ecoSync: An Energy-Efficient Clock Discipline Data Synchronization in Wi-Fi IoMT Systems

Abstract

The growth of the Internet of Medical Things (IoMT) and healthcare data analytics allows wearable Wireless Body Area Networks (WBANs) and ambient sensors to collect the large quantities of physiological signals necessary for better patient diagnostics and treatments. Artificial intelligence and machine learning algorithms frequently require precisely synchronized signals from multiple sensors, which in turn require time-consuming and energy-inefficient synchronization methods with constant wireless network connectivity. We propose ecoSync, a highly energy-efficient time synchronization algorithm for Wi-Fi devices in IoMT applications. We demonstrated that ecoSync can correct the time difference error to ±42 µs with an hour between resynchronizations, using only 658 millijoules of energy. This is an 87% improvement in time difference error and a 99.93% reduction in energy usage over using TSF for synchronization alone over a 1 h period. Wireless synchronization of sensors allows placement of physiological sensors on objects of everyday use (Smart Stuff), which in turn allows seamless collection of physiological status data every time we interact with smart objects in an IoMT environment.

Development of an artificial intelligence based occupational noise induced hearing loss early warning system for mine workers

“…The smart watch applies IoT and can communicate with the hearing protection via Bluetooth technology. Several authors have made use of the ESP-32 as the basis for their smart-watch design ( Volsa et al, 2022 ; Himi et al, 2023 ; Joseph, 2023 ; Puckett and Emil, 2023 ). The smart hearing protection can monitor real time noise levels using the sensors installed on it and cloud technology.…”

Synchronization of Separate Sensors’ Data Transferred through a Local Wi-Fi Network: A Use Case of Human-Gait Monitoring

“…These methodologies encompass diverse approaches, such as harnessing GPS modules, utilizing pulse-per-second (PPS) signals, and employing synchronization protocols that focus on estimating nondeterministic delays to achieve accurate time measurements [1,2], the sensorimotor synchronization method [3], or the Sync-ESP-NOW protocol and other specialized protocols, such as NTP and PTP, for IoT devices [4,5]. Furthermore, investigations into synchronization have extended to Bluetooth-based sensor networks [6] and time measurement in medical devices [7]. An extension of reference-broadcast infrastructure synchronization (RBIS) with wide coverage of multiple access points and a significantly improved timing accuracy superior to NTP was implemented in research presented in [8].…”