An analysis of the dynamic characteristics of pull-in for parallel-plate and torsional electrostatic actuators is presented. Traditionally, the analysis for pull-in has been done using quasi-static assumptions. However, it was recently shown experimentally that a step input can cause a decrease in the voltage required for pull-in to occur. We propose an energy-based solution for the step voltage required for pull-in that predicts the experimentally observed decrease in the pull-in voltage. We then use similar energy techniques to explore pull-in due to an actuation signal that is modulated depending on the sign of the velocity of the plate (i.e., modulated at the instantaneous mechanical resonant frequency). For this type of actuation signal, significant reductions in the pull-in voltage can theoretically be achieved without changing the stiffness of the structure. This analysis is significant to both parallel-plate and torsional electrostatic microelectromechanical systems (MEMS) switching structures where a reduced operating voltage without sacrificing stiffness is desired, as well as electrostatic MEMS oscillators where pull-in due to dynamic effects needs to be avoided.

Dynamic pull-in of parallel plate and torsional electrostatic MEMS actuators.

The Internet of Things (IoT), as a pervasive paradigm, is becoming an integral part of the tech industry and academic research in recent years. It forms a ubiquitous heterogeneous network connecting humans and things. The basic premise is acquiring data from the environment with sensors and remote intelligent management via actuators. For IoT service providers, time and place are functional parameters. Whereas most IoT scenarios are in indoor spaces and GPS cannot fully cover them, applying an indoor positioning system (IPS) is necessary. Besides, indoor enabling technologies can leverage the capability of IoT in context-aware services. In this article, we aim to provide a panoramic view of IPSs and localization services with the centrality of IoT. First, we explain the main concepts and review the latest positioning methods, techniques, and technologies with IoT remarks. Then, we discuss technical implementation challenges and open issues with feasible solutions. Finally, we mentioned location-based services (LBSs), real IoT applications, and active vendors in the realm of positioning services. This article provides a real insight into LBSs in IoT for future research.

A Survey on Indoor Positioning Systems for IoT-Based Applications

To solve object detection issues in infrared images, such as a low recognition rate and a high false alarm rate caused by long distances, weak energy, and low resolution, we propose a region-free object detector named YOLO-FIR for infrared (IR) images with YOLOv5 core by compressing channels, optimizing parameters, etc. An improved infrared image object detection network, YOLO-FIRI, is further developed. Specifically, while designing the feature extraction network, the cross-stage-partial-connections (CSP) module in the shallow layer is expanded and iterated to maximize the use of shallow features. In addition, an improved attention module is introduced in residual blocks to focus on objects and suppress background. Moreover, multiscale detection is added to improve small object detection accuracy. Experimental results on the KAIST and FLIR datasets show that YOLO-FIRI demonstrates a qualitative improvement compared with the state-of-the-art detectors. Compared with YOLOv4, the mean average precision (mAP50) of YOLO-FIRI is increased by 21% on the KAIST dataset, the speed is reduced by 62%, the parameters are decreased by 89%, the weight size is reduced by more than 94%, and the computational costs are reduced by 84%. Compared with YOLO-FIR, YOLO-FIRI has an approximately 5% to 20% improvement in AP, AR (average recall), mAP50, F1, and mAP50:75. Furthermore, due to the shortcomings of high noise and weak features, image fusion can be applied to image preprocessing as a data enhancement method by fusing visible and infrared images based on a convolutional neural network.

YOLO-FIRI: Improved YOLOv5 for Infrared Image Object Detection

The Internet of Bodies (IoB) is an imminent extension to the vast Internet of things domain, where interconnected devices (e.g., worn, implanted, embedded, swallowed, etc.) located in-on-and-around the human body form a network. Thus, the IoB can enable a myriad of services and applications for a wide range of sectors, including medicine, safety, security, wellness, entertainment, to name but a few. Especially considering the recent health and economic crisis caused by novel coronavirus pandemic, a.k.a. COVID-19, the IoB can revolutionize today's public health and safety infrastructure. Nonetheless, reaping the full benefit of IoB is still subject to addressing related risks, concerns, and challenges. Hence, this survey first outlines the IoB requirements and related communication and networking standards. Considering the lossy and heterogeneous dielectric properties of the human body, one of the major technical challenges is characterizing the behavior of the communication links in-on-and-around the human body. Therefore, this paper presents a systematic survey of channel modeling issues for various link types of human body communication (HBC) channels below 100 MHz, the narrowband (NB) channels between 400 MHz and 2.5 GHz, and ultra-wideband (UWB) channels from 3 to 10 GHz. After explaining bio-electromagnetics attributes of the human body, physical and numerical body phantoms are presented along with electromagnetic propagation tool models. Then, the first-order (i.e., path loss, shadowing, multipath fading) and the second-order (i.e., delay spread, power delay profile, average fade duration, level crossing rate, etc.) channel statistics for NB and UWB channels are covered with a special emphasis on body posture, mobility, and antenna effects. For the HBC channels, three different coupling methods are considered: capacitive, galvanic, and magnetic. Based on these coupling methods, four different channel modeling methods (i.e., analytical, numerical, circuit, and empirical) are investigated, and electrode effects are discussed. Lastly, interested readers are provided with open research challenges and potential future research directions.

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The Internet of Bodies: A Systematic Survey on Propagation Characterization and Channel Modeling

Flexible electronics are compatible with film substrates that are soft and stretchable, resulting in conformal integration with human body. Integrated with various sensors and communication ICs, wearable flexible electronics are able to effectively track human vital signs without affecting the body activities. Such a wearable flexible system contains a sensor, a front-end amplifier (FEA), an analog-to-digital converter (ADC), a micro-controller unit (MCU), a radio, a power management unit (PMU), where the radio is the design bottleneck due to its high power consumption. Different from conventional wireless communications, body channel communication (BCC) uses the human body surface as the signal transmission medium resulting in less signal loss and low power consumption. However, there are some design challenges in BCC, including body channel model, backward loss, variable contact impedance, stringent spectral mask, crystalless design, body antenna effect, etc. In this paper, we conduct a survey on BCC transceiver, and analyze its potential role and challenges in wearable flexible electronics.

The Role and Challenges of Body Channel Communication in Wearable Flexible Electronics

Detecting objects such as pedestrians and cars plays an indispensable role in autonomous driving. To be robust to the low-illumination situation such as nighttime, thermal cameras have become increasingly popular in autonomous driving system, and it is highly desirable to develop an accurate, robust algorithm concentrated on object detection in thermal imagery. In this work, we propose an DNN-based, one-stage detector namely ThermalDet. The main idea of ThermalDet is that since there doesn’t exist lots of detailed visual characteristics (e.g. color and texture) in thermal images, features from low levels and high levels are equally important when performing detection task on them. The proposed detector inherits the architecture of RefineDet and further improves it. First, we design a dual-pass fusion block(DFB) to directly fuse features from all different levels. Then we add a channel-wise enhance module(CEM) to adaptively assign weights to different channels of the feature maps to achieve the best use of them. Experimental results on FLIR ADAS Dataset demonstrate that ThermalDet performs better than the state-of-art methods such as MMTOD-UNIT, MMTOD-CG.

Every Feature Counts: An Improved One-Stage Detector in Thermal Imagery

Temperature fluctuations seriously damage the performance of resonant accelerometers. Two approaches have been proposed in this paper to address this problem. In structural design, an electrostatic softening spring is utilized to modulate the external acceleration on the frequency of resonator’s anti-phase modal without any stress transmission and thus improve the thermal robustness of the accelerometer. In control circuit, a continuous ring-down technique is employed for real-time quality factor (utilized as a virtual thermometer) monitoring, which attenuates measuring hysteresis and improves the precision of temperature compensation. A prototype is implemented to verify the proposed approaches. Experiments show that this accelerometer is insensitive to stress and has better performance of temperature compared with the vibration beam resonant accelerometer. The bias stability of acceleration output was improved from 35.2 to 0.08 mg with real-time quality factor compensation ranging from −40 °C to +40 °C.

A MEMS Resonant Accelerometer With High Performance of Temperature Based on Electrostatic Spring Softening and Continuous Ring-Down Technique

The two dimensional micromirror works as a resonant actuator applied in light detection and ranging (LiDAR) devices. A deep embedded coils design was applied here to provide a large micromirror driving force. The paper describes the advantages of the structures through modal and harmonic response analysis. The fabrication process and the parameters for the fabrication of the structure are also mentioned. For the fabrication, deep etching was performed to produce the coil trenches. Electroplating was conducted subsequently and due to different growth speeds, oxide deposited at low-temperature worked as a sacrificial layer for the isolation of adjacent coils after treatment with BOE solutions (HF and NH4F solutions). Metal bridge above the oxide layer are used to form the current loop with the coils. The paper also discusses the stress issues in the fabrication processes which are caused by the different thermal expansion coefficients. The regionalized deposition of both metal and lift-off processes were taken to partially reduce the stress due to metal deposition. The SEM images of the micromirror after fabrication processes are illustrated in the paper. The open-loop sinusoidal signals generated by the signal generator verified that the 3 mm micromirror could be driven with a 5 V voltage. The horizontal and vertical swing angles are ±23.6 and ±5.7 ° respectively.

The fabrication of 2D micromirror with large electromagnetic driving forces

High-precision and low-cost wireless 16-channel measurement system for multi-layer thin film characterization

This paper presents a UWB-based(Ultra Wideband, UWB) indoor location ranging scheme and a method for improving accuracy through error compensation. UWB is widely used in high-precision indoor positioning because of its strong anti-interference performance, high transmission rate, wide bandwidth, low power consumption, and low transmission power. An inverse star location model was established based on the principle of spatial 4-point location. This scheme adopts STM32 to control the DW1000 to realize the UWB signal transceiving on the hardware. The software algorithm uses the TOF(Time of Flight, TOF) principle combined with the spatial 4-point positioning method to determine the position of the target point, uses the error compensation method to correct the data, and improves the accuracy of distance measurement positioning. Finally, the accuracy of the system was tested and corrected by experiments, and the effectiveness of the error compensation method in improving the system accuracy was verified.

Tong Zhou

Papers

Every Feature Counts: An Improved One-Stage Detector in Thermal Imagery

A MEMS Resonant Accelerometer With High Performance of Temperature Based on Electrostatic Spring Softening and Continuous Ring-Down Technique

The fabrication of 2D micromirror with large electromagnetic driving forces

High-precision and low-cost wireless 16-channel measurement system for multi-layer thin film characterization

Research on UWB-Based Indoor Ranging Positioning Technolog and a Method to Improve Accuracy