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Electronics
Special Issues
Applications of Light Sensing Technology
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Applications of Light Sensing Technology

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 3738

Special Issue Editor

Dr. Xin Li

E-Mail Website
Guest Editor
Peter Grünberg Research Centre, College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China
Interests: optoelectronics device based on III–V group semiconductors; light sensing technology; photonic integrated chip; visible light communications

Special Issue Information

Dear Colleagues,

The properties of light (intensity, wavelength, phase, polarization, etc.) are modulated by the environmental conditions, such as chemical factors, biological factors, and motion, which allows them to be utilized for realizing sensing functions. Light sensing technology plays a vital role in many fields and has attracted wide interest from research groups and the industry because of its excellent performance and higher integration.

In recent years, many light sensors have been continuously proposed, and their use demonstrated for new applications such as in health monitoring, environmental perception for autopilot, and wireless sensor networks of IoT (internet of things). This Special Issue is seeking submissions that highlight the emerging applications of light sensing technology and relevant studies that contribute to innovative light sensing devices and systems.

Authors are encouraged to submit original contributions about innovative and novel applications of light sensing technology in any of the following topics:

  • Light emitting diodes optical sensing;
  • Optical fiber sensing;
  • Opto-fluidics sensing;
  • Integrated photonics chip for light sensing;
  • Visible Light Detection and Ranging (VILDAR);
  • Laser Detection and Ranging (LIDAR);
  • Light sensing for internet of things (IoT) system;
  • Light sensing for health and security;
  • Light sensing for smart city.

Submissions on other topics are also welcome as along as they are in accordance with the Special Issue theme.

Dr. Xin Li
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. Electronics 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 2400 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

  • optical fiber sensing
  • opto-fluidics sensing
  • integrated photonics chip for light sensing
  • Visible Light Detection and Ranging (VILDAR)
  • Laser Detection and Ranging (LIDAR)
  • light sensing for internet of things (IoT) system
  • light sensing for health and security
  • light sensing for smart city

Published Papers (2 papers)

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Research

25 pages, 1932 KiB  
Article
LiLo: ADL Localization with Conventional Luminaries and Ambient Light Sensor
by Jiaxuan Wu, Yunfei Feng and Carl K. Chang
Electronics 2022, 11(16), 2503; https://doi.org/10.3390/electronics11162503 - 11 Aug 2022
Viewed by 1471
Abstract
Indoor localization is a key factor for activities of daily living (ADLs)-related services. Many studies invest effort and money on high-cost infrastructure with modified devices. In this paper, an indoor localization system (LiLo) that utilizes ambient light sensor and orientation information on smartphones [...] Read more.
Indoor localization is a key factor for activities of daily living (ADLs)-related services. Many studies invest effort and money on high-cost infrastructure with modified devices. In this paper, an indoor localization system (LiLo) that utilizes ambient light sensor and orientation information on smartphones to recognize ADLs is proposed. Indoor ADLs are recognized by analyzing the data combination of visible light based localization, orientation and time. In the cold start period, LiLo estimates the location based on the computed luminance field map and the frequent orientation, validating the location result by the angle of arrival information. Then, LiLo produces the locations with a machine learning classifier. Compared with previous works, LiLo leaves out the laborious device configuration setup and data collection during the off-line phase. Another advantage is that LiLo utilizes a conventional luminaire and a standard smartphone, without extra infrastructure spreading in rooms. Therefore, every resident with a smartphone can benefit from this technology. An experimental study using data collected from smartphones shows that LiLo is able to achieve high localization accuracy at a low cost. Full article
(This article belongs to the Special Issue Applications of Light Sensing Technology)
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18 pages, 3914 KiB  
Article
Semantic Depth Data Transmission Reduction Techniques Based on Interpolated 3D Plane Reconstruction for Light-Weighted LiDAR Signal Processing Platform
by Taewon Chong, Dongkyu Lee and Daejin Park
Electronics 2022, 11(14), 2135; https://doi.org/10.3390/electronics11142135 - 7 Jul 2022
Cited by 1 | Viewed by 1787
Abstract
In vehicles for autonomous driving, light detection and ranging (LiDAR) is one of the most used sensors, along with cameras. LiDAR sensors that produce a large amount of data in one scan make it difficult to transmit and calculate data in real-time in [...] Read more.
In vehicles for autonomous driving, light detection and ranging (LiDAR) is one of the most used sensors, along with cameras. LiDAR sensors that produce a large amount of data in one scan make it difficult to transmit and calculate data in real-time in the vehicle’s embedded system. In this paper, we propose a platform based on semantic depth data-based data reduction and reconstruction algorithms that reduce the amount of data transmission and minimize the errors between original and restored data in a vehicle system using four LiDAR sensors. The proposed platform consists of four LiDAR sensors, an integrated processing unit (IPU) that reduces the data of the LiDAR sensors, and the main processor that reconstructs the reduced data and processes the image. In the proposed platform, the 58,000 bytes of data constituting one frame detected by the VL-AS16 LiDAR sensor were reduced by an average of 87.4% to 7295 bytes by the data reduction algorithm. In the IPU placed near the LiDAR sensor, the memory usage increased by the data reduction algorithm, but the data transmission time decreased by an average of 40.3%. The transmission time where the vehicle’s processor received one frame of data decreased from an average of 1.79 to 0.28 ms. Compared with the original LiDAR sensor data, the reconstructed data showed an average error of 4.39% in the region of interest (ROI). The proposed platform increased the time required for image processing in the vehicle’s main processor by an average of 6.73% but reduced the amount of data by 87.4% with a decrease in data accuracy of 4.39%. Full article
(This article belongs to the Special Issue Applications of Light Sensing Technology)
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