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Advances in CMOS-MEMS Devices and Sensors
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Advances in CMOS-MEMS Devices and Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 2751

Special Issue Editor

Prof. Dr. Chih-Cheng Lu

E-Mail Website
Guest Editor
Department of Intelligent Automation Engineering, National Taipei University of Technology, Taipei 10608, Taiwan
Interests: MEMS; CMOS-MEMS smart sensors; bio-medical and magnetic sensors; bio-mechatronics; IOTs; artificial intelligence in engineering; medical applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To date, the application diversity of sensors is not only a rapidly growing demand and phenomenon, but also an emerging business market in terms of the Smart Internet of Things (IoT) and wearable devices. In addition to traditional development, advancements in CMOS-MEMS sensors or microsystems have been continuing to contribute toward all aspects of industrial activities and human life around the world, and thus evolving into more fascinating themes of technological innovation.

The Special Issue aims to invite original and innovative topics describing the latest research in macro-scale, meso-scale, or micro-scale sensors or devices. For CMOS-MEMS microsensors, they may include novel methodologies or process integrations in all technology disciplines, even nanomaterial deposition for sensing and packaging requirements. These smart sensors with effective designs of transducing circuits do play a crucial role in a variety of next-generation applications such as pattern recognition, edge computing, big data analysis and AI deep learning, etc. Potential topics may include, but are not limited to, the following:

  • “From macro to nano” sensors: design, fabrication, packaging and reliability
  • CMOS-MEMS/NEMS sensors in specific or multi-disciplines
  • Sensor testing, interface, correction and calibration techniques
  • Smart sensors or sensory systems
  • Transducing circuits for sensor modulation/demodulation
  • Sensors for Internet of Things (IoT) and artificial intelligence (AI)

Prof. Dr. Chih-Cheng Lu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • CMOS
  • MEMS
  • NEMS
  • CMOS integration
  • methodology
  • smart sensors
  • fabrication
  • testing
  • calibration
  • transducing circuits
  • automation
  • healthcare

Published Papers (3 papers)

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Research

15 pages, 5909 KiB  
Article
An Unmanned Aerial Vehicle Indoor Low-Computation Navigation Method Based on Vision and Deep Learning
by Tzu-Ling Hsieh, Zih-Syuan Jhan, Nai-Jui Yeh, Chang-Yu Chen and Cheng-Ta Chuang
Sensors 2024, 24(1), 190; https://doi.org/10.3390/s24010190 - 28 Dec 2023
Cited by 1 | Viewed by 762
Abstract
Recently, unmanned aerial vehicles (UAVs) have found extensive indoor applications. In numerous indoor UAV scenarios, navigation paths remain consistent. While many indoor positioning methods offer excellent precision, they often demand significant costs and computational resources. Furthermore, such high functionality can be superfluous for [...] Read more.
Recently, unmanned aerial vehicles (UAVs) have found extensive indoor applications. In numerous indoor UAV scenarios, navigation paths remain consistent. While many indoor positioning methods offer excellent precision, they often demand significant costs and computational resources. Furthermore, such high functionality can be superfluous for these applications. To address this issue, we present a cost-effective, computationally efficient solution for path following and obstacle avoidance. The UAV employs a down-looking camera for path following and a front-looking camera for obstacle avoidance. This paper refines the carrot casing algorithm for line tracking and introduces our novel line-fitting path-following algorithm (LFPF). Both algorithms competently manage indoor path-following tasks within a constrained field of view. However, the LFPF is superior at adapting to light variations and maintaining a consistent flight speed, maintaining its error margin within ±40 cm in real flight scenarios. For obstacle avoidance, we utilize depth images and YOLOv4-tiny to detect obstacles, subsequently implementing suitable avoidance strategies based on the type and proximity of these obstacles. Real-world tests indicated minimal computational demands, enabling the Nvidia Jetson Nano, an entry-level computing platform, to operate at 23 FPS. Full article
(This article belongs to the Special Issue Advances in CMOS-MEMS Devices and Sensors)
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24 pages, 12319 KiB  
Article
Design and Verification of a New Universal Active Filter Based on the Current Feedback Operational Amplifier and Commercial AD844 Integrated Circuit
by Hua-Pin Chen, I-Chyn Wey, Liang-Yen Chen, Cheng-Yueh Wu and San-Fu Wang
Sensors 2023, 23(19), 8258; https://doi.org/10.3390/s23198258 - 05 Oct 2023
Cited by 1 | Viewed by 902
Abstract
This paper presents a triple-input and four-output type voltage-mode universal active filter based on three current-feedback operational amplifiers (CFOAs). The filter employs three CFOAs, two grounded capacitors, and six resistors. The filter structure has three high-input and three low-output impedances that simultaneously provide [...] Read more.
This paper presents a triple-input and four-output type voltage-mode universal active filter based on three current-feedback operational amplifiers (CFOAs). The filter employs three CFOAs, two grounded capacitors, and six resistors. The filter structure has three high-input and three low-output impedances that simultaneously provide band-reject, high-pass, low-pass, and band-pass filtering functions with single-input and four-output type and also implements an all-pass filtering function by connecting three input signals to one input without the use of voltage inverters or switches. The same circuit configuration enables two unique filtering functions: low-pass notch and high-pass notch. Three CFOAs with three high-input and low-output impedance terminals enable cascading without voltage buffers. The circuit is implemented using three commercial off-the-shelf AD844 integrated circuits, two grounded capacitors, and six resistors and further implemented as a CFOA-based chip using three CFOAs, two grounded capacitors, and six resistors. The CFOA-based chip has lower power consumption and higher integration than the AD844-based filter. The circuit was simulated using OrCAD PSpice to verify the AD844-based filter and Synopsys HSpice for post-layout simulation of the CFOA-based chip. The theoretical analysis is validated and confirmed by measurements on an AD844-based filter and a CFOA-based chip. Full article
(This article belongs to the Special Issue Advances in CMOS-MEMS Devices and Sensors)
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11 pages, 6555 KiB  
Article
Investigation on the Effective Measures for Improving the Performance of Calorimetric Microflow Sensor
by Jiali Qi, Chun Shao, Wei Wu and Ruijin Wang
Sensors 2023, 23(17), 7413; https://doi.org/10.3390/s23177413 - 25 Aug 2023
Viewed by 730
Abstract
The performance of the calorimetric microflow sensor is closely related to the thermal sensing part design, including structure parameter, heater temperature, and operation environment. In this paper, several measures to enhance the performance of the calorimetric microflow sensor were proposed and further verified [...] Read more.
The performance of the calorimetric microflow sensor is closely related to the thermal sensing part design, including structure parameter, heater temperature, and operation environment. In this paper, several measures to enhance the performance of the calorimetric microflow sensor were proposed and further verified by numerical simulations. The results demonstrate that it is more favorable to reduce the negative impact of flow separation as the space between detectors and heater is set to be 1.6 μm so as to improve the accuracy of the sensor. With an appropriate gap, the front arranged obstacle of the upstream detector can effectively widen the measure range of the sensor, benefiting from the decrease in upstream viscous dissipation. Compared to a cantilever structure, the resonances can be effectively suppressed when the heater and detectors are designed as bridge structures. In particular, the maximum amplitude of the bridge structure is only 0.022 μm at 70 sccm, which is 53% lower than that of the cantilever structure. The optimized sensor widens the range by 14.3% and significantly increases the sensitivity at high flow rates. Moreover, the feasibility of the improved measures is also illustrated via the consistency of the trend between the simulation results and experimental ones. Full article
(This article belongs to the Special Issue Advances in CMOS-MEMS Devices and Sensors)
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