Abstract: In the first instance it aims to it provide an overview addressing the state-of-the-art in the area of activity recognition in Smart homes. Smart homes are augmented residential environments equipped with sensors, actuators and devices. In early method, they used data-driven approaches only for sensor data in this paper introduces a knowledge-driven approach to real-time, continuous activity recognition and describe the underlying ontology-based recognition process. We analyze the characteristics of smart homes and Activities of Daily Living (ADL) upon which we built both context and ADL ontologies.we will concern ourselves with one type of stochastic signal model is hidden markov model for recognition process.