Sensor-Based Optimization Model for Air Quality Improvement in Home IoT

Kim, Jonghyuk; Hwangbo, Hyunwoo

doi:10.3390/s18040959

Cited by 19 publications

(13 citation statements)

References 37 publications

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“…[7,8,9,10,11]. In addition, e-noses can also be applied to the monitoring of air quality [12,13,14,15,16,17,18], of gases emitted by the soil [1,19,20,21], in the evaluation of the food quality [22,23,24], the quality of wine [25,26], medical applications [27,28,29,30], among others.…”

Section: Introductionmentioning

confidence: 99%

A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose

Voss

Júnior

Farinelli

et al. 2019

Sensors

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Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.

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Section: Introductionmentioning

confidence: 99%

A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose

Voss

Júnior

Farinelli

et al. 2019

Sensors

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“…To easily access the IoT system through the Web or mobile applications in air quality improvement model. (Kim and Hwangbo, 2018) A big data analysis of PM2.5 and PM10 from low cost air quality sensors near traffic areas.…”

Section: The Specific Modeling Techniquesmentioning

confidence: 99%

Development of IoT Technologies for Air Pollution Prevention and Improvement

Zhao

Jiali

Huang

et al. 2020

Aerosol Air Qual. Res.

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In order to mitigate the challenges of air pollution prevention and improvement, a large number of Internet of Things (IoT) related technologies have been developed to evaluate and monitor various parameters of air quality. This paper reviews the fundamental characteristics of IoT technologies and accordingly proposes an intelligent and multifunctional IoT monitoring platform to prevent and improve air pollution. The techniques of radio frequency identification (RFID), M2M and sensor network were discussed and compared. To improve the ambient air quality more efficiently, the comprehensive network communication system, cloud decision system, tracking information system, and online management system should be well established using IoT technologies. Meanwhile, we also discussed several cases verifying the availability and feasibility of the performance of the smart ambient air quality management platform on the IoT basis.

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“…Taiwan’s economy has grown rapidly over the past few decades, but although this has greatly increased wealth, it has also caused environmental pollution. Air quality control has become an important research issue in an intelligent environment field [ 1 , 2 ]. In particular, because of the topography and prevailing wind directions in western Taiwan, particulate matter produced by industrial parks and thermal power plants cannot easily disperse, which has caused the air pollution situation to deteriorate steadily.…”

Section: Motivation and Goalmentioning

confidence: 99%

Use of Multi-Agent Theory to Resolve Complex Indoor Air Quality Control Problems

Chen

2019

Sensors

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Taiwan has suffered from widespread haze and poor air quality during recent years, and the control of indoor air quality has become an important topic. This study relies on Multi-Agent theory in which collected air quality was used in calculations and after agents make decisions in accordance with pre-written rules to construct and indoor air quality control system and conflict resolution mechanism, which will serve to maintain a healthy and comfortable indoor environment. As for implementation, the simulated system used the Arduino open source microcontroller system to collect air quality data and turn on building equipment in order to improve indoor air quality. This study also used the graphic control program LabVIEW to write a control program and user interface. The implementation verifies the feasibility of applying multi-agent theory to air quality control systems, and an Individual intelligent agent has the basic ability to resolve their own conflicts autonomously. However, when there are multiple factors and user status are simultaneously involved in the decision-making, it is difficult for the system to exhaust all conflict conditions, and when context control surpassing the restrictions of binary logic rule-based reasoning, it is necessary to change the algorithm and redesign the system.

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Sensor-Based Optimization Model for Air Quality Improvement in Home IoT

Cited by 19 publications

References 37 publications

A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose

A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose

Development of IoT Technologies for Air Pollution Prevention and Improvement

Use of Multi-Agent Theory to Resolve Complex Indoor Air Quality Control Problems

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