The field of smart homes has gained notable attention from both academia and industry. The majority of the work has been directed at regular users, and less attention has been placed on users with special needs, particularly those with mobility problems or quadriplegia. Brain computer interface has started the mission of helping people with special needs in smart homes by developing an environment that allows them to make more independent decisions. This study investigates the efforts made in the literature for smart homes that have been established to manage and control home components by disabled people and makes a comparison between the reviewed papers, in terms of the controlled devices, the central controller, the people with disabilities the system is meant for, whether or not machine learning was used in the system, and the system's command method. In the field of machine learning-based smart homes for disabled people, the limitations have been pointed out and talked about. Current challenges and possible future directions for further progress have also been given.