for urban vegetation to help reduce the level of atmospheric CO\sub 2\, a major heat-trapping gas. This study quantified the functio of home energy savings and carbon emission reduction by shading, evapotranspiration and windspeed reduction of urban vegetatioin in Chuncheon. Tree and shrub cover averaged approximately 13% in residential land. The effects of shading, evapotranspiration and windspeed reduction annually saved heating energy by 2.2% and cooling energy by 8.8%. The heating and cooling energy savings reduced carbon emissions by 3.0% annually. These avoided emissions equaled the amount of carbon emitted annually from fossil fuel consumption by a population of about 1,230. Carbon emission reduction per residential building was 55kg for detached buildings and 872 kg for multifamily buildings. Urban vegetation annually decreased heating and cooling energy cost by ￦1.1 billions, which were equivalent to annual savings of ￦10,000 savings and carbon emission reduction due to tree plantings in the wrong locations, while windspeed reduction had a great effect. Plantings fo large trees close to the west and east wall of buildings, full tree plantings on the north, and avoidance of shade-tree plantings or selection of solar-friendlytrees on the south were recommended to improve the function of building energy savings and carbon emission reduction by urban vegetation.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.42 no.1
• /
• pp.41-49
• /
• 2014

This study spatially assesses the impact of trees on residential rooftop solar energy potential using urban three-dimensional models derived from Light Detection and Ranging(LiDAR) data in San Francisco, California. In recent years on-site solar energy generation in cities has become an essential agenda in municipal climate action plans. However, it can be limited by neighboring environments such as shade from topography, buildings and trees. Of all these effects, the impact of trees on rooftop photovoltaics(PVs) requires careful attention because improper situation of solar panels without considering trees can result in inefficient solar energy generation, tree removal, and/or increasing building energy demand and urban heat island effect. Using ArcMap 9.3.1, we calculated the incoming annual solar radiation on individual rooftops in San Francisco and the reduced insolation affected by trees. Furthermore, we performed a multiple regression analysis to see what attributes of trees in a neighborhood(tree density, tree heights, and the variance of tree heights) affect rooftop insolation. The result shows that annual total residential rooftops insolation in San Francisco is 18,326,671 MWh and annual total light-loss reduction caused by trees is 326,406 MWh, which is about 1.78%. The annual insolation shows a wide range of values from $34.4kWh/m^2/year$ to $1,348.4kWh/m^2/year$. The result spatially maps the locations that show the various levels of impact from trees. The result from multiple regression shows that tree density, average tree heights and the variation of tree heights in a neighborhood have statistically significant effects on the rooftop solar potential. The results can be linked to municipal energy planning in order to manage potential conflicts as cities with low to medium population density begin implementing on-site solar energy generation. Rooftop solar energy generation makes the best contribution towards achieving sustainability when PVs are optimally located while pursuing the preservation of urban trees.

• Journal of KIISE:Information Networking
• /
• v.34 no.5
• /
• pp.360-369
• /
• 2007

Since wireless sensor networks consist of nodes with the constrained battery, it is important to construct the topology performing energy-efficient routing while maximizing the whole network lifetime. Previous works related to this do not take into consideration the specific communication pattern in wireless sensor networks. In this paper, we propose a novel routing algorithm, called Up-Down Tree(UDT), which first constructs the tree topology based on distance and then adjusts the transmission range determined by the two different phases, tree setup and data gathering, to adapt the specific communication pattern in wireless sensor networks. Therefore, the UDT can improve energy efficiency, maximize the network lifetime, and block network partition Simulation results show that the UDT has the improved energy efficiency by constructing the optimal topology.

• The KIPS Transactions:PartC
• /
• v.17C no.1
• /
• pp.69-80
• /
• 2010

Wireless sensor networks (WSN) consisting of a large number of sensors aim to gather data in a variety of environments and are being used and applied to many different fields. The sensor nodes composing a sensor network operate on battery of limited power and as a result, high energy efficiency and long network lifetime are major goals of research in the WSN. In this paper we propose a novel tree-based clustering approach for energy efficient wireless sensor networks. The proposed scheme forms the cluster and the nodes in a cluster construct a tree with the root of the cluster-head., The height of the tree is the distance of the member nodes to the cluster-head. Computer simulation shows that the proposed scheme enhances energy efficiency and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes such as LEACH, PEGASIS, and TREEPSI.

• Journal of the Korean Solar Energy Society
• /
• v.37 no.2
• /
• pp.23-33
• /
• 2017

Accurate prediction of stochastic behavior of occupants is a well known problem for improving prediction performance of building energy use. Many researchers have been tried various sensors that have information on the status of occupant such as $CO_2$ sensor, infrared motion detector, RFID etc. to predict occupants, while others have been developed some algorithm to find occupancy probability with those sensors or some indirect monitoring data such as energy consumption in spaces. In this research, various sensor data and energy consumption data are utilized for decision tree algorithms (C4.5 & CART) for estimation of sub-hourly occupancy status. Although the experiment is limited by space (private room) and period (cooling season), the prediction result shows good agreement of above 95% accuracy when energy consumption data are used instead of measured $CO_2$ value. This result indicates potential of IoT data for awareness of indoor environmental status.

• Journal of the Korean Solar Energy Society
• /
• v.31 no.6
• /
• pp.32-39
• /
• 2011

This study is about the installation of the solar cell modules. The solar cell modules are built by the tree-mimic structure, and the performance is compared with that of the flat-plate type solar cell module installation. The mathematical tree model, which was suggested by Fisher and Honda, is utilized to determine the location of the solar cell modules for the tree-mimic type. The experiment shows that the generated electric power of the flat-plate type is higher than that of the tree-mimic type by 30% for one month of July. This lower performance for the tree-mimic type comes from the shading effects among the solar cell modules. The theoretical calculation for the absorbed solar radiation on the two types of solar cell installation shows that the tree-mimic type is higher than the flat-plate type by 8.5%. The shading area for the tree-mimic model is calculated with time by using the 3D-CAD, which will be utilized for the optimization of the tree-mimic model in the future.

• Journal of Information Processing Systems
• /
• v.14 no.2
• /
• pp.396-417
• /
• 2018

GR-tree and query aggregation techniques have been proposed for spatial query processing in conventional spatial query processing for wireless sensor networks. Although these spatial query processing techniques consider spatial query optimization, time query optimization is not taken into consideration. The index reorganization cost and communication cost for the parent sensor nodes increase the energy consumption that is required to ensure the most efficient operation in the wireless sensor node. This paper proposes itinerary-based R-tree (IR-tree) for more efficient spatial-temporal query processing in wireless sensor networks. This paper analyzes the performance of previous studies and IR-tree, which are the conventional spatial query processing techniques, with regard to the accuracy, energy consumption, and query processing time of the query results using the wireless sensor data with Uniform, Gauss, and Skew distributions. This paper proves the superiority of the proposed IR-tree-based space-time indexing.

• Transactions of the Korean hydrogen and new energy society
• /
• v.25 no.6
• /
• pp.609-619
• /
• 2014

In the present study, the frequency of the undesired accident was estimated for a quantitative risk assessment of a large-scale hydrogen liquefaction plant. As a representative example, the hydrogen liquefaction plant located in Ingolstadt, Germany was chosen. From the analysis of the liquefaction process and operating conditions, it was found that a $LH_2$ storage tank was one of the most dangerous facilities. Based on the accident scenarios, frequencies of possible accidents were quantitatively evaluated by using both fault tree analysis and event tree analysis. The overall expected frequency of the loss containment of hydrogen from the $LH_2$ storage tank was $6.83{\times}10^{-1}$times/yr (once per 1.5 years). It showed that only 0.1% of the hydrogen release from the $LH_2$ storage tank occurred instantaneously. Also, the incident outcome frequencies were calculated by multiplying the expected frequencies with the conditional probabilities resulting from the event tree diagram for hydrogen release. The results showed that most of the incident outcomes were dominated by fire, which was 71.8% of the entire accident outcome. The rest of the accident (about 27.7%) might have no effect to the population.