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Xu D, Zhu X, An J, Chen G, Bao J, Xu X. UV-vis-IR Broad Spectral Photodetectors Based on VO 2-ZnO Nanocrystal Films. ACS OMEGA 2022; 7:37078-37084. [PMID: 36312338 PMCID: PMC9607667 DOI: 10.1021/acsomega.2c02549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 07/25/2022] [Indexed: 06/16/2023]
Abstract
As a narrow band semiconductor at room temperature and a metallic material above ∼68 °C, functional VO2 films are widely investigated for smart windows, whereas their potential for ultraviolet-visible-infrared (UV-vis-IR) broad spectral photodetectors has not been efficiently studied. In this report, photodetectors based on VO2-ZnO nanocrystal composite films were prepared by nanocrystal-mist (NC-mist) deposition. An enhanced photodetection switching ratio was achieved covering the ultraviolet to infrared wavelength. Due to the synergetic effect of nanosize, surface, phase transition, percolation threshold, and the band structure of the heterojunction, the transfer and transport of photogenerated carriers modulate the device performance. This study probes new chances of applying VO2-semiconductor-based nanocomposites for broad spectral photodetectors.
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Abstract
Experts confirm that 85% of the world’s population is expected to live in cities by 2050. Therefore, cities should be prepared to satisfy the needs of their citizens and provide the best services. The idea of a city of the future is commonly represented by the smart city, which is a more efficient system that optimizes its resources and services, through the use of monitoring and communication technology. Thus, one of the steps towards sustainability for cities around the world is to make a transition into smart cities. Here, sensors play an important role in the system, as they gather relevant information from the city, citizens, and the corresponding communication networks that transfer the information in real-time. Although the use of these sensors is diverse, their application can be categorized in six different groups: energy, health, mobility, security, water, and waste management. Based on these groups, this review presents an analysis of different sensors that are typically used in efforts toward creating smart cities. Insights about different applications and communication systems are provided, as well as the main opportunities and challenges faced when making a transition to a smart city. Ultimately, this process is not only about smart urban infrastructure, but more importantly about how these new sensing capabilities and digitization developments improve quality of life. Smarter communities are those that socialize, adapt, and invest through transparent and inclusive community engagement in these technologies based on local and regional societal needs and values. Cyber security disruptions and privacy remain chief vulnerabilities.
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Akhter F, Khadivizand S, Siddiquei HR, Alahi MEE, Mukhopadhyay S. IoT Enabled Intelligent Sensor Node for Smart City: Pedestrian Counting and Ambient Monitoring. SENSORS (BASEL, SWITZERLAND) 2019; 19:E3374. [PMID: 31374837 PMCID: PMC6696396 DOI: 10.3390/s19153374] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 07/30/2019] [Accepted: 07/30/2019] [Indexed: 11/17/2022]
Abstract
An Internet of Things (IoT) enabled intelligent sensor node has been designed and developed for smart city applications. The fabricated sensor nodes count the number of pedestrians, their direction of travel along with some ambient parameters. The Field of View (FoV) of Fresnel lens of commercially available passive infrared (PIR) sensors has been specially tuned to monitor the movements of only humans and no other domestic animals such as dogs, cats etc. The ambient parameters include temperature, humidity, pressure, Carbon di Oxide (CO2) and total volatile organic component (TVOC). The monitored data are uploaded to the Internet server through the Long Range Wide Area Network (LoRaWAN) communication system. An intelligent algorithm has been developed to achieve an accuracy of 95% for the pedestrian count. There are a total of 74 sensor nodes that have been installed around Macquarie University and continued working for the last six months.
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Affiliation(s)
- Fowzia Akhter
- Department of Engineering, Macquarie University, Sydney, NSW 2109, Australia
| | - Sam Khadivizand
- Department of Engineering, Macquarie University, Sydney, NSW 2109, Australia
| | - Hasin Reza Siddiquei
- Department of Electrical and Electronic Engineering, Uttara University, Dhaka 1230, Bangladesh
| | - Md Eshrat E Alahi
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Subhas Mukhopadhyay
- Department of Engineering, Macquarie University, Sydney, NSW 2109, Australia.
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Mokhtari G, Anvari-Moghaddam A, Zhang Q, Karunanithi M. Multi-Residential Activity Labelling in Smart Homes with Wearable Tags Using BLE Technology. SENSORS 2018; 18:s18030908. [PMID: 29562666 PMCID: PMC5876614 DOI: 10.3390/s18030908] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Revised: 03/07/2018] [Accepted: 03/14/2018] [Indexed: 11/27/2022]
Abstract
Smart home platforms show promising outcomes to provide a better quality of life for residents in their homes. One of the main challenges that exists with these platforms in multi-residential houses is activity labeling. As most of the activity sensors do not provide any information regarding the identity of the person who triggers them, it is difficult to label the sensor events in multi-residential smart homes. To deal with this challenge, individual localization in different areas can be a promising solution. The localization information can be used to automatically label the activity sensor data to individuals. Bluetooth low energy (BLE) is a promising technology for this application due to how easy it is to implement and its low energy footprint. In this approach, individuals wear a tag that broadcasts its unique identity (ID) in certain time intervals, while fixed scanners listen to the broadcasting packet to localize the tag and the individual. However, the localization accuracy of this method depends greatly on different settings of broadcasting signal strength, and the time interval of BLE tags. To achieve the best localization accuracy, this paper studies the impacts of different advertising time intervals and power levels, and proposes an efficient and applicable algorithm to select optimal value settings of BLE sensors. Moreover, it proposes an automatic activity labeling method, through integrating BLE localization information and ambient sensor data. The applicability and effectiveness of the proposed structure is also demonstrated in a real multi-resident smart home scenario.
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Affiliation(s)
- Ghassem Mokhtari
- Deloitte Consulting Pty Ltd., Riverside Center, Brisbane 4000, Australia.
- CSIRO Australian e-Health Research Center, Butterfield St & Bowen Bridge Rd, Herston, QLD 4029, Australia.
| | | | - Qing Zhang
- CSIRO Australian e-Health Research Center, Butterfield St & Bowen Bridge Rd, Herston, QLD 4029, Australia.
| | - Mohanraj Karunanithi
- CSIRO Australian e-Health Research Center, Butterfield St & Bowen Bridge Rd, Herston, QLD 4029, Australia.
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Yan J, Lou P, Li R, Hu J, Xiong J. Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors. SENSORS 2018; 18:s18020604. [PMID: 29462908 PMCID: PMC5854993 DOI: 10.3390/s18020604] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Revised: 02/01/2018] [Accepted: 02/11/2018] [Indexed: 11/18/2022]
Abstract
Analysis of the multiple factors affecting human identification ability based on pyroelectric infrared technology is a complex problem. First, we examine various sensed pyroelectric waveforms of the human body thermal infrared signal and reveal a mechanism for affecting human identification. Then, we find that the mechanism is decided by the distance, human target, pyroelectric infrared (PIR) sensor, the body type, human moving velocity, signal modulation mask, and Fresnel lens. The mapping relationship between the sensed waveform and multiple influencing factors is established, and a group of mathematical models are deduced which fuse the macro factors and micro factors. Finally, the experimental results show the macro-factors indirectly affect the recognition ability of human based on the pyroelectric technology. At the same time, the correctness and effectiveness of the mathematical models is also verified, which make it easier to obtain more pyroelectric infrared information about the human body for discriminating human targets.
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Affiliation(s)
- Junwei Yan
- School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China; (J.Y.); (P.L.); (J.H.)
| | - Ping Lou
- School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China; (J.Y.); (P.L.); (J.H.)
| | - Ruiya Li
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China;
| | - Jianmin Hu
- School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China; (J.Y.); (P.L.); (J.H.)
| | - Ji Xiong
- School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China; (J.Y.); (P.L.); (J.H.)
- Correspondence: ; Tel.: +86-1363-8600-244
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Luo X, Tan H, Guan Q, Liu T, Zhuo HH, Shen B. Abnormal Activity Detection Using Pyroelectric Infrared Sensors. SENSORS 2016; 16:s16060822. [PMID: 27271632 PMCID: PMC4934248 DOI: 10.3390/s16060822] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Revised: 05/30/2016] [Accepted: 05/31/2016] [Indexed: 11/21/2022]
Abstract
Healthy aging is one of the most important social issues. In this paper, we propose a method for abnormal activity detection without any manual labeling of the training samples. By leveraging the Field of View (FOV) modulation, the spatio-temporal characteristic of human activity is encoded into low-dimension data stream generated by the ceiling-mounted Pyroelectric Infrared (PIR) sensors. The similarity between normal training samples are measured based on Kullback-Leibler (KL) divergence of each pair of them. The natural clustering of normal activities is discovered through a self-tuning spectral clustering algorithm with unsupervised model selection on the eigenvectors of a modified similarity matrix. Hidden Markov Models (HMMs) are employed to model each cluster of normal activities and form feature vectors. One-Class Support Vector Machines (OSVMs) are used to profile the normal activities and detect abnormal activities. To validate the efficacy of our method, we conducted experiments in real indoor environments. The encouraging results show that our method is able to detect abnormal activities given only the normal training samples, which aims to avoid the laborious and inconsistent data labeling process.
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Affiliation(s)
- Xiaomu Luo
- School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou 510006, China.
| | - Huoyuan Tan
- School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou 510006, China.
| | - Qiuju Guan
- College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture Engineering, Guangzhou 5102256, China.
| | - Tong Liu
- Department of Electronic Science, Huizhou University, Huizhou 516007, China.
| | - Hankz Hankui Zhuo
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006, China.
| | - Baihua Shen
- School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China.
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Sudhakaran JM, Philip J. Triglycine sulphate and its deuterated analog in polyurethane matrix for thermal/infrared detection: A comparison. J Appl Polym Sci 2015. [DOI: 10.1002/app.42250] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | - Jacob Philip
- Department of Instrumentation; Cochin University of Science and Technology; Cochin 682 022 Kerala India
- Amal Jyothi College of Engineering; Kanjirappally Kottayam 686 518 Kerala India
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Wireless displacement sensing of micromachined spiral-coil actuator using resonant frequency tracking. SENSORS 2014; 14:12399-409. [PMID: 25014100 PMCID: PMC4168463 DOI: 10.3390/s140712399] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Revised: 07/06/2014] [Accepted: 07/07/2014] [Indexed: 11/17/2022]
Abstract
This paper reports a method that enables real-time displacement monitoring and control of micromachined resonant-type actuators using wireless radiofrequency (RF). The method is applied to an out-of-plane, spiral-coil microactuator based on shape-memory-alloy (SMA). The SMA spiral coil forms an inductor-capacitor resonant circuit that is excited using external RF magnetic fields to thermally actuate the coil. The actuation causes a shift in the circuit's resonance as the coil is displaced vertically, which is wirelessly monitored through an external antenna to track the displacements. Controlled actuation and displacement monitoring using the developed method is demonstrated with the microfabricated device. The device exhibits a frequency sensitivity to displacement of 10 kHz/µm or more for a full out-of-plane travel range of 466 µm and an average actuation velocity of up to 155 µm/s. The method described permits the actuator to have a self-sensing function that is passively operated, thereby eliminating the need for separate sensors and batteries on the device, thus realizing precise control while attaining a high level of miniaturization in the device.
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