indoor air quality analysis using deep learning with sensor data

Prediction of Indoor Air Temperature Based on Deep Learning

Prediction of Indoor Air Temperature Based on Deep Learning Jing Jin, ... The output is the optimal indoor air temperature. Data collection We adopt the supervised learning method to train the neural network model. (9) One key task is to collect the labeled data obtained from an office used as a benchmark. The overall layout of the office and the sensor distribution are shown in Fig. 2 ...

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[PDF] Indoor Air Quality Analysis Using Deep Learning with ...

Indoor air quality analysis is of interest to understand the abnormal atmospheric phenomena and external factors that affect air quality. By recording and analyzing quality measurements, we are able to observe patterns in the measurements and predict the air quality of near future. We designed a microchip made out of sensors that is capable of periodically recording measurements, and proposed ...

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Time Series Pattern Recognition with Air Quality Sensor Data

· In the project, two datasets are provided, each consists of one week of air quality sensor readings. They are provided to accomplish the following four tasks: 1. Find anomalies in the data set to automatically flag events. 2. Categorize anomalies as “System fault” or “external event” 3. Provide any other useful conclusions from the pattern in the data set. 4. Visualize inter ...

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Indoor Air Quality Analysis Using Deep Learning with ...

Indoor Air Quality Analysis Using Deep Learning with Sensor Data. Authors: Jaehyun Ahn Dongil Shin Kyuho Kim Jihoon Yang. Sensors (Basel) 2017 Oct 28;17(11). Epub 2017 Oct 28. Department of Computer Science and Engineering, Sogang University, Seoul 04107, Korea. Indoor air quality analysis is of interest to understand the abnormal atmospheric phenomena and external factors that affect air ...

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Machine learning and statistical models for predicting ...

· Indoor air quality (IAQ), as determined by the concentrations of indoor air pollutants, can be predicted using either physically based mechanistic models or statistical models that are driven by measured data. In comparison with mechanistic models mostly used in unoccupied or scenario-based environments, statistical models have great potential to explore IAQ captured in large measurement ...

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Chapter 10 Air quality - Department of Environment ...

impacts on indoor air quality. Indoor combustion for cooking and heating, using coal, wood, paraffin or traditional sources of fuel (dung and agricultural . residues) may produce high levels of particulate matter (condensed volatile organic vapours) and carbon monoxide. Exposure to indoor air pollution is dependent on the type of fuel used, type of equipment used, location of the stove, and ...

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Review—Deep Learning Methods for Sensor Based Predictive ...

· Denoising can help in improving the quality of data and hence the quality of the forecasts. Dimensionality reduction can help improve computational efficiency when the data is high dimensional. 53–55. Choosing a network. Forecasting and prognosis are usually implemented using supervised learning. For time-series data, the sensor values themselves constitute the target values. A sliding ...

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The world's most comprehensive air sensor that provides ...

The uHoo Smart Air Indoor Air Quality Monitor performs well and can detect changes in air quality within minutes. Push notifications are quick and provide general guidance on how to mitigate the issue. Unfortunately, it is not possible to export your data at this time. Regardless, it is nice to have some peace-of-mind of the indoor air quality with many of us spending more time at home ...

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Indoor Air Quality Analysis Using Deep Learning with ...

Article “Indoor Air Quality Analysis Using Deep Learning with Sensor Data” Detailed information of the J-GLOBAL is a service based on the concept of Linking, Expanding, and Sparking, linking science and technology information which hitherto stood alone to support the generation of ideas. By linking the information entered, we provide opportunities to make unexpected discoveries and obtain ...

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Indoor Air Quality Analysis Using Deep Learning with ...

Indoor air quality analysis is of interest to understand the abnormal atmospheric phenomena and external factors that affect air quality. By recording and analyzing quality measurements, we are able to observe patterns in the measurements and predict the air quality of near future. We designed a mic … Indoor Air Quality Analysis Using Deep Learning with Sensor Data Sensors (Basel). 2017 Oct ...

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Indoor Air Quality Guide - ASHRAE

Indoor Air Quality Guide: Best Practices for Design, Construction and Commissioning is designed for architects, design engineers, contractors, commissioning agents, and all other professionals concerned with indoor air quality.. Summary (Part I) and Detailed (Part II) Guidance provides: Hundreds of internal and external links to resources for the design, construction, and commissioning of ...

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Predicting Air Quality Index using Python - GeeksforGeeks

· Let us see how to predict the air quality index using Python. AQI is calculated based on chemical pollutant quantity. By using machine learning, we can predict the AQI. AQI: The air quality index is an index for reporting air quality on a daily basis. In other words, it is a measure of how air pollution affects one’s health within a short ...

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Indoor Air Quality Analysis Using Deep Learning with ...

Indoor Air Quality Analysis Using Deep Learning with Sensor Data . By Jaehyun Ahn, Dongil Shin, Kyuho Kim and Jihoon Yang. Cite . BibTex; Full citation; Abstract. Indoor air quality analysis is of interest to understand the abnormal atmospheric phenomena and external factors that affect air quality. By recording and analyzing quality measurements, we are able to observe patterns in the ...

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