Artificial Intelligence, Data and Robotics: Foundations, Transformations and Future Directions | 2026
Authors: Sayyahi A.; Alavi S.E.; Jaderyan M.
DOI: 10.1007/978-3-032-10561-5_18
Journal: Artificial Intelligence, Data and Robotics: Foundations, Transformations and Future Directions
Year: 2026
Publisher: Springer Nature
Document Type: Book chapter
Open Access: All Open Access; Gold Open Access
Cited by: 0
Since the integration of robotics into the field of healthcare, considerable potential has arisen to transform the delivery of medical care, making services more precise, efficient, and accessible. Robotics has begun making the surgical, rehabilitation, and patient care realms its own. With the arrival of IoT and deep learning, the potential of these hybrid systems is accentuated with seamless connectivity, real-time data analysis, and intelligent decision-making. While IoT allows robotic devices to interact with other healthcare systems, deep learning enables robots to process massive datasets and learn from experience to better their performance. These two fields together are setting the stage for smarter, adaptive, and highly efficient healthcare solutions. As the demand for healthcare increases, the solutions through robotics using IoT and deep learning algorithms solve problems ranging from the lack of healthcare resources for minimally invasive procedures to the management of chronic diseases. For example, an IoT-enabled robotic system could monitor patient conditions in real time while adapting robot functions based on predictive analytics, whereas deep learning can identify patterns from more intricate datasets that lead to swifter and more accurate diagnoses. By bringing together these recently developed technologies, healthcare robotics is in for a dramatic restructuring of the generally accepted practice of medicine, whereby new solutions will emerge to enhance patient outcomes and streamline clinical workflows. © The Editor(s) (if applicable) and The Author(s) 2026.
Chronic disease management; Data security; Deep learning; Internet of Things (IoT); Patient monitoring; Real-time analytics; Rehabilitation robotics; Robotics in healthcare; Surgical assistance