• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.11a
• /
• pp.48-53
• /
• 2006

Noise mapping is performed in the city of Cheongju which has 626,614 inhabitants on a $153.41km^2$ area. This city has 71,387 buildings and 969,274m roads. Many database sets like information of roads, topography and buildings are required for making the noise map of large area. These database sets are provided by the various departments of the regional administration in Cheongju city. Using the given database sets, 3-dimensional model of topography and buildings are made to consider the multi-reflections and diffractions. A predicted noise level is compared with measured noise level of the road traffic noise. As the tool of management and decision of urban noise policy, noise map is combined into the map of land use to make the conflict noise map. This conflict noise map is useful to assess the present urban noise and to make the better life in complicated urban life.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.04a
• /
• pp.882-888
• /
• 2008

The increase in logistics and the emergence of high speed vehicles are aggravating the noise problem, and disturbing large numbers of people. Therefore, growing attention is being paid to the creation and utilization of a noise map in order to grasp and predict the influence of noise, and to establish a policy that effectively reduces noise. However, so far there has been little progress in developing a predictive formula for railway noise, and a noise prediction program suitable for the domestic environment. Therefore, there is a need for a method to apply the overseas prediction formula to domestic railway vehicles. This study evaluated the prediction method, the result of which is similar to that of a real measurement, using a noise map. It also employed a commercial software program, SoundPlan, to predict noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.10a
• /
• pp.163-168
• /
• 2011

Noise map is drawn up under launch environment through analyzing jet noise of guided weapon in this research. This has an important significance in terms of having an opportunity to look at influence of noise which is caused by guided weapon in the surrounding environment. In this paper, the magnitude of jet noise that was measured by using microphone and the result of numerical analysis that was gained by using ENPro which is environment noise prediction program are shown. At this point estimation of noise source was based on ISO 9613. Finally noise map derived from results mentioned above will become useful material when setting safety guide for protecting hearing loss of operator of weapon system in the future.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.10
• /
• pp.802-808
• /
• 2014

The purpose of this study is to suggest efficient methods for estimating population exposed to noises by analyzing differences of population exposed to noises estimated by each method through comparing exposed population estimated by utilizing existing methods and those estimated by using census output areas reflecting the actual population information of each address. For population exposed to noises, the error of exposed population estimated by using the per capita living space turned out to be the biggest, and other estimation methods had no significant difference. For population exposed to excess noises, as a result of analyzing population estimated by each method based on census output areas, the error of the method using a grid noise map turned out to be the biggest. For the method to estimate population exposed to noises by using a noise map, the estimation methods using census output areas and total ground area are considered to be more rational than the grid noise map estimation method or the method to estimate the living space per capita.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.4
• /
• pp.174-183
• /
• 2021

This study aims to suggest a method to provide a real-time noise map based on cloud using Amazon AWS. Acquiring environmental noise information, an Android app was developed to collect data on noise level, location, and measurement time of campus in Inha Technical College as a study area. Noise measurement information is transmitted to the AWS Cloud and managed, and the noise information collected through Amazon Quick Site is displayed in charts and maps. Finally, a web-based noise contour map and the results mapped to buildings were visualized with a Google map for users to search for the current environmental noise distribution. The real-time noise map presented as a result of this study is expected to be helpful for noise status and reduction policies.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.05a
• /
• pp.877-881
• /
• 2007

Recently, noise map is used widely by synthetic estimation method for noise reduction. For correct manufacture of noise map, selection of suitable noise prediction method is important. This study compares XPS31-133 with CRTN, RLS90 which are widely used by foreign commercial noise maps.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2013.10a
• /
• pp.605-610
• /
• 2013

This study proposes an analysis model to simulate a noise map and estimate noise distribution for a location and its surroundings of a power plant. The noise map analysis was executed by using ENPro that is a commercial program for environmental noise prediction. Experimental evaluation for the proposed analysis model was carried out by comparing the results from noise analysis and measurement at several major points of the power plant and residential areas.

• Journal of Environmental Science International
• /
• v.16 no.7
• /
• pp.823-830
• /
• 2007

Traffic noise is a kind of noise caused by cars, trains and aircraft. Among them, noise produced by cars is the most important factor in cities. According to the National Institute of Environmental Research(NIER)'s survey, Road traffic noise levels in Susan are the highest of all the cities in Korea. So, appropriate measures for road traffic noise reduction is required. For this purpose, the construction of a noise map in Susan will playa vital role. However, road traffic noise formulas are constructed considering regional characteristics such as each country road's environment and vehicle quality. Therefore, prior to constructing a noise map in Susan, examination processes about each formula constituent status and estimation process are required preferentially. In this research, the basic first stage is to estimate Susan's road traffic noise. First, investigate characteristics of each road traffic noise estimate and using this, a noise map is constructed for road traffic noise in Susan. Then the adaptation of a road traffic noise formula is evaluated.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.3
• /
• pp.15-20
• /
• 2003

For some applications such as teleconference or telecommunication systems using a distant-talking hands-free microphone, the near-end speech signals to be transmitted is disturbed by an ambient noise and by an echo which is due to the coupling between the microphone and the loudspeaker. Furthermore, the environmental noise including channel distortion or additive noise is assumed to affect the original input speech. In the present paper, a new approach using echo canceller and maximum a posteriori(MAP) estimation is introduced to improve the accuracy of hands-free speech recognition. In this approach, it was shown that the proposed system was effective for hands-free speech recognition in ambient noise environment including echo. The experimental results also showed that the combination system between echo canceller and MAP environmental adaptation technique were well adapted to echo and noise environment.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.23 no.4
• /
• pp.295-300
• /
• 2013

The noise map can be applied to predict the effect of noise and establish the noise reduction measure. But the predicted value in the noise map can vary depending on the input variables. Thus, we surveyed the several prediction models and analyzed the changes corresponding to the variables for obtaining the coherency and accuracy of prediction results. As a result, we know that the Schall03 and CRN model can be applied to predict the railway noise in Korea and the correction value, such as bridges correction, multiple reflection correction, curve correction must be used for reflecting the condition of the prediction site. Also, we know that the prediction guideline is an essential prerequisite in order to obtain the unified and accurate predicted value for railway noise.