Users often need to control and monitor the environmental variables of their homes, even when they are not at home. In this paper, we present a multifunctional, low-cost, and flexible system for smart home control and environmental monitoring. This system employs an embedded micro web server based on an Arduino Yún microcontroller with Internet connectivity that allows remote device control. The proposed system can be controlled via the Internet through an Android-based mobile app. To guarantee access regardless of Internet availability, the proposed system can also be controlled via standalone manual operation using a touch display. The proposed system transmits sensor data to a cloud platform and can receive commands from the server, allowing many devices to be automatically controlled. To demonstrate the feasibility and effectiveness of this system, devices such as light switches, power plugs, and various sensors, including temperature, gas, 2.5- $\mu \text{m}$ particulate matter (PM2.5) and motion sensors, were integrated into a prototype of the proposed home control system. Finally, we implemented the prototype in a model home to validate the flexibility, scalability, usability and reliability of the system.

We present a wearable device built on an Adafruit Circuit Playground Express (CPE) board and integrated with a photoplethysmographic (PPG) optical sensor for heart rate monitoring and multiple embedded sensors for medical applications—in particular, sleep physiological signal monitoring. Our device is portable and lightweight. Due to the microcontroller unit (MCU)-based architecture of the proposed device, it is scalable and flexible. Thus, with the addition of different plug-and-play sensors, it can be used in many applications in different fields. The innovation introduced in this study is that with additional sensors, we can determine whether there are intermediary variables that can be modified to improve our sleep monitoring algorithm. Additionally, although the proposed device has a relatively low cost, it achieves substantially improved performance compared to the commercially available Philips ActiWatch2 wearable device, which has been approved by the Food and Drug Administration (FDA). To assess the reliability of our device, we compared physiological sleep signals recorded simultaneously from volunteers using both our device and ActiWatch2. Motion and light detection data from our device were shown to be correlated to data simultaneously collected using the ActiWatch2, with correlation coefficients of 0.78 and 0.89, respectively. For 7 days of continuous data collection, there was only one instance of a false positive, in which our device detected a sleep interval, while the ActiWatch2 did not. The most important aspect of our research is the use of an open architecture. At the hardware level, general purpose input/output (GPIO), serial peripheral interface (SPI), integrated circuit (I²C), and universal asynchronous receiver-transmitter (UART) standards were used. At the software level, an object-oriented programming methodology was used to develop the system. Because the use of plug-and-play sensors is associated with the risk of adverse outcomes, such as system instability, this study heavily relied on object-oriented programming. Object-oriented programming improves system stability when hardware components are replaced or upgraded, allowing us to change the original system components at a low cost. Therefore, our device is easily scalable and has low commercialization costs. The proposed wearable device can facilitate the long-term tracking of physiological signals in sleep monitoring and related research. The open architecture of our device facilitates collaboration and allows other researchers to adapt our device for use in their own research, which is the main characteristic and contribution of this study.

Electrocardiograms (ECGs) provide important information for diagnosing cardiovascular diseases. In clinical practice, the conventional Ag/AgCl electrode is generally used; however, it is not suitable for long-term ECG measurement because of the risk of allergic reactions on the skin and the dying issue of electrolytic gels. In previous studies, several dry electrodes have been proposed to address these issues. However, most dry electrodes, which are the mode of conductive materials, have to contact the skin well and are easily affected by motion artifacts in daily life. In the smart clothes developed in this study, a noncontact electrode was used to assess the biopotential across the clothes to prevent skin irritation and discomfort. Moreover, a three-dimensional parametric model based on anthropometric data was built, and the technique of customized product design was introduced into the smart clothes development process to reduce the influence of motion artifacts. The experimental results show that the proposed smart clothes can maintain a good ECG signal quality stably under motion from different activities.

Assistive devices are one of the crucial medical instruments for rehabilitation. Customized designs are required to match the geometry and dimensions of the affected sites of human bodies. The existing practice of assistive device development remains mostly a manual process, in which an experienced physiotherapist employs simple two-dimensional measurements and visual estimation to handcraft each device. The resulting devices not only vary substantially in fit to wearers, but also are not compatible to modern developmental technologies such as three-dimensional (3D) printing. This study incorporated substantial quantities of anthropometric data to construct a parametric 3D hand model. This study employed a customized assistive device - splint for carpal tunnel syndrome as a target object for testing the feasibility of the proposed method and verified the practicability through 3D printing implementation. Moreover, a wearable device embedded with inertial measurement unit sensor and vibration module will be integrated into the customized assistive device to offer a smart way for rehabilitation. With the help of this developed wearable device, continuously tracking user’s activity wirelessly and provide the real-time physically intervention feedback of vibration module based on back-end monitoring system platform. This new concept by integrating customized design and the IMU sensor and vibration module open a new window for the field of customized assistive device and improve its practical values.

In this research, we propose a Prognostics and Health Management (PHM) system that integrates an energy monitoring framework to enhance the efficiency of maintenance strategy of aerospace autoclaves, which are usually subjected to expensive and complicated inspection processes. It provides real-time health indicators, predicts the condition of equipment, and performs energy audits. A health evaluation logic was built upon the current balance through the analysis of the three-phase current fluctuation amount of heater units and circulation fan motors. Using a main-sub health assessment structure, the PHM system processes data from individual equipment units, identifies anomalies, and notifies maintenance personnel to carry out corrective actions. It uses complex AI techniques such as RNN, GRU, LSTM, etc., for trend prediction of health for proactive maintenance. It also accounts for energy consumption and carbon emissions per batch of production, thereby contributing to sustainability in the aerospace industry. Ultimately, this implementation makes autoclaves more reliable, longer-lasting, and more efficient, while minimizing maintenance costs, as well as energy consumption and carbon emissions. The end-to-end solution offers a powerful means of enhancing autoclave performance, and of enabling green aerospace operations.