ArticleHardwareX2025
A 360-degree imagery-multisensor system for visualizing environmental parameters in architecture and urban spaces.
Article in HardwareX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This research has designed a 360-degree imagery-multisensor system aiming to capture and visualize environmental parameters in architecture and urban spaces. Unlike existing tools, this system enables simultaneous recording of both imagery and non-imagery environmental data, including lighting, thermal, air quality, sound, and physical space parameters, within a 360-degree field of view. Lighting conditions are captured using panoramic high dynamic range imagery, complemented by a 360-degree array of sensors measuring illuminance levels and spectral power distribution. Thermal and air quality conditions are recorded using 360-degree thermal imagery, combined with hygrometers and air particle meters. Sound levels are also monitored across the full 360-degree field. The system is built using 3D printing technologies and Raspberry Pi computers, equipped with various sensor modules. Custom Python scripts enable real-time data capture, processing, and visualization. This cost-effective, easy-to-manufacture, programmable, and customizable innovation is aimed at students and educators in design and architecture, as well as building engineers. Furthermore, integrating imagery and sensor data supports the development of immersive virtual and augmented reality applications, offering new opportunities for education and the exploration of effective design solutions.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.