Analysis of the drivers and barriers influencing artificial intelligence for tackling climate change challenges DOI
Alireza Moghayedi, Kathy Michell, Bankole Awuzie

et al.

Smart and Sustainable Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

Purpose Facilities management (FM) organizations are pivotal in enhancing the resilience of buildings against climate change impacts. While existing research delves into adoption digital technologies by FM organizations, there exists a gap regarding specific utilization artificial intelligence (AI) to address challenges. This study aims investigate drivers and barriers influencing AI South African mitigating Design/methodology/approach focuses on Africa, developing nation grappling with change’s ramifications its infrastructure. Through combination systematic literature review an online questionnaire survey, data was collected from representatives 85 professionally registered Africa. Analysis methods employed include content analysis, Relative Importance Index (RII), Total Interpretative Structural Modeling (TISM). Findings The findings reveal that regulatory compliance responsible supply chain serve as critical for among organizations. Conversely, policy constraints Africa’s energy crisis emerge major combating challenges within sector. Originality/value contributes knowledge bridging understanding how utilized challenges, particularly context like aim inform policymakers fostering conducive environment harness built assets.

Language: Английский

Context-aware smart energy management system: A reinforcement learning and IoT-based framework for enhancing energy efficiency and thermal comfort in sustainable buildings DOI
Badr Saad Alotaibi

Energy and Buildings, Journal Year: 2025, Volume and Issue: 340, P. 115804 - 115804

Published: April 28, 2025

Language: Английский

Citations

0
A Meta-Survey on Intelligent Energy-Efficient Buildings DOI Creative Commons
Md Babul Islam, Antonio Guerrieri, Raffaele Gravina

et al.

Big Data and Cognitive Computing, Journal Year: 2024, Volume and Issue: 8(8), P. 83 - 83

Published: July 30, 2024

The rise of the Internet Things (IoT) has enabled development smart cities, intelligent buildings, and advanced industrial ecosystems. When IoT is matched with machine learning (ML), advantages resulting enhanced environments can span, for example, from energy optimization to security improvement comfort enhancement. Together, ML technologies are widely used in particular, reduce consumption create Intelligent Energy-Efficient Buildings (IEEBs). In IEEBs, models typically analyze predict various factors such as temperature, humidity, light, occupancy, human behavior aim optimizing building systems. literature, many review papers have been presented so far field IEEBs. Such mostly focus on specific subfields or a limited number papers. This paper presents systematic meta-survey, i.e., articles, that compares state art IEEBs using Prisma approach. more detail, our meta-survey aims give broader view, respect already published surveys, state-of-the-art IEEB field, investigating use supervised, unsupervised, semi-supervised, self-supervised variety IEEB-based scenarios. Moreover, compare surveys by answering five important research questions about definitions, architectures, methods/models used, datasets real implementations utilized, main challenges/research directions defined. provides insights useful both newcomers researchers who want learn methodologies IEEBs’ design implementation.

Language: Английский

Citations

3
Introducing Security Mechanisms in OpenFog-Compliant Smart Buildings DOI Open Access
Imanol Martín Toral, Isidro Calvo,

Eneko Villar

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(15), P. 2900 - 2900

Published: July 23, 2024

Designing smart building IoT applications is a complex task. It requires efficiently integrating broad number of heterogeneous, low-resource devices that adopt lightweight strategies. frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 standard, promotes use free open source (FOS) technologies and has been identified for in buildings. However, systems present vulnerabilities, which can put their integrity at risk. Adopting state-of-the-art security mechanisms this domain critical but not trivial. complicates design operation applications, increasing cost deployed systems. In addition, difficulties arise finding qualified cybersecurity personnel. OpenFog identifies requirements although it does describe clearly how implement them. This article presents scalable architecture, based on reference provide by buildings different sizes. adopts FOS over low-cost devices. Moreover, guidelines developers create secure even experts. also proposes selection layers achieve dimensions defined X.805 ITU-T recommendation. A proof-of-concept Indoor Environment Quality (IEQ) system, nodes, was Faculty Engineering Vitoria-Gasteiz illustrate implementation presented approach. The IEQ system analyzed using software tools frequently used find vulnerabilities such encryption, certificates, protocol network partitioning/configuration OpenFog-based architecture improves security.

Language: Английский

Citations

2
Analyzing and Forecasting Laboratory Energy Consumption Patterns Using Autoregressive Integrated Moving Average Models DOI Open Access
Yitong Niu,

Xiongjie Jia,

Chee Keong Lee

et al.

Laboratories, Journal Year: 2024, Volume and Issue: 2(1), P. 2 - 2

Published: Dec. 30, 2024

This study applied ARIMA modeling to analyze the energy consumption patterns of laboratory equipment over one month, focusing on enhancing management in laboratory. By explicitly examining AC and DC equipment, this obtained detailed daily operating cycles periods inactivity. Advanced differencing diagnostic checks were used verify model accuracy white noise characteristics through enhanced Dickey–Fuller testing residual analysis. The results demonstrate model’s predicting consumption, providing valuable insights into use model. highlights adaptability validity environments, contributing more competent practices.

Language: Английский

Citations

2
Electricity Production Prediction by Microsoft Azure Machine Learning Service and Python User Blocks DOI
Vladyslav Pliuhin, Yevgen Tsegelnyk, Maria Sukhonos

et al.

Advances in environmental engineering and green technologies book series, Journal Year: 2024, Volume and Issue: unknown, P. 227 - 267

Published: May 1, 2024

In this chapter, the forecasting of electricity consumption and production is conducted by analyzing indicators from previous years. The problem addressed using machine learning within Microsoft Azure Machine Learning Studio. outcome an independent service integrated into Excel, enabling for specified dates. Excel user interface developed Visual Basic Applications. Python was used to create blocks modifying input data pools forming graphical dependencies, seamlessly original modules An additional aspect forecast results involves evaluating quality predicted indicators. materials chapter were sourced with support Ukraine's National Power Company UKRENERGO.

Language: Английский

Citations

1
Analysis of the drivers and barriers influencing artificial intelligence for tackling climate change challenges DOI
Alireza Moghayedi, Kathy Michell, Bankole Awuzie

et al.

Smart and Sustainable Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

Purpose Facilities management (FM) organizations are pivotal in enhancing the resilience of buildings against climate change impacts. While existing research delves into adoption digital technologies by FM organizations, there exists a gap regarding specific utilization artificial intelligence (AI) to address challenges. This study aims investigate drivers and barriers influencing AI South African mitigating Design/methodology/approach focuses on Africa, developing nation grappling with change’s ramifications its infrastructure. Through combination systematic literature review an online questionnaire survey, data was collected from representatives 85 professionally registered Africa. Analysis methods employed include content analysis, Relative Importance Index (RII), Total Interpretative Structural Modeling (TISM). Findings The findings reveal that regulatory compliance responsible supply chain serve as critical for among organizations. Conversely, policy constraints Africa’s energy crisis emerge major combating challenges within sector. Originality/value contributes knowledge bridging understanding how utilized challenges, particularly context like aim inform policymakers fostering conducive environment harness built assets.

Language: Английский

Citations

0