Implementation of an Intelligent Indoor Environmental Monitoring and management system in cloud

Yang, Chao-Tung; Hsu, Chih‐Yu; Den, Walter; Wang, Yunting; Kristiani, Endah

doi:10.1016/j.future.2018.02.041

Cited by 99 publications

(42 citation statements)

References 18 publications

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“…It has been indicated that in the development strategies of the WSN system, ZigBee, a wireless standard based on the IEEE 802.15.4 specification, is regarded as the most reliable communication protocol because of its low cost, low consumption, and low data rate [187,188]. In addition, use of the ZigBee protocol allows networks to work in power-saving mode [189,190].…”

Section: Wireless Sensor Network (Wsn)-based Systemsmentioning

confidence: 99%

Indoor Air Pollution, Related Human Diseases, and Recent Trends in the Control and Improvement of Indoor Air Quality

Tran

Park

Lee

2020

IJERPH

432

164

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Indoor air pollution (IAP) is a serious threat to human health, causing millions of deaths each year. A plethora of pollutants can result in IAP; therefore, it is very important to identify their main sources and concentrations and to devise strategies for the control and enhancement of indoor air quality (IAQ). Herein, we provide a critical review and evaluation of the major sources of major pollutant emissions, their health effects, and issues related to IAP-based illnesses, including sick building syndrome (SBS) and building-related illness (BRI). In addition, the strategies and approaches for control and reduction of pollutant concentrations are pointed out, and the recent trends in efforts to resolve and improve IAQ, with their respective advantages and potentials, are summarized. It is predicted that the development of novel materials for sensors, IAQ-monitoring systems, and smart homes is a promising strategy for control and enhancement of IAQ in the future.

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Section: Wireless Sensor Network (Wsn)-based Systemsmentioning

confidence: 99%

Indoor Air Pollution, Related Human Diseases, and Recent Trends in the Control and Improvement of Indoor Air Quality

Tran

Park

Lee

2020

IJERPH

432

164

View full text Add to dashboard Cite

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“…According to the WHO surveillance case definition, ILI is defined as an acute respiratory infection with fever more than 38 °C and with cough symptoms, as well as morbidity within the last 10 days. This study will collect information on the rate of influenza-like emergency visits from the Department of Health and Welfare and the PM 2.5 open-source data from the Environmental Protection Department's Air Quality Monitoring Network [16]. Deep learning techniques are used to predict the status of future influenza-like treatment and the effects of air pollution on the respiratory tract in inducing influenza-like symptoms, as well as the natural delay characteristics between a patient's inhalation of excessively high levels of contaminated gases and the onset of flu-like symptoms [17].…”

Section: Introductionmentioning

confidence: 99%

Influenza-like illness prediction using a long short-term memory deep learning model with multiple open data sources

et al. 2020

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The influenza problem has always been an important global issue. It not only affects people's health problems but is also an essential topic of governments and health care facilities. Early prediction and response is the most effective control method for flu epidemics. It can effectively predict the influenza-like illness morbidity, and provide reliable information to the relevant facilities. For social facilities, it is possible to strengthen epidemic prevention and care for highly sick groups. It can also be used as a reminder for the public. This study collects information on the influenzalike illness emergency department visits to the Taiwan Centers for Disease Control, and the PM 2.5 open-source data from the Taiwan Environmental Protection Administration's air quality monitoring network. By using deep learning techniques, the relevance of short-term estimates and the outbreak calculation method can be determined. The techniques are published by the WHO to determine whether the influenza-like illness situation is still in a stage of reasonable control. Finally, historical data and future forecasted data are integrated on the web page for visual presentation, to show the actual regional air quality situation and influenza-like illness data and to predict whether there is an outbreak of influenza in the region.

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“…Fuzzy partitions allow a node belongs to multiple communities simultaneously. Considering a real-world situation, some staff work together in a building, and the manager would like to track the movement history for each staff [ 11 ]. Each one may move to various rooms, and the move purpose comes from the role of each staff.…”

Section: Introductionmentioning

confidence: 99%

Detecting Overlapping Communities in Modularity Optimization by Reweighting Vertices

Tsung

Chen

et al. 2020

Entropy

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On the purpose of detecting communities, many algorithms have been proposed for the disjointed community sets. The major challenge of detecting communities from the real-world problems is to determine the overlapped communities. The overlapped vertices belong to some communities, so it is difficult to be detected using the modularity maximization approach. The major problem is that the overlapping structure barely be found by maximizing the fuzzy modularity function. In this paper, we firstly introduce a node weight allocation problem to formulate the overlapping property in the community detection. We propose an extension of modularity, which is a better measure for overlapping communities based on reweighting nodes, to design the proposed algorithm. We use the genetic algorithm for solving the node weight allocation problem and detecting the overlapping communities. To fit the properties of various instances, we introduce three refinement strategies to increase the solution quality. In the experiments, the proposed method is applied on both synthetic and real networks, and the results show that the proposed solution can detect the nontrivial valuable overlapping nodes which might be ignored by other algorithms.

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Implementation of an Intelligent Indoor Environmental Monitoring and management system in cloud

Cited by 99 publications

References 18 publications

Indoor Air Pollution, Related Human Diseases, and Recent Trends in the Control and Improvement of Indoor Air Quality

Indoor Air Pollution, Related Human Diseases, and Recent Trends in the Control and Improvement of Indoor Air Quality

Influenza-like illness prediction using a long short-term memory deep learning model with multiple open data sources

Detecting Overlapping Communities in Modularity Optimization by Reweighting Vertices

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