# Rebirth of Distributed AI--A Review of eHealth Research
## 4 Categories of eHealth Applications
### Category I--IoMT-Based Health Applications  
The Covid-19 pandemic is yet another motivation for discerning the direction in which future health applications should go. Specifically, the future health applications should be designed to improve quality of life and to serve the mass of patients remotely and with minimal interventions by humans. IoMT-based systems are the embodiment of such solutions. They leverage the advancement in wireless communication, big-data analytic, and sensing technologies to make personalized healthcare services available for everybody, anytime and anywhere.  
An IoMT application consists mainly of four parts, as depicted in Figure 5: a device layer, a communication layer, data layers, and users. These parts reside in a classic layered architecture, i.e., sensors reside on the device layer, which makes use of the communication bit-pipes (base station) of the communication layer to connect to the data layer (data center) and cloud resources. Ref. [34] goes into detail in describing IoMT, especially its key component--Wireless Body Area Network (WBAN). A WBAN connects the wearable sensors with the user's mobile phone, which serves as an edge device and where some basic processing occurs. The WBAN typically expands over the whole human body and the nodes are connected via short-range wireless communications. Among different short-range communications, infrared, Wi-Fi, Ultra-wideband (UWB), ZigBee, and Infrared Data Association (IrDA), Bluetooth is currently the most suitable standard for implementation into wearable healthcare systems. Bluetooth is characterized by its low latency of 3 ms, its high data rate of 1 Mbps, its robustness against interference and noise, and its security [34].  
Figure 4: E-Health application categories.  
Currently, different sensors on the market can be used with different physical indications and for different objectives, such as sensors monitoring heart rate, respiration, blood oxygen saturation, glucose, or even motion. After initial processing in the smartphone, the information gets transmitted to the cloud, where advanced processing occurs using deep learning or ML techniques. To conduct this transmission, long-range communication technology is used, namely Low Power Wide Area (LPWA) technology. LPWA emerged as a term in 2013--not as a new technology standard, but rather as a class of wireless technologies that are well suited to the specific needs of machine-to-machine (M2M) and IoT devices. The majority of IoT devices, especially those in smart city and industrial sectors, do not require the same speed and bandwidth that consumer cellular devices need. However, they do need the longevity of traditional Long-Term Evolution (LTE) cellular networks [35]. Besides the communication technology, IoMT utilizes identification technology such as RFID, QR code, or node self-identification for nodes to identify themselves prior to communication. Moreover, IoMT utilizes location technology that is very beneficial in wearable devices [36]. An endless list of applications can be developed under the umbrella of IoMT. In Section 8, we focus on examples of these applications to demonstrate the role of FL to enable them.