Analysis and real-time monitoring of air quality in single-family homes through the use of the time series and business intelligence

2018 ◽  
Author(s):  
Bryan Erazo ◽  
Bryan Espinosa ◽  
Paola Pelaez ◽  
Freddy Tapia Leon
Keyword(s):  
Time Series ◽  
Air Quality ◽  
Real Time ◽  
Business Intelligence ◽  
Single Family ◽  
Real Time Monitoring

scholarly journals Indoor Air Quality Real-Time Monitoring in Airport Terminal Areas: An Opportunity for Sustainable Management of Micro-Climatic Parameters

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3798 ◽  
Author(s):  
Sara Zanni ◽  
Francesco Lalli ◽  
Eleonora Foschi ◽  
Alessandra Bonoli ◽  
Luca Mantecchini
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Real Time ◽  
Indoor Air ◽  
Electronic Monitoring ◽  
Ventilation System ◽  
Real Time Monitoring ◽  
Airport Terminal ◽  
Air Ventilation ◽  
Gaseous Contaminants

Indoor air quality (IAQ) management in public spaces is assuming a remarkable importance. Busy environments, like airport terminals, are currently regarded as possible hotspots and IAQ is a crucial element for passengers and staff protection, as well as a key aspect of airport passenger experience. A one-month monitoring period has been performed on IAQ in the airport of Bologna (Italy), as prototypal example of large regional airport. Four strategic areas within the airport have been equipped with electronic monitoring platforms, including different contaminants and two microclimatic sensors. Data suggest that daily variation in IAQ parameters typically follow the activity pattern of the different environments under study (i.e., passengers’ flows) for gaseous contaminants, where particulate matter counts oscillate in a definite range, with a significant role played by ventilation system. Gaseous contaminants show a correlation between indoor and outdoor concentrations, mainly due to airside activities. Micro-climatic comfort parameters have been tested to match with standards for commercial environments. As results appears in line with typical households IAQ values, the current air ventilation system appears to be adequate. Nevertheless, an integrated air management system, based on real-time monitoring, would lead to optimization and improvement in environmental and economical sustainability.

scholarly journals Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series

Forests ◽  
2017 ◽  
Vol 8 (8) ◽  
pp. 275 ◽  
Author(s):  
Valerie Pasquarella ◽  
Bethany Bradley ◽  
Curtis Woodcock
Keyword(s):  
Time Series ◽  
Real Time ◽  
Real Time Monitoring ◽  
Insect Defoliation

The Development and Application of Real-Time Monitoring and Forecasting System of Urban Air Quality

2012 ◽  
Vol 201-202 ◽  
pp. 586-589
Author(s):  
Rui Lian Hou
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Urban Air Quality ◽  
Urban Air ◽  
Real Time Monitoring ◽  
Network Database ◽  
Low Energy Consumption ◽  
Function Modules ◽  
Monitoring And Forecasting ◽  
Forecasting System

Underlying on the technologies of internet, network database and GIS, this paper presents the total solution of the development of the real-time monitoring and forecasting system model of urban air quality, which fulfils the requirements to low energy consumption and quick response and provides reference for similar project research.The paper systematically describes the system target,background of the development,running environment choice of the software, process of the development etc.Then it analyses function modules of the system.At last it gives the structures and implementation methods of the system’s database and the system security solution.This system not only can generate the state analysis reports and the early warning, but also can visualize the data analysing of the air quality by GIS.

scholarly journals Research on a Real-Time Monitoring Method for the Wear State of a Tool Based on a Convolutional Bidirectional LSTM Model

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1233 ◽  
Author(s):  
Chen ◽  
Xie ◽  
Yuan ◽  
Huang ◽  
Li
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Tool Wear ◽  
Real Time ◽  
Original Data ◽  
Attention Mechanism ◽  
Cnc Machining ◽  
Numerical Control ◽  
Real Time Monitoring ◽  
Monitoring Method

To monitor the tool wear state of computerized numerical control (CNC) machining equipment in real time in a manufacturing workshop, this paper proposes a real-time monitoring method based on a fusion of a convolutional neural network (CNN) and a bidirectional long short-term memory (BiLSTM) network with an attention mechanism (CABLSTM). In this method, the CNN is used to extract deep features from the time-series signal as an input, and then the BiLSTM network with a symmetric structure is constructed to learn the time-series information between the feature vectors. The attention mechanism is introduced to self-adaptively perceive the network weights associated with the classification results of the wear state and distribute the weights reasonably. Finally, the signal features of different weights are sent to a Softmax classifier to classify the tool wear state. In addition, a data acquisition experiment platform is developed with a high-precision CNC milling machine and an acceleration sensor to collect the vibration signals generated during tool processing in real time. The original data are directly fed into the depth neural network of the model for analysis, which avoids the complexity and limitations caused by a manual feature extraction. The experimental results show that, compared with other deep learning neural networks and traditional machine learning network models, the model can predict the tool wear state accurately in real time from original data collected by sensors, and the recognition accuracy and generalization have been improved to a certain extent.

Real-Time Data Quality Monitoring System for Data Cleansing

2012 ◽  
Vol 3 (1) ◽  
pp. 83-93
Author(s):  
Cihan Varol ◽  
Henry Neumann
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Business Intelligence ◽  
Quality Attributes ◽  
Real Time Monitoring ◽  
Time Data ◽  
Main Concept ◽  
Data Cleansing ◽  
Data Set ◽  
Personal Names

To assist business intelligence companies dealing with data preparation problems, different approaches have been developed to handle the dirty data. However, these data cleansing approaches do not have real-time monitoring capabilities. Therefore, business intelligence companies and their clients are not able to predict the final outcome before running all business process. This yields an extra cost for the company if the data are highly corrupted. Therefore, to reduce cost for these types of businesses, the authors design a framework that monitors the quality attributes during the data cleansing process. Moreover, the system provides feedback to the user and allows the user to restructure the workflow based on quality attributes. The main concept of the framework is based on client-server architecture that uses multithreading to allow real-time monitoring of the process. A child thread is dedicated to run and another is dedicated to monitor the processes and give feedback to the user. The real-time monitoring system not only displays the cleansing process done on the data set, but also estimates the risk propagation probabilities in the data cleansing process. De-duplication elimination, address normalization, spelling correction for personal names, and non-ASCII character removal techniques are employed.

scholarly journals Indoor Air Quality Real-Time Monitoring Results of Pathology Department

2015 ◽  
Vol 06 (08) ◽  
pp. 851-856 ◽  
Author(s):  
Like Shi ◽  
Yue Wang ◽  
Liang Xu ◽  
Yan Liu ◽  
Dongsheng Yao ◽  
...  
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Real Time ◽  
Indoor Air ◽  
Real Time Monitoring ◽  
Pathology Department
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