# Data Gathering Techniques in WSN: A Cross-Layer View
## 6 Wearables and Wireless Body Area Networks (WBAN)  
Numerous applications rely on data gathering and report collection in WSN and IoT, and some are mentioned throughout the paper. There is no doubt that the essence of WSN is the applications that utilize the infrastructure discussed throughout this paper. Providing a thorough review of such applications can encompass several surveys. Since wearables are becoming highly popular and a ubiquitous application which imposes new challenges in the context of data gathering, we discuss several recent results and related challenges in the context of wearables. Figure 5 depicts the main topics discussed in this section. Wearable technology refers to smart devices attached to the human body or apparel to monitor the user and their environment. Wearables are designed to detect, analyze, and transmit information, which allows continuous monitoring of the subject. In some cases (e.g., healthcare applications), feedback is returned to the wearer with strict performance constraints (e.g., reliability, latency bounds). Such applications can necessitate the monitoring of both bodily conditions, such as blood pressure, blood glucose level (e.g., in conjunction with an insulin pump), ECG, EMG, body temperature, accelerometer, and gyroscope, as well as environmental conditions that might influence the user, such as temperature, humidity, CO\({}_{2}\) level, dust level, and location. Sensing essential human physiological parameters led to the innovation of wireless body area networks (WBANs). WBAN typically relates to a small area network that spans the whole human body. It comprises devices (wearables) located in the apparel, on the body, or under the skin, and are wirelessly connected. Even though tracking physical conditions applies to diverse domains, including medical, social, and economic ones, each with its particular implications and extensive research in the field, the specific challenges of acquiring data in WBANs necessitated new solutions designed for WBAN. Specifically,  
Figure 5: The main topics in the context of wearables covered in the section, and a rough partition of the papers covered by these topics. since the sensors in WBANS are designed to be located close to the monitored individual, they impose particular challenges related to their specific structural, functional, and size-related constraints. In the sequel, we dwell on some of the most critical challenges and recent promising results on WBANS. The main objective of this survey is to understand the data-gathering challenges. In the special case of WBANS, we also elaborate on the sensors' physical and mechanical structure, which directly impact the data acquisition process. Many of the challenges pertaining to WSN in general, which are described throughout this survey, also apply to wearables. However, some of these challenges are exaggerated when applied to wearables due to their unique characteristics. For example, energy-related challenges that are essential to address and substantially influence any WSN design and performance, open a different perspective on wearables. Specifically, due to their sensing devices' tiny size, the energy storing capacities are limited. Yet, many wearable applications, particularly healthcare ones, employ continuous sampling and communication tasks that constantly consume energy and deplete the device's battery. Frequent battery replacement, which can be a burden in any WSN, can be even more cumbersome in wearables and can hinder the adoption of these technologies (e.g., when the wearables are implants, battery replacement can involve an invasive medical intervention). Accordingly, energy-efficient approaches designed for wearable sensor networks are important for disseminating the technology into additional domains. An inclusive review of energy-efficient approaches designed for human context recognition (HCR) based on wearable sensor networks is given by [192].