ArticleSensors (Basel, Switzerland)2019
Using the IBM SPSS SW Tool with Wavelet Transformation for CO₂ Prediction within IoT in Smart Home Care.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Review of an intelligent indoor environment monitoring and management system for COVID-19 risk mitigation.Frontiers in public health · 2022Pooled it
- Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care.Sensors (Basel, Switzerland) · 2023Article
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- The Current Situation and Learning Strategies of Foreign Students in Chinese Learning Following Entrepreneurial Psychology.Frontiers in psychology · 2021Article
- Indirect Recognition of Predefined Human Activities.Sensors (Basel, Switzerland) · 2020Article
- Prevalence and Antimicrobial Susceptibility Patterns of Bacterial Pathogens in Urinary Tract Infections in University Hospital of Campania "Luigi Vanvitelli" between 2017 and 2018.Antibiotics (Basel, Switzerland) · 2020Article
- Wavelet-Based Filtration Procedure for Denoising the Predicted COSensors (Basel, Switzerland) · 2020Article
- Design of a New Method for Detection of Occupancy in the Smart Home Using an FBG Sensor.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Standard solutions for handling a large amount of measured data obtained from intelligent buildings are currently available as software tools in IoT platforms. These solutions optimize the operational and technical functions managing the quality of the indoor environment and factor in the real needs of residents. The paper examines the possibilities of increasing the accuracy of CO₂ predictions in Smart Home Care (SHC) using the IBM SPSS software tools in the IoT to determine the occupancy times of a monitored SHC room. The processed data were compared at daily, weekly and monthly intervals for the spring and autumn periods. The Radial Basis Function (RBF) method was applied to predict CO₂ levels from the measured indoor and outdoor temperatures and relative humidity. The most accurately predicted results were obtained from data processed at a daily interval. To increase the accuracy of CO₂ predictions, a wavelet transform was applied to remove additive noise from the predicted signal. The prediction accuracy achieved in the selected experiments was greater than 95%.
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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.