Accurately positioning energy-constrained devices in indoor environments is of great interest to many professional, care, and personal applications. Hybrid RF-acoustic ranging systems have shown to be a viable technology in this regard, enabling accurate distance measurements at ultra-low energy costs. However, they often suffer from self-interference due to multipaths in indoor environments. We replace the typical single loudspeaker beacons used in these systems with a phased loudspeaker array to promote the signal-to-interference-plus-noise ratio towards the tracked device. Specifically, we optimize the design of a low-cost uniform planar array (UPA) through simulation to achieve the best ranging performance using ultrasonic chirps. Furthermore, we compare the ranging performance of this optimized UPA configuration to a traditional, single-loudspeaker system. Simulations show that vertical phased-array configurations guarantee the lowest ranging errors in typical shoe-box environments, having a limited height with respect to their length and width. In these cases, a P50 ranging error of around 3 cm and P95 ranging error below 30 cm were achieved. Compared to a single-speaker system, a 10 × 2 vertical phased array was able to lower the P80 and P95 up to an order of magnitude.
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http://dx.doi.org/10.3390/s23187997 | DOI Listing |
Environ Res
January 2025
Institute of Environmental and Occupational Health Sciences, National Yang-Ming Chiao-Tung University, Taipei, 11221, Taiwan. Electronic address:
Ground-level ozone (O) can infiltrate indoor environments, severely impacting the environment and human health. Moisture-induced catalyst deactivation is a major challenge in catalytic ozone removal. MOF-template-derived heterojunctions supported by carbon materials can prevent chemisorption of water vapor at active sites.
View Article and Find Full Text PDFPLoS One
January 2025
Changchun University of Science and Technology, School of Optoelectronic Engineering, Changchun, Jilin, China.
Accurate localization is a critical technology for the application of intelligent robots and automation systems in complex indoor environments. Traditional visual SLAM (Simultaneous Localization and Mapping) techniques often face challenges with localization accuracy in high similarity scenes. To address this issue, this paper proposes an improved visual SLAM loop closure detection algorithm that integrates deep learning techniques.
View Article and Find Full Text PDFActa Parasitol
January 2025
Research Center for Hydatid Disease in Iran, Institute of Infectious Diseases and Tropical Medicine, Afzalipour School of Medicine, Kerman University of Medical Sciences, Kerman, Iran.
Objective: Different Acanthamoeba species are among the most ubiquitous organisms causing serious diseases in humans including central nervous system (CNS) and eye infections. Contact lenses, lens care solutions and the hospital environments particularly the indoor and outdoor environments of ophthalmology wards where people are present with different types of eye diseases, are the potential sources of human infection. The purpose of the present study was the molecular investigation of free-living amoebae in the used contact lenses, lens care solutions and hospital samples from the ophthalmology wards and operating rooms in a referral hospital in southeastern Iran.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Intelligent Systems & Robotics, Chungbuk National University, Cheongju 28644, Republic of Korea.
Handheld LiDAR scanners, which typically consist of a LiDAR sensor, Inertial Measurement Unit, and processor, enable data capture while moving, offering flexibility for various applications, including indoor and outdoor 3D mapping in fields such as architecture and civil engineering. Unlike fixed LiDAR systems, handheld devices allow data collection from different angles, but this mobility introduces challenges in data quality, particularly when initial calibration between sensors is not precise. Accurate LiDAR-IMU calibration, essential for mapping accuracy in Simultaneous Localization and Mapping applications, involves precise alignment of the sensors' extrinsic parameters.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institute of Computer Science, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland.
Simultaneous localization and mapping (SLAM) techniques can be used to navigate the visually impaired, but the development of robust SLAM solutions for crowded spaces is limited by the lack of realistic datasets. To address this, we introduce InCrowd-VI, a novel visual-inertial dataset specifically designed for human navigation in indoor pedestrian-rich environments. Recorded using Meta Aria Project glasses, it captures realistic scenarios without environmental control.
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