With the development of smart sensorial media, things, and cloud technologies, smart healthcare is getting remarkable consideration from academia, government, industry, and the healthcare community. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality with a massive amount of data and numerous services. Cloud computing fits well as enabling technology in this scenario as it presents a flexible stack of computing, storage, and software services at a low cost. Cloud-based services can provide a high quality of experience to physicians, clinics, and other caregivers anytime and from anywhere seamlessly.

However, the convergence of IoT and the cloud can provide new opportunities for both technologies. IoT cloud convergence can play a significant role in smart healthcare by offering better insight into heterogeneous healthcare content (e.g., X-rays, ECG, MRI, ultrasound images, clinical notes, claims, and so on) to support affordable and quality patient care. It can also support powerful processing and storage facilities of substantial IoT data streams (big data) beyond the capability of individual "things" as well as to provide automated decision-making in real-time. While researchers have been making advances in the study of IoT and cloud services individually, very little attention has been given to developing cost-effective and affordable smart healthcare services. The IoT cloud convergence for smart healthcare has the potential to revolutionize many aspects of our society, however, many technical challenges need to be addressed before this potential can be realized. Some of these challenges include: How to use the combined potential of IoT and cloud services or applications for providing smart healthcare solutions? How can these technologies assist with the right patient care at the right time and in the right place? How IoT cloud convergence along with healthcare big data analytics can facilitate healthcare data representation, storage, analysis, and integration for effective smart healthcare solutions?

This Special Issue intends to report high-quality research on recent advances toward smart sensorial technologies for smart healthcare, more specifically state-of-the-art approaches, methodologies, and systems for the design, development, deployment, and innovative use of those convergence technologies for providing insights into smart healthcare service demands.

Potential topics include but are not limited to the following:

• Intelligent techniques for IoT cloud enabled connected healthcare
• Enabling IoT cloud convergence technologies for smart healthcare
• Machine learning for medical sensorial big data analytics
• Energy-efficient data offloading and computing for smart sensors in healthcare applications
• Medical IoT and big data analytics
• IoT cloud for human activity monitoring
• Context-aware situation understanding for smart healthcare
• Deep learning approaches for smart healthcare
• Privacy and security issues in sensorial data management of smart healthcare
• Dynamic resource provisioning for mobile healthcare
• Techniques, algorithms, and methods of processing smart healthcare data over the IoT cloud