scholarly journals FUZZY LOGIC PROGRAM FOR BUS INDOOR ENVIRONMENTAL ASSESSMENT

2021 ◽  
Vol 11 (4) ◽  
pp. 129-142
Author(s):  
Adrian Allana ◽  
Alvin Chua
Keyword(s):  
Fuzzy Logic ◽  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Logic Program ◽  
Fuzzy Logic System ◽  
Comfort Index ◽  
Input Parameters ◽  
Four Levels ◽  
Logic System

This paper proposes a fuzzy logic algorithm that evaluates the indoor environmental conditions on an urban bus specifically in Metro Manila. This algorithm identifies the value of three indexes: IAQI, TCI, and CO2. The Indoor Air Quality Index (IAQI) quantifies the level of indoor air quality of the bus. CO2, CO, NO2, O3, TVOC, and PM10 are the input parameters for the fuzzy logic system that will determine IAQI. Thermal Comfort Index (TCI) quantifies the indoor thermal condition in four levels. The indoor temperature and humidity are the input parameters for the fuzzy logic system that will determine TCI. The fuzzy logic program in this study is designed mainly for the bus ventilation control system. The created FLS program was able to give good results. The observations from the program were the following: as the indoor air pollutants increased, the IAQI decreased; as the level of thermal parameters increased, the TCI decreased; and as the CO2 level and temperature increased, the number of passengers also increased.

scholarly journals Determination of indoor air quality in collective living spaces utilizing Fuzzy logic analysis

2020 ◽  
Vol 19 (3) ◽  
pp. 288-300
Author(s):  
Ahmet Cosgun ◽  
Keyword(s):  
Air Pollution ◽  
Fuzzy Logic ◽  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Environmental Protection Agency ◽  
Environmental Pollutants ◽  
The United States ◽  
Indoor Environments ◽  
Negative Effects

Individuals have to work in collective living spaces which might be indoor or outdoor areas. In indoor works, people spend approximately 90% of their time in a closed space. There are many parameters affecting indoor air quality. Among these, for indoor and outdoor, important parameters can be listed as carbon monoxide (CO), carbon dioxide (CO2), sulfur dioxide (SO₂), particles, nitrogen oxides (NOx), various microorganisms, harmful allergens, and powders. Some health problems might emerge in people who stay in indoor environments for a long time. For instance, newborns and infants are more likely to stay indoors. It is the primary reason for occurring many acute and chronic diseases at an early age, as babies and children are more sensitive to environmental pollutants. Recently published studies, which report that appendicitis failures might be fatal and air pollution can increase the rate of these failures, are remarkable. On the other hand, there are many negative effects of polluted indoor air on human health such as attention deficit and excessive daytime sleepiness. Moreover, the negative effects of this kind of indoor air quality on human learning and perception can not be neglected. The researchers focusing on indoor air quality are conducting studies showing that air pollution has an effect on physical activity and neurological interaction in humans. Even though air pollutants in outdoor air content were evaluated with fuzzy logic method in many studies, there are quite few studies using the fuzzy approach for indoor air quality. In this study, through the standard formula developed by the United States Environmental Protection Agency (EPA), calculations were made using fuzzy logic in MATLAB utilizing air quality index. In the study, indoor air quality measurement parameters were evaluated with the “Mamdani” method used in fuzzy logic. In the study, the model suitable for the logic structure created with the fuzzy tool in MATLAB was analyzed with the help of Mamdani method, and the suitability of evaluating the indoor air quality with artificial intelligence was investigated. A set of suggestions has been made evaluating and criticizing the results

scholarly journals Indoor air quality improvement in natural ventilation using a fuzzy logic controller

2020 ◽  
pp. 1-19
Author(s):  
Cezary Kulis ◽  
Jarosław Müller
Keyword(s):  
Fuzzy Logic ◽  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Optical Sensors ◽  
Natural Ventilation ◽  
Fuzzy Logic Controller ◽  
Ventilation System ◽  
Raspberry Pi ◽  
Physical Parameters

The aim of the research was to design and validate the prototype of a device developed to improve the quality of indoor air by supporting the natural ventilation in building. A CO2 sensor and thermo-hygrometer were used to measure the physical parameters of the indoor air. The developed device is based on the Raspberry Pi single-board-computer (SBC) and optical sensors. The prototype casing was made using 3D printing technology. The software was written using the Python 2.7 programming language. The key algorithm of control uses fuzzy logic. The effectiveness of the developed device has been confirmed. The use of the device enabled improvement of the indoor air quality. The presented device may be a solution to improve the indoor air quality by supporting the ventilation system.

Indoor air quality in a metropolitan area metro using fuzzy logic assessment system

2013 ◽  
Vol 449 ◽  
pp. 461-469 ◽  
Author(s):  
M.N. Assimakopoulos ◽  
A. Dounis ◽  
A. Spanou ◽  
M. Santamouris
Keyword(s):  
Fuzzy Logic ◽  
Air Quality ◽  
Indoor Air Quality ◽  
Metropolitan Area ◽  
Indoor Air ◽  
Assessment System

scholarly journals Fuzzy logic-based improved ventilation system for the pharmaceutical industry

2018 ◽  
Vol 7 (2) ◽  
pp. 640 ◽  
Author(s):  
Sam Matiur Rahman ◽  
Mohammad Fazle Rabbi ◽  
Omar Altwijri ◽  
Mahdi Alqahtani ◽  
Tasriva Sikandar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Air Quality ◽  
Pharmaceutical Industry ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Air Flow ◽  
Ventilation System ◽  
Inference System

Indoor air quality in pharmaceutical industry plays a vital role in the production and storing of medicine. Stable indoor environment including favorable temperature, humidity, air flow and number of microorganisms requires consistent monitoring. This paper aimed to develop a fuzzy logic-based intelligent ventilation system to control the indoor air quality in pharmaceutical sites. Specifically, in the proposed fuzzy inference system, the ventilation system can control the air flow and quality in accordance with the indoor temperature, humidity, air flow and microorganisms in the air. The MATLAB® fuzzy logic toolbox was used to simulate the performance of the fuzzy inference system. The results show that the efficiency of the system can be improved by manipulating the input-output parameters according to the user’s demands. Compared with conventional heating, ventilation and air-conditioning (HVAC) systems, the proposed ventilation system has the additional feature of the existence of microorganisms, which is a crucial criterion of indoor air quality in pharmaceutical laboratories.

scholarly journals Combined Model for IAQ Assessment: Part 1—Morphology of the Model and Selection of Substantial Air Quality Impact Sub-Models

2019 ◽  
Vol 9 (18) ◽  
pp. 3918 ◽  
Author(s):  
Piasecki ◽  
Kostyrko
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Quality Index ◽  
Practical Case ◽  
Indoor Environmental Quality ◽  
Comfort Index ◽  
Application Potential

Indoor air quality (IAQ) is one of the most important elements affecting a building user’s comfort and satisfaction. Currently, many methods of assessing the quality of indoor air have been described in the literature. In the authors’ opinion, the methods presented have not been collected, systematized, and organized into one multi-component model. The application purpose of the assessment is extremely important when choosing IAQ model. This article provides the state-of-the-art overview on IAQ methodology and attempts to systematize approach. Sub-models of the processes that impact indoor air quality, which can be distinguished as components of the IAQ model, are selected and presented based on sensory satisfaction functions. Subcomponents of three potential IAQ models were classified according to their application potential: IAQ quality index, IAQ comfort index, and an overall health and comfort index. The authors provide a method for using the combined IAQ index to determine the indoor environmental quality index, IEQ. In addition, the article presents a method for adjusting the weights of particular subcomponents and a practical case study which provides IAQ and IEQ model implementation for a large office building assessment (with a BREEAM rating of excellent).

Fuzzy Comprehensive Evaluation of Air Quality in Home

2014 ◽  
Vol 484-485 ◽  
pp. 484-487
Author(s):  
Qing Tao Wei ◽  
Li Na Zhao ◽  
Hai Ting Lv
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Objective Evaluation ◽  
Weight Vector ◽  
Comprehensive Evaluation Method ◽  
Four Levels

Based on the indoor air quality and the evaluation index, utilize the fuzzy mathematical theory, comprehensively consider on the three important factors which influence the air quality, and through the calculation and determination the weight vector, divide the air quality into four levels as "qualified"," mild overweight"," overweight", "severe overweight". Through sampling the indoor air in a family, according to the fuzzy comprehensive evaluation method and the maximum membership degree principle, get every sample point levels from data. It will provide the method of getting a more objective evaluation of indoor air quality situation.

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