This review offers a critical overview of recent developments in lead-free piezoelectric materials and flexible device architectures for self-powered wearable and Internet of Things systems. It examines the scientific and technological rationale for replacing conventional battery-dependent power sources with ambient mechanical energy harvesters, and it evaluates the relative merits of inorganic ceramics, organic polymers, and composite systems in achieving efficient electromechanical conversion under practical operating conditions. The discussion further considers compositional tuning, phase boundary engineering, microstructural optimization, and device-level integration as key strategies for improving piezoelectric output, mechanical compliance, durability, and manufacturability. By connecting fundamental materials design with application-driven device requirements, the review identifies the principal challenges and emerging directions necessary for the realization of reliable, scalable, and sustainable electronic platforms.

Lighting has been used for a long time as a medium to convey brightness from darkness, and through incandescent lamps and fluorescent lamps, LED light sources have now become the standard in the lighting industry. Recently, the lighting equipment industry has been undergoing rapid digital transformation, starting with smart lighting, and is evolving into smart lighting customized for individuals and spaces through the development of IoT technology, cloud-based services, and data analysis. However, the blue light emitted from digital devices (computers, smartphones, tablets, etc.) or LED lights stimulates the melanopsin in the optic ganglion cells in the retina of the eye, which in turn stimulates the secretion of melatonin through the pineal gland, which regulates the secretion of melatonin. This can reduce sleep quality or disrupt biological rhythms. This interaction between blue light and melatonin has such a significant impact on human sleep patterns and overall health that it is essential to reduce exposure to blue light, especially in the evening. Human-centered lighting refers to lighting that takes into account the effects of light on the physical and mental areas, such as human activity and awakening, improvement of sleep quality, and health management. Many research institutes study the effects in the visible area and the non-visible area. By studying the impact, it is expected to improve the quality of human life. In this study, we plan to study ways to implement humancentered lighting by collecting sunrise and sunset data and linking commercialized LED packages and control devices with opensource hardware.

The Internet of Things (IoT) device is a key component for Industry 4.0, which is the network in homes, factories, buildings, and infrastructures to monitor and control the systems. To demonstrate the IoT network, batteries are widely utilized as power sources, and the batteries inevitably require repeated replacement due to their limited capacity. Magneto-mechanoelectric (MME) generators are one of the candidate to develop self-powered IoT systems since MME generators can harvest electricity from stray alternating current (AC) magnetic fields arising from electric power cables. Herein, we report a magnetomechano- triboelectric generator enabled by a ferromagnetic-ferroelectric composite. In the triboelectric nylon matrix, a ferromagnetic carbonyl iron powder (CIP) was introduced to induce magnetic force near the AC magnetic field for MME harvesting. Additionally, a ferroelectric ceramic powder was also added to the MME composite material to enhance the chargetrapping capability during triboelectric harvesting. The final ferromagnetic-ferroelectric composite-based MME triboelectric harvester can generate an open-circuit voltage and a short-circuit current of 110 V and 8 μA, respectively, which were enough to turn on a light emitting diode (LED) and charge a capacitor. These results verify the feasibility of the MME triboelectric generator for not only harvesting electricity from an AC magnetic field but also for various self-powered IoT applications.

Energy harvesting technologies that can convert wasted various energy into usable electrical energy have been widely investigated to overcome the limitation of batteries for the powering of IoT sensors and small electronic devices. Hybrid energy harvesting is known as a technology that enhances the output power of single energy harvesting device by housing two or more various energy harvesting mechanisms. In this study, we introduce a hybrid MME (Magneto-Mechano-Electric) generator coupled with the triboelectric effect. Through FEA modeling, four triboelectric materials, including PI (Polyimide), PFA(Teflon), Cu, and Al, were selected and compared with the expected triboelectric potentials. The effect of surface morphology was investigated as well. Among various combination of triboelectric materials and surface morphologies, PFA-Al combination with the surface morphology having nano-scale square projections showed highest output potential under triboelectrification. It is also experimentally confirmed that output voltage and power of the hybrid MME generator with triboelectric material combinations.

This paper reports a method to use a wireless sensor network deployed in the field to real-time monitor soil moisture, warning when the moisture level reaches a specific value, and wirelessly controlling an additional device (LED or water supply system, etc.). In addition, we report all processes related to wireless irrigation system, including field deployment of sensors, real-time monitoring using a smartphone, data calibration, and control of additional devices deployed in the field by smartphone. A commercially available open-source Internet of Things (IoT) platform, NodeMCU, was used, which was combined with a 9V battery, LED and soil humidity sensor to be integrated into a portable prototype. The IoT-based soil humidity sensor prototype deployed in the field was installed next to a tree for on-site demonstration for the measurement of soil humidity in real-time for about 30 hours, and the measured data was successfully transmitted to a smartphone via Wifi. The measurement data were automatically transmitted via e-mail in the form of a text file, stored on the web, followed by analyses and calibrations. The user can check the humidity of the soil real-time through a personal smartphone. When the humidity of a soil reached a specific value, an additional device, an LED device, placed in the field was successfully controlled through the smartphone. This LED can be easily replaced by other electronic devices such as water supplies, which can also be controlled by smartphones. These results show that farmers can not only monitor the condition of the field real-time through a sensor monitoring system manufactured simply at a low cost but also control additional devices such as irrigation facilities from a distance, thereby reducing unnecessary energy consumption and helping improve agricultural productivity.

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

There are many difficulties in the applications of smart manufacturing technology in the era of the 4th industrial revolution. In this paper, a test bed was built to aim for acquiring smart manufacturing technology, and the test bed was designed to acquire basic technologies necessary for PLC (Programmable Logic Controller), HMI, Internet of Things (IoT), artificial intelligence (AI) and big data. By building a vehicle maintenance lift that can be easily accessed by the general public, PLC control technology and HMI drawing technology can be acquired, and by using cloud services, workers can respond to emergencies and alarms regardless of time and space. In addition, by managing and monitoring data for smart manufacturing, it is possible to acquire basic technologies necessary for embedded systems, the Internet of Things, artificial intelligence, and big data. It is expected that the improvement of smart manufacturing technology capability according to the results of this study will contribute to the effect of creating added value according to the applications of smart manufacturing technology in the future.

Vocational education needs to be transformed to cultivate talents with diverse fusion competencies, which is in line with the recent changes that have become a part of the complex technological developments in the 4th Industrial Revolution. Therefore, it is very important for college graduates to obtain employment skills as they are required to prepare for careers within the complex environments of future societies. With the transition to the Internet of Things (IoT)-based control in the manufacturing industry, the development of technological education and related training programs is required to cultivate practical talents for students who have acquired not only the information on existing programmable logic controller (PLC)-based technology, but also that on embedded programming technology. Therefore, to develop an NCS-based education program for analog signal processing to ensure that programming can easily be learned for cultivating practical talent, this study summarizes the opinions of field experts, selects the appropriate NCS competency unit, and designs an adequate technology education training program.

The advancement and diversification of urban functions has caused an increasing need to improve the reliability of power supplies. The diversification of urban areas causes social disruptions by paralyzing urban functions during power outages. A large power outage occurs in the event of an accident, owing to the subduction of distribution lines. Therefore, in recent years, for the sake of the environment and safety, the safety diagnosis of electric power facilities has become an important issue. In this system, because thermal information changes rapidly during unattended monitoring owing to heat concentration phenomenon due to abnormal load or deterioration, studies have been conducted on the development of a device that can notify the manager at all times.