Neurorehabilitation has become a highly critical field of interest in the field of modern medical care, especially for geriatric patients and those disabled individuals affected by a variety of cognitive disorders. The field has been widely popular due to the overwhelming need for effective treatment protocols that can improve the quality of life of such vulnerable populations. In addition, with the exponential and remarkable development of portable technologies, the use of IoT-based sensor networks, together with the integration of artificial intelligence, there has been a visible and strong trend towards more advanced therapy models and driven by data that can provide more advanced attention and rehabilitation results. This chapter has an exhaustive and deep examination of cognitive therapy based on AI, especially in the broadest context of Neurorehabilitation. The chapter emphasizes the vital forms in which portable devices, IoT communication protocols and automatic learning algorithms can work integrally in the service of a variety of aspects of significant attention. These include continuous monitoring of patient progress, early detection of cognitive deterioration and personalized support based on the individualized needs of each patient who is rehabilitated. The chapter is informed by three main objectives: understand how smart medical care systems can collect and integrate data with portable technology; understand the application of sensor networks and IoT communication protocols to facilitate the transfer of health data without problems; and explore AI and ML methods of prediction and decision making in therapy environments. Conceptual and literature-informed, the chapter brings light to the technological, clinical, and pragmatic aspects of implementing smart neurorehabilitation architectures, providing insightful information for researchers, practitioners, and policy-makers working in the area of cognitive healthcare innovation.