## 1 Introduction
The applications of WBANs are diverse, and range from e-health and ambient assisted living to mobile health and sports training. Wireless sensor networks provide a communication framework that enables the sensing, gathering and forwarding of data to a central destination for further data analysis and decision making [10]. One of the main concerns in these networks is to guarantee their energy efficiency for as long as possible. This collection of sensors can be linked with the Internet of Things to provide innovative applications for scientific research purposes. In order to develop our smart system, we combine many fields of computer science such as wireless sensor networks, classification techniques and probabilistic approaches. The proposed architecture consists of a smart connected system for ubiquitous healthcare applications. The aim is to use WBAN devices as a real-time medical data source and to provide an autonomous intelligent system that is capable of monitoring patients in a medical setting. Table 1 summarizes the nomenclature and the technical specificities of the main used sensors in a single or multiple-WBAN environment. It is important to note that this research work focuses on the BP-related sensor. The other sensors such as ECG, EMG and EEG are shown for information purposes only. In this  
Figure 1: Wireless body area network (WBAN) architecture for e-health applications illustrating the existing types of communication. paper, we examine only on-body area networks; blood pressure sensors belong to this group, since these devices are attached to a patient. Currently, one of the top challenges that every country is facing is healthcare [11]. Numerous ubiquitous healthcare structures are outlined here and various different perspectives are taken into consideration, such as the reliability of the vital patient information to be transmitted, and the lifetime and monitoring of battery utilization based on optimized routing protocols [12]. There is a rapidly growing body of literature on ubiquitous healthcare systems, which highlights its value and contains many examples of research in this field. The objective is to propose a healthcare solution that is capable of monitoring a patient's vital signs and notifying physicians and/or technicians wirelessly when these metrics exceed certain limits. In this section, we give a brief overview of the state-of-the-art of ubiquitous systems and several examples that are related to our work. In [13; 14; 15], a ubiquitous healthcare system consisting of physiological data-gathering devices using medical sensors offers monitoring and managing solutions for a patient's health condition. Several works propose interesting solutions applied to e-health and ubiquitous systems; for example, [PERSON] et al. [16] used EEG sensors in order to classify stress status based on brain signals, while [PERSON] et al. [17] designed a mobile healthcare application based on an image representation of the tongue, a vital muscular organ. A summary of the energy requirements of a WBAN-based real-time healthcare monitoring architecture can be found in [PERSON] et al. [18]. [PERSON] et al. [19] implemented a multi-agent system based mobile medical service using the framework for modeling and simulation of cloud computing infrastructures and services (CloudSim). [PERSON] et al. [20] created a software system that improved the maintenance management of medical technology by sorting medical maintenance requests. [PERSON] and [PERSON] [21] presented a data management system (DMS) architecture, an agent-based middleware that utilizes both hardware/software resources within a pervasive environment and provides data quality management. [PERSON] et al. [22] proposed a management system for diabetes patients based on generated rules and a K-nearest neighbors (KNN) classification technique. [PERSON] et al. [23] developed a healthcare system for diabetes patients that makes it easier to obtain a rapid diagnosis.