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Environmental noise is a major environmental concern in metropolitan cities. The rapid social and economic growth in the 20th century is not always accompanied by adequate land planning and environmental management measures. As a consequence of rapid urbanization processes, cities are facing an increase in noise pollution. Noise is being recognized as a serious environmental problem and one which must be accounted for in a sustained development policy designed to improve the quality of life for citizens. Therefore, the monitoring of noise is a crucial aspect of urban planning to allow urban planners to create harmonious and livable environments for communities worldwide. This research aims at assessing the noise levels and associated sources of noise in downtown areas through the involvement of crowdsourcing techniques. The incorporation of noise mapping and increased public awareness are achieved by a framework that enables a comparative scheme between two cities: Alexandria, Egypt and Zagreb, Croatia. The methodology depends on combining crowdsourcing techniques using mobile applications and geographic information system (GIS) tools to detect and analyze noise. Finally, this research provides a comparison between the two cities using the adopted methodology and introduces recommendations to enhance urban planning decisions. [ABSTRACT FROM AUTHOR]

Environmental noise is a major environmental concern in metropolitan cities. The rapid social and economic growth in the 20th century is not always accompanied by adequate land planning and environmental management measures. As a consequence of rapid urbanization processes, cities are facing an increase in noise pollution. Noise is being recognized as a serious environmental problem and one which must be accounted for in a sustained development policy designed to improve the quality of life for citizens. Therefore, the monitoring of noise is a crucial aspect of urban planning to allow urban planners to create harmonious and livable environments for communities worldwide. This research aims at assessing the noise levels and associated sources of noise in downtown areas through the involvement of crowdsourcing techniques. The incorporation of noise mapping and increased public awareness are achieved by a framework that enables a comparative scheme between two cities: Alexandria, Egypt and Zagreb, Croatia. The methodology depends on combining crowdsourcing techniques using mobile applications and geographic information system (GIS) tools to detect and analyze noise. Finally, this research provides a comparison between the two cities using the adopted methodology and introduces recommendations to enhance urban planning decisions.

A fast preprocessing Least Square-Constant Modulus Algorithm (LS-CMA) is proposed for blind adaptive beamforming. This new preprocessing method precludes noise capture caused by the original LS-CMA with the preprocessing procedure controlled by the static Constant Modulus Algorithm (CMA). The simulation results have shown that the proposed fast preprocessing LS-CMA can effectively reject the co-channel interference, and quickly lock onto the constant modulus desired signal with only one snapshot in a highly corruptive environment. [ABSTRACT FROM AUTHOR]