Smart building involves a construction of multiple layer system that is capable to sense, acquire, analyze and perform the proper action to maintain the operation of certain city entity. The layered system incorporates six layers including: sensing layer, network layer, software layer, semantic discovery layer, processing and reasoning layer, and service layer. All the statistics show that there will be a large demand for smart buildings in the future as it has the potential for energy saving, indoor services such as tracking, mapping, localization, identifying products, and downloading relevant information are the main drive for future trends. The number of smart devices is expected to be x10 of the current number in 2020. Efficient Resource allocation for context aware based systems with the future demand for smart devices is challenging. Thus, it is essential to utilize techniques such as data mining and machine learning for data analytics, reasoning, and decision-making in order to maximize the smart building operation efficiency and overcome all the related challenges.​​