Comparison of edge computing methods in Internet of Things architectures for efficient estimation of indoor environmental parameters with Machine Learning
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Comparison of edge computing methods in Internet of Things architectures for efficient estimation of indoor environmental parameters with Machine Learning
Authors
Keywords
-
Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 126, Issue -, Pages 107149
Publisher
Elsevier BV
Online
2023-10-05
DOI
10.1016/j.engappai.2023.107149
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Optimal fog node selection based on hybrid particle swarm optimization and firefly algorithm in dynamic fog computing services
- (2023) Sunday Oyinlola Ogundoyin et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- An innovative deep anomaly detection of building energy consumption using energy time-series images
- (2023) Abigail Copiaco et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- The State-of-the-Art in Air Pollution Monitoring and Forecasting Systems Using IoT, Big Data, and Machine Learning
- (2023) Amisha Gangwar et al. WIRELESS PERSONAL COMMUNICATIONS
- Assessing the perception of overall indoor environmental quality: Model validation and interpretation
- (2022) Hao Tang et al. ENERGY AND BUILDINGS
- Integrated artificial neural network prediction model of indoor environmental quality in a school building
- (2022) Ji Hyeon Cho et al. Journal of Cleaner Production
- Updating Indoor Air Quality (IAQ) Assessment Screening Levels with Machine Learning Models
- (2022) Ling-Tim Wong et al. International Journal of Environmental Research and Public Health
- IoT-based platform for automated IEQ spatio-temporal analysis in buildings using machine learning techniques
- (2022) Francisco Troncoso-Pastoriza et al. AUTOMATION IN CONSTRUCTION
- Prediction and optimization of thermal comfort, IAQ and energy consumption of typical air-conditioned rooms based on a hybrid prediction model
- (2022) Fangli Hou et al. BUILDING AND ENVIRONMENT
- Smart Air Quality Monitoring IoT-Based Infrastructure for Industrial Environments
- (2022) Laura García et al. SENSORS
- Internet of Things (IoT) Based Indoor Air Quality Sensing and Predictive Analytic—A COVID-19 Perspective
- (2021) Rafia Mumtaz et al. Electronics
- Moving to a green building: Indoor environment quality, thermal comfort and health
- (2021) Rana Elnaklah et al. BUILDING AND ENVIRONMENT
- Parameter estimation of proton exchange membrane fuel cell using a novel meta-heuristic algorithm
- (2021) Manish Kumar Singla et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- Photovoltaic cell parameter estimation based on improved equilibrium optimizer algorithm
- (2021) Jingbo Wang et al. ENERGY CONVERSION AND MANAGEMENT
- An IoT enabled system for enhanced air quality monitoring and prediction on the edge
- (2021) Ahmed Samy Moursi et al. Complex & Intelligent Systems
- Use of optimised MLP neural networks for spatiotemporal estimation of indoor environmental conditions of existing buildings
- (2021) Miguel Martínez-Comesaña et al. BUILDING AND ENVIRONMENT
- ANN-based position and speed sensorless estimation for BLDC motors
- (2021) Jose-Carlos Gamazo-Real et al. MEASUREMENT
- An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
- (2021) Abdulmohsen Almalawi et al. ENVIRONMENTAL RESEARCH
- Indoor Air Quality Monitoring Systems for Enhanced Living Environments: A Review toward Sustainable Smart Cities
- (2020) Gonçalo Marques et al. Sustainability
- A performance comparison of multi-objective optimization-based approaches for calibrating white-box building energy models
- (2020) Sandra Martínez et al. ENERGY AND BUILDINGS
- Data Flow and Distributed Deep Neural Network based low latency IoT-Edge computation model for big data environment
- (2020) Veeramanikandan et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Distributed Fog Computing for Internet of Things (IoT) Based Ambient Data Processing and Analysis
- (2020) Mehreen Ahmed et al. Electronics
- Spatial interpolation-based analysis method targeting visualization of the indoor thermal environment
- (2020) Zhuoyu Yu et al. BUILDING AND ENVIRONMENT
- Vector field-based support vector regression for building energy consumption prediction
- (2019) Hai Zhong et al. APPLIED ENERGY
- Machine learning and statistical models for predicting indoor air quality
- (2019) Wenjuan Wei et al. INDOOR AIR
- From Cloud Down to Things: An Overview of Machine Learning in Internet of Things
- (2019) Farzad Samie et al. IEEE Internet of Things Journal
- Real-Time Monitoring of Indoor Air Quality with Internet of Things-Based E-Nose
- (2019) Mehmet Taştan et al. Applied Sciences-Basel
- Climate Compensation and Indoor Temperature Optimal Measuring Point Energy Saving Control in VAV Air-Conditioning System
- (2019) Xiuying Yan et al. Energies
- Distributing Intelligence to the Edge and Beyond [Research Frontier]
- (2019) Edgar Ramos et al. IEEE Computational Intelligence Magazine
- Review of parameters used to assess the quality of the indoor environment in Green Building certification schemes for offices and hotels
- (2019) Wenjuan Wei et al. ENERGY AND BUILDINGS
- Industry 4.0: A bibliometric analysis and detailed overview
- (2018) Pranab K. Muhuri et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Applications of Python to evaluate environmental data science problems
- (2017) Akhil Kadiyala et al. Environmental Progress & Sustainable Energy
- Data Fusion and IoT for Smart Ubiquitous Environments: A Survey
- (2017) Furqan Alam et al. IEEE Access
- Edge Computing: Vision and Challenges
- (2016) Weisong Shi et al. IEEE Internet of Things Journal
- A review on buildings energy consumption information
- (2007) Luis Pérez-Lombard et al. ENERGY AND BUILDINGS
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started