Internet of Things (IoT) analytics is an essential mean to derive knowledge and support applications for smart homes. Connected appliances and devices inside the smart home produce a significant amount of data about consumers and how they go about their daily activities. IoT analytics can aid in personalizing applications that benefit both homeowners and the ever growing industries that need to tap into consumers profiles. This article presents a new platform that enables innovative analytics on IoT captured data from smart homes. We propose the use of fog nodes and cloud system to allow data-driven services and address the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis. We discuss in this paper the requirements and the design components of the system. To validate the platform and present meaningful results, we present a case study using a dataset acquired from real smart home in Vancouver, Canada. The results of the experiments show clearly the benefit and practicality of the proposed platform.