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We propose the conditions for maximum overall efficiency at the constraint of satisfying asymmetric load power requirements for each receiver, for multiple-receivers wireless power transfer. Previously, the limitation of multiple-receiver analysis was that only the efficiency was maximized, whereas the requirements of load power were neglected. In many cases, conventional efficiency maximization assigns insufficient power to receivers far from the transmitter, while supplying excessive power to receivers near the transmitter. To resolve this limitation, we maximize the efficiency at the constraints of specified load power for each receiver. The proposed closed-form equation provides an optimum TX coil current amplitude, and the optimum load resistances of each receiver, to achieve the maximum efficiency at the load power regulation.

This paper proposes a wireless power transfer (WPT) system by placing repeater coils to transfer power to multiple loads for the internet of things (IoT) devices and sensors in smart grid applications. The proposed system intermediate resonators (repeaters) not only function as power relays to enhance the transfer distance but also supplies power to its load attached to them. Equal power distribution and load-independent characteristics were obtained without efficiency degradation when any one of the loads was changed during system operation. Identical high-quality factor coils were designed using Litz-wire to reduce the skin effect. The coil size was 15.5 cm × 15.5 cm and the four relays achieved total efficiency of 51.7%, delivering 2 W power and output voltage of 5 V to each load with a total power transfer distance of 62 cm.

A dual-impedance operation, where coil impedance is controlled by operating frequency selection, is proposed to maintain optimum reflected impedance across coupling variation. More specifically, this work focuses on how high coupling between coils presents excessively high reflected resistance to transmitter (Tx) inverters, degrading the efficiency and output power of the inverter. To overcome this problem, the proposed system is equipped with dual-impedance coil and selects high- or low-impedance coil based on the ability to operate both at 200 kHz and 6.78 MHz frequencies. The reactive impedances of 6.78 MHz coils are designed to be higher than that of 200 kHz coils. Since the reflected resistance is proportional to the coil impedances and coupling squared, at close distance with high coupling coefficient, 200 kHz coils with low coil impedances are activated to prevent an excessive rise in reflected resistance. On the other hand, at large distance spacing with low coupling coefficient, 6.78 MHz coils with high coil impedances are activated so that sufficient reflected resistance is obtained even under the small coupling. The proposed system’s advantages are the high efficiency and the elimination of bulky mechanical relay switches. Measured efficiencies are 88.6–50% across 10 coupling variations.

Haptic interface technologies for virtual reality applications have been developed to increase the reality and manipulability of a virtual object by creating a diverse tactile sensation. Most evaluation of the haptic technologies, however, have been limited to the haptic perception of the tactile stimuli via static virtual objects. Noting this, we investigated the effect of lateral cutaneous feedback, along with kinesthetic feedback on the perception of virtual object weight during manipulation. We modeled the physical interaction between a participant’s finger avatars and virtual objects. The haptic stimuli were rendered with custom-built haptic feedback systems that can provide kinesthetic and lateral cutaneous feedback to the participant. We conducted two virtual object manipulation experiments, 1. a virtual object manipulation with one finger, and 2. the pull-out and lift-up of a virtual object grasped with a precision grip. The results of Experiment 1 indicate that the participants felt the virtual object rendered with lateral cutaneous feedback significantly heavier than with only kinesthetic feedback (p mref = 100 and 200 g). Similarly, the participants of Experiment 2 felt the virtual objects significantly heavier when lateral cutaneous feedback was available (p mref = 100, 200, and 300 g). Therefore, the additional lateral cutaneous feedback to the force feedback led the participants to feel the virtual object heavier than without the cutaneous feedback. The results also indicate that the contact force applied to a virtual object during manipulation can be a function of the perceived object weight (p = 0.005 for Experiment 1 and p = 0.02 for Experiment 2).

It is inevitable for data collection that IoT sensors are distributed to interested areas. However, not only the proper placement of sensors, but also the replacement of sensors that have run out of energy is very difficult. As a remedy, wireless charging systems for IoT sensors have been researched recently, but it is apparent that the availability of charging system is limited especially for IoT sensors scattered in rugged terrain. Thus, it is important that the sensor relocation models to recover sensing holes employ energy-efficient scheme. While there are various methods in the mobile model of wireless sensors, well-known wheel-based movements in rough areas are hard to achieve. Thus, research is ongoing in various areas of the hopping mobile model in which wireless sensors jump. Many past studies about hopping sensor relocation assume that all sensor nodes are aware of entire network information throughout the network. These assumptions do not fit well to the actual environment, and they are nothing but classical theoretical research. In addition, the physical environment (sand, mud, etc.) of the area in which the sensor is deployed can change from time to time. In this paper, we overcome the theoretical-based problems of the past researches and propose a new realistic hopping sensor relocation protocol considering terrain conditions. Since the status of obstacles around the sensing hole is unknown, the success rate of the hopping sensor relocation is used to predict the condition of the surrounding environment. Also, we are confident that our team is uniquely implementing OMNeT++ (Objective Modular Network Testbed in C++) simulation in the hopping sensor relocation protocol to reflect the actual communication environment. Simulations have been performed on various obstacles for performance evaluation and analysis, and we are confident that better energy efficiency with later appearance of sensing holes can be achieved compared to well-known relocation protocols.

The acquisition of physiological data are essential to efficiently predict and treat cardiac patients before a heart attack occurs and effectively expedite motor recovery after a stroke. This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring. In this paper, we present a wireless physiological signal acquisition device and a smartphone-based software platform for real-time data processing and monitor and cloud server access for everyday ECG/EMG signal monitoring. The device is implemented in a compact size (diameter: 30 mm, thickness: 4.5 mm) where the biopotential is measured and wirelessly transmitted to a smartphone or a laptop for real-time monitoring, data recording and analysis. Adaptive digital filtering is applied to eliminate any interference noise that can occur during a regular at-home environment, while minimizing the data process time. The accuracy of ECG and EMG signal coverage is assessed using Bland–Altman analysis by comparing with a reference physiological signal acquisition instrument (RHS2116 Stim/Recording System, Intan). Signal coverage of R-R peak intervals showed almost identical outcome between this proposed work and the RHS2116, showing a mean difference in heart rate of 0.15 ± 4.65 bpm and a Wilcoxon’s p value of 0.133. A 24 h continuous recording session of ECG and EMG is conducted to demonstrate the robustness and stability of the device based on extended time wearability on a daily routine.

With the growing interest in big data technology, mobile IoT devices play an essential role in data collection. Generally, IoT sensor nodes are randomly distributed to areas where data cannot be easily collected. Subsequently, when data collection is impossible (i.e., sensing holes occurrence situation) due to improper placement of sensors or energy exhaustion of sensors, the sensors should be relocated. The cluster header in the sensing hole sends requests to neighboring cluster headers for the sensors to be relocated. However, it can be possible that sensors in the specific cluster zones near the sensing hole are continuously requested to move. With this knowledge, there can be a ping-pong problem, where the cluster headers in the neighboring sensing holes repeatedly request the movement of the sensors in the counterpart sensing hole. In this paper, we first proposed the near-uniform selection and movement scheme of the sensors to be relocated. By this scheme, the energy consumption of the sensors can be equalized, and the sensing capability can be extended. Thus the network lifetime can be extended. Next, the proposed relocation protocol resolves a ping-pong problem using queues with request scheduling. Another crucial contribution of this paper is that performance was analyzed using the fully-customed OMNeT++ simulator to reflect actual environmental conditions, not under over-simplified artificial network conditions. The proposed relocation protocol demonstrates a uniform and energy-efficient movement with ping-pong free capability.

A fast time-domain finite-element algorithm is developed for the analysis and the design of very large-scale on-chip circuits. The structure specialty of on-chip circuits, such as Manhattan geometry and layered permittivity, is preserved in the proposed algorithm. As a result, the large-scale matrix solution encountered in the 3-D circuit analysis is turned into a simple scaling of the solution of a small 1-D tridiagonal matrix, which can be obtained in linear (optimal) complexity with negligible cost. Furthermore, the time step size is not sacrificed, and the total number of time steps to be simulated is also significantly reduced, thus achieving a total cost reduction in the CPU time. Applications to the simulation of very large-scale on-chip circuit structures on a single core have demonstrated the superior performance of the proposed method.

Recent advances in big data technology collecting and analyzing large amounts of valuable data have attracted a lot of attention. When the information in non-reachable areas is required, IoT wireless sensor network technologies have to be applied. Sensors fundamentally have energy limitations, and it is almost impossible to replace energy-depleted sensors that have been deployed in an inaccessible region. Therefore, moving healthy sensors into the sensing hole will recover the faulty sensor area. In rough surfaces, hopping sensors would be more appropriate than wheel-driven mobile sensors. Sensor relocation algorithms to recover sensing holes have been researched variously in the past. However, the majority of studies to date have been inadequate in reality, since they are nothing but theoretical studies which assume that all the topology in the network is known and then computes the shortest path based on the nonrealistic backing up knowledge&mdash, The topology information. In this paper, we first propose a distributed hopping sensor relocation protocol. The possibility of movement of the hopping sensor is also considered to recover sensing holes and is not limited to applying the shortest path strategy. Finally, a performance analysis using OMNeT++ has demonstrated the solidification of the excellence of the proposed protocol.