Shabir Ahmad1, Jehad Ali2, Faisal Jamil3, Taeg Keun Whangbo1, DoHyeun Kim3,*
CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1271-1288, 2021, DOI:10.32604/cmc.2021.017773
Abstract Smart cities have different contradicting goals having no apparent solution. The selection of the appropriate solution, which is considered the best compromise among the candidates, is known as complex problem-solving. Smart city administrators face different problems of complex nature, such as optimal energy trading in microgrids and optimal comfort index in smart homes, to mention a few. This paper proposes a novel architecture to offer complex problem solutions as a service (CPSaaS) based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart city. Predictive model optimization uses a machine learning module and… More >
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