Context-Aware Monitoring and Control of Ventilation Rate in Indoor Environments Using Internet of Things

Rastogi, Krati; Lohani, Divya; Acharya, Debopam

doi:10.1109/jiot.2021.3057919

Cited by 18 publications

(9 citation statements)

References 39 publications

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“…Existing published work about IAQ indexes is mainly based on real-time data generated by indoor air pollutants, like the one developed by Yuan et al [90]. Based on the data collected from sensors in a classroom, Rastogi et al [91] proposed a novel method for the determination of ventilation states using three indoor pollutants, PM 2.5 , PM 10 , and carbon monoxide (CO), with three levels of alerts: 1) "poor"; 2) "moderate"; and 3) "good". Balbis-Morejón et al [92] proposed an Air Conditioning Performance Indicator (ACPI) based on six criteria: energy consumption, IAQ, thermal comfort, carbon emissions, investment costs, and finally, operation and maintenance costs.…”

Section: Methodology and Resultsmentioning

confidence: 99%

Filling the Health Gap in Energy Performance Certificates to Reduce Pulmonary Diseases Due to Bad Indoor Air Quality

Reis

Dias

Tavares

2022

Lecture Notes in Civil Engineering

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Section: Methodology and Resultsmentioning

confidence: 99%

Filling the Health Gap in Energy Performance Certificates to Reduce Pulmonary Diseases Due to Bad Indoor Air Quality

Reis

Dias

Tavares

2022

Lecture Notes in Civil Engineering

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“…Cybercriminals have developed a substantial criminal interest in the music ecosystem. e influx of visitors combined with the vast amounts of music content spent daily creates a new landscape of threats [22]. By this logic, they often utilize advanced techniques, even zero-day attacks, to steal credentials and generally launch ATA on music streaming platforms.…”

Section: Use Casementioning

confidence: 99%

Cyberattacks Defense in Digital Music Streaming Platforms by Mobile Distributed Machine Learning

Fan

2022

Computational Intelligence and Neuroscience

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Given the massive popularity of digital music industry repositories and their corresponding targeting by cybercriminals, this paper presents an intelligent model for cyberattacks defense in digital music streaming platforms by mobile distributed machine learning. The basic idea of machine learning is to use large data sets to create a model that responds well to inputs it has never processed before. With the increase in data volume and complexity of models, it becomes increasingly challenging to complete machine learning processes in a single machine. Distributed ML was developed to solve this problem, and a standard procedure is completed through the collaboration of multiple servers. With the evolution of mobile devices and the increase in their number, it is possible to create an integrated and compact mobile distributed machine learning (MDML) system that could reduce the workload of servers. A distributed logit polynomial function model is proposed, which is used to model options in distributed binary regression accounting units, which are of low complexity and high stability in noisy environments.

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“…Previous studies have examined ventilation rates [6,7,14,15,45,46]. However, most of them recommend values of ventilation rates required to eliminate anthropogenic pollution in classrooms under a single temperature condition, without considering the effect of temperature on human biological emissions.…”

Section: Introductionmentioning

confidence: 99%

Field and intervention study on indoor environment in professional classrooms

Lyu

2024

Build. Eng.

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To study the variation of environment in the professional classroom during lecture hours, multiple field experiments and intervention experiments on indoor and outdoor temperatures were conducted in a university professional classroom in Shaoxing during the spring. Environmental data, including indoor and outdoor temperatures, relative, and CO2 concentrations, were recorded every 5 min. Volatile organic compounds (VOC) were sampled, and indoor air quality was evaluated repeatedly. Results showed that the classroom’s average indoor air temperature ranged from 17.8–29.2 ℃, the average indoor relative humidity from 34.5%–91.0%, the average CO2 concentrations from 921.6–1805.2 ppmv, and total VOC concentrations from 330–682 ppbm. The subjective evaluation conducted during the intervention experiments indicated a significant increase in perceived odor intensity upon entering the classroom. When the CO2 concentration reached 2000 ppmv, the satisfaction and acceptability of the air quality for the subjects and invitees decreased significantly. In the temperature range of 17–31 ℃, the CO2 emission rate of human body was estimated to increase by 0.78 L/h for every 1 ℃ increase in temperature. To maintain the indoor CO2 concentration at 1000 ppmv, the required ventilation rate for each person must be increased by 0.25 ± 0.3 L/s.

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Context-Aware Monitoring and Control of Ventilation Rate in Indoor Environments Using Internet of Things

Cited by 18 publications

References 39 publications

Filling the Health Gap in Energy Performance Certificates to Reduce Pulmonary Diseases Due to Bad Indoor Air Quality

Filling the Health Gap in Energy Performance Certificates to Reduce Pulmonary Diseases Due to Bad Indoor Air Quality

Cyberattacks Defense in Digital Music Streaming Platforms by Mobile Distributed Machine Learning

Field and intervention study on indoor environment in professional classrooms

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