In a few decades, requests for assistance to the elderly will increase the already high health care costs. Within this context, a possible solution is represented by smart environments where services help dwellers' life. The development of smart technologies requires large datasets for training, validation or testing. Since the data collection from real smart homes has high costs the authors developed SHARON – a Simulator of Human Activity, ROutines and Needs. This software aims to support such projects, virtually reproducing environments and behaviors of the dwellers. This work proposes and validates a behavioral model able reproduce decisions and human habits, starting from an available data set or an interview. Physiological parameters and habits are merged with a probabilistic approach, choosing the most likely activity. With respect to other behavioral simulators available in the literature, SHARON is focused on routines and activities generation, based on user defined high level parameters. Within the evaluation phase it was applied a cross-validation approach, by simulating 300 days starting from a training set of 23 days and testing with the remaining 7 days validation set. As expected, results prove the simulated data correctly reproduce the activities routine distributions, in particular the more regular ones.