# Smart Hospitals and IoT Sensors: Why Is QoS Essential Here?
###### Abstract  
Background: the increasing adoption of smart and wearable sensors in the healthcare domain empowers the development of cutting-edge medical applications. Smart hospitals can employ sensors and applications for critical decision-making based on real-time monitoring of patients and equipment. In this context, quality of service (QoS) is essential to ensure the reliability of application data. Methods: we developed a QoS-aware sensor middleware for healthcare 4.0 that orchestrates data from several sensors in a hybrid operating room. We deployed depth imaging sensors and real-time location tags to monitor surgeries in real-time, providing data to medical applications. Results: an experimental evaluation in an actual hybrid operating room demonstrates that the solution can reduce the jitter of sensor samples up to 90.3%. Conclusions: the main contribution of this article relies on the QoS Service Elasticity strategy that aims to provide QoS for applications. The development and installation were demonstrated to be complex, but possible to achieve. healthcare 4.0; internet of things; sensors; middleware; quality of service +
Footnote †: journal: journal: Sensors and Actuator Networks  
employed for ICU patients with Coronavirus Disease 2019 (COVID-19) to identify the relation between many indicators [10]. Figure 1 presents an overview of future medical processes. Internet of Things (IoT) is spreading among several areas, paving the way to a new industrial revolution [6; 11]. In hospitals, this is not different [4]. This context encompasses the numerous sensor devices scattered all over the hospital setting generating information from various assets, including the patient and the medical team. Currently, artificial intelligence applications emerge to handle an increasing data volume. It supports the medical team by providing information to help them perceive dangerous situations and patient condition deterioration. Medical processes are highly critical, and errors or delays in handling critical situations may harm the patient and even lead to death. With a wide variety of data provided by IoT technology, centralized systems provide a global analysis of data from patients improving healthcare services. Although positive, centralized systems suffer from scalability problems which may increase the delay in data transmission. Scalability is the ability of a system to maintain its performance and quality of service (QoS) regardless of the input workload and internal processing [12]. Centralized systems concentrate data processing at a single point. As the number of sensors and applications connected increases, the system can lose performance due to network overload. That would cause instabilities in the data flow to different systems, which can be critical depending on the application. Therefore, a sensor data middleware for medical settings must provide QoS to the applications. Currently, some studies are focusing on improving network performance using routing protocols [13; 14]. However, they still suffer from problems such as network node overload [13] or lack of focus on acute care environments such as the operating room [14]. Focusing on providing QoS for such infrastructures, this article presents the design and implementation of a sensor middleware for medical settings called HealthStack. HealthStack introduces techniques to automatically adapt itself to workload changes to deliver the same QoS to applications. HealthStack works as a wrapper for applications to access data from many devices installed in many medical settings between the sensors and applications. The main contributions of the current article are listed as follows:  
* It presents a middleware model for healthcare 4.0 with automatic QoS support for real-time data transmission;
* It defines a QoS strategy based on artificial neurons to choose which QoS services to deliver for each middleware component;  
Figure 1: Real-time data acquisition, analysis, and feedback in healthcare.