Integrating Artificial Intelligence in Construction Management: Improving Project Efficiency and Cost-effectiveness

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(2), P. 639 - 647

Published: March 26, 2024

The construction industry faces challenges such as project complexity, delays, and communication issues. Leveraging AI, particularly through data analysis, predictive analytics, machine learning, addresses these by optimizing planning, scheduling, risk management. This paper outlines strategies for AI integration, including collection, learning algorithms, cloud computing. Case studies highlight successful implementations, showcasing benefits increased efficiency, cost savings, improved safety. However, like security workforce acceptance must be considered. abstract concludes discussing future trends encouraging the to embrace enhanced outcomes.

Language: Английский

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A Contactless Multi-Modal Sensing Approach for Material Assessment and Recovery in Building Deconstruction

Sustainability, Journal Year: 2025, Volume and Issue: 17(2), P. 585 - 585

Published: Jan. 14, 2025

As material scarcity and environmental concerns grow, reuse waste reduction are gaining attention based on their potential to reduce carbon emissions promote net-zero buildings. This study develops an innovative approach that combines multi-modal sensing technologies with machine learning enable contactless assessment of in situ building materials for potential. By integrating thermal imaging, red, green, blue (RGB) cameras, as well depth sensors, the system analyzes conditions reveals hidden geometries within existing enhances understanding by analyzing materials, including compositions, histories, assemblies. A case drywall deconstruction demonstrates these can effectively guide process, potentially reducing costs significantly. The findings highlight feasible scenarios offer insights into improving techniques through automated feedback visualization cut lines fastener positions. research indicates methods technically viable, economically advantageous, environmentally beneficial. Serving initial step toward novel view classify this lays a foundation future research, promoting sustainable construction practices optimize negative impact.

Language: Английский

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Performance Evaluation of Predicting IoT Malicious Nodes Using Machine Learning Classification Algorithms

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2024, Volume and Issue: 10(3)

Published: Aug. 6, 2024

The prediction of malicious nodes in Internet Things (IoT) networks is crucial for enhancing network security. Malicious can significantly impact performance across various scenarios. Machine learning (ML) classification algorithms provide binary outcomes ("yes" or "no") to accurately identify these nodes. This study implements classifier address the problem node classification, using “SensorNetGuard” dataset. dataset, comprising 10,000 records with 21 features, was preprocessed and used train multiple ML models, including Logistic Regression, Decision Tree, Naive Bayes, K-Nearest Neighbors (KNN), Support Vector (SVM). Performance evaluation models followed workflow, utilizing Python libraries such as scikit-learn, Seaborn, Matplotlib, Pandas. results indicated that Bayes outperformed others an accuracy 98.1%. paper demonstrates effectiveness classifiers detecting IoT networks, providing a robust predictive model real-time application. dataset available on IEEE data port Kaggle platform.

Language: Английский

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A Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle

Buildings, Journal Year: 2024, Volume and Issue: 14(7), P. 2137 - 2137

Published: July 11, 2024

Buildings significantly contribute to global energy consumption and greenhouse gas emissions. This systematic literature review explores the potential of artificial intelegence (AI) enhance sustainability throughout a building’s lifecycle. The identifies AI technologies applicable sustainable building practices, examines their influence, analyses implementation challenges. findings reveal AI’s capabilities in optimising efficiency, enabling predictive maintenance, aiding design simulation. Advanced machine learning algorithms facilitate data-driven analysis, while digital twins provide real-time insights for decision-making. also barriers adoption, including cost concerns, data security risks, While offers innovative solutions optimisation environmentally conscious addressing technical practical challenges is crucial its successful integration practices.

Language: Английский

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ASSESSING THE IMPACT OF CLIMATE CHANGE ON HVAC SYSTEM DESIGN AND PROJECT MANAGEMENT

International Journal of Applied Research in Social Sciences, Journal Year: 2024, Volume and Issue: 6(3), P. 173 - 184

Published: March 8, 2024

In the face of rapidly changing climate conditions, field HVAC (Heating, Ventilation, and Air Conditioning) system design project management is confronted with a myriad challenges. This review delves into critical importance assessing impact change on these aspects highlights key considerations for industry professionals. Climate poses multifaceted challenges to management, primarily due its influence temperature patterns, extreme weather events, evolving energy demands. Rising global temperatures necessitate innovative approaches cooling systems, focus efficiency sustainable practices. Furthermore, increasing frequency intensity heatwaves cold spells demand systems that can adapt dynamically fluctuating environmental conditions. The underscores significance incorporating projections future-proofing strategies design. By leveraging predictive modeling techniques data, engineers optimize performance, minimize consumption, enhance indoor air quality amidst climatic Additionally, integration renewable sources such as solar geothermal technologies explored means mitigate reduce reliance fossil fuels. Effective in context entails proactive risk assessment mitigation strategies. Project managers must anticipate potential disruptions arising from supply chain disruptions, regulatory changes influenced by policies. Adopting adaptive methodologies enables stakeholders respond swiftly emerging ensure resilience uncertainties. imperative embrace approach towards management. prioritizing resilience, sustainability, innovation, professionals navigate complexities posed contribute more resilient built environment. Keywords: Change, HVAC, Management, System Design, Review.

Language: Английский

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Intelligent Manufacturing through Generative Artificial Intelligence, Such as ChatGPT or Bard

SSRN Electronic Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

This research paper explores the transformative possibilities arising from integration of ChatGPT, an advanced language model, into domain intelligent manufacturing. In face rapid changes in manufacturing landscape, there is increasing demand for adaptive and systems to elevate efficiency, productivity, decision-making processes. study investigates incorporation ChatGPT's or Bard cutting-edge natural processing capabilities various forefront aspects establish a novel paradigm The ChatGPT processes presents versatile approach tackle challenges seize opportunities within modern production systems. A pivotal aspect this lies augmenting human-machine collaboration factory. understanding facilitates seamless communication between human operators automated systems, fostering more intuitive responsive environment. Additionally, delves utilization predictive maintenance facilities. Through analysis historical data real-time information, can provide insights potential equipment failures, enabling proactive strategies that mitigate downtime optimize resource utilization. also application supply chain management. model's capacity process vast amounts textual contributes improved forecasting, inventory optimization, risk results resilient agile ecosystem capable adapting dynamic market conditions. Furthermore, role quality control defect detection. model analyze intricate patterns data, identifying anomalies defects with high degree accuracy. Integrating assurance ensures higher product quality, reducing waste, enhancing overall customer satisfaction. findings highlight revolutionize processes, propelling industry towards greater adaptability, competitiveness rapidly evolving global market.

Language: Английский

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Contribution of ChatGPT and Similar Generative Artificial Intelligence for Enhanced Climate Change Mitigation Strategies

SSRN Electronic Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

The urgent acceleration of climate change necessitates the development innovative and adaptive mitigation strategies. This study investigates how ChatGPT or Bard, an advanced language model, enhances efforts to mitigate change. By leveraging natural processing machine learning, facilitates improved communication, collaboration, decision-making among stakeholders, thereby accelerating implementation paper begins by examining context change, emphasizing need for robust measures. It underscores limitations traditional approaches introduces transformative potential integrating into action frameworks. model's capacity analyze extensive datasets generate human-like text allows it comprehend intricate science, distill key insights, communicate them effectively. research identifies strategies that benefit from ChatGPT's intervention. One such strategy involves optimizing deployment renewable energy. assists in identifying optimal locations energy infrastructure, considering geographical climatic factors. Additionally, model aids developing sophisticated management systems, enhancing efficiency reliability sources. In sustainable agriculture, contributes providing real-time data analysis precision farming. helps farmers optimize resource utilization, minimize environmental impact, adopt climate-resilient agricultural practices. Moreover, formulating policies promote land use forest conservation. also explores role resilience through risk assessment adaptation planning. analyzing data, vulnerable regions targeted infrastructure resilience, disaster preparedness, community engagement. Furthermore, discusses fostering global collaboration. cross-border information exchange, knowledge sharing, formulation unified policies. collaborative approach is essential addressing transboundary nature achieving international goals. harnessing capabilities, stakeholders can unlock new dimensions innovation, paving way a more resilient future.

Language: Английский

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Application of IoT and Sensor Technologies in Environmental Monitoring

Published: April 27, 2025

The increasing environmental challenges, such as pollution, climate change, and resource depletion, highlighted the need for efficient real-time monitoring solutions. Traditional methods often lack accuracy, scalability, automation. advancement of Internet Things (IoT) sensor technologies has showed innovative approaches tracking parameters like air quality, water temperature variations. These smart systems authorize continuous data collection, analysis, automated responses to risks. This study explores role IoT in monitoring, discussing its benefits, future potential.

Language: Английский

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Economic, Policy, Social, and Regulatory Aspects of AI-Driven Smart Buildings

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 111666 - 111666

Published: Dec. 1, 2024

Language: Английский

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Enhancing water and air pollution monitoring and control through ChatGPT and similar generative artificial intelligence implementation

SSRN Electronic Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

This research delves into the utilization of advanced artificial intelligence (AI), specifically ChatGPT or Bard, to improve strategies for monitoring and controlling water air pollution. Given escalating concerns surrounding environmental degradation its repercussions on public health, there is a pressing demand innovative pollution management techniques. investigation centers harnessing capabilities ChatGPT, an language model, address real-time data analysis, decision-making, engagement challenges within realm quality. Incorporating cutting-edge methods in monitoring, such as sensor networks, satellite imagery, IoT devices, this aims obtain comprehensive understanding dynamics. Nevertheless, substantial volume presents processing extracting meaningful insights. employed intelligent tool proficient comprehending natural queries delivering insightful analyses. integration streamlines interpretation intricate sets, enabling swift decision-making control authorities. Moreover, assumes pivotal role by serving user-friendly interface disseminating information levels, regulatory measures, preventive actions. Through interactive conversations, it enhances communication between agencies general public, cultivating awareness encouraging participation initiatives. paper underscores significance collaborative human-AI approach tackling multifaceted The also ethical considerations associated with AI-driven emphasizing importance responsible AI implementation. As technologies progress, proposed framework contribute ongoing discourse sustainable involvement. By synergizing state-of-the-art techniques, seeks offer efficacious solution advancing contemporary landscape.

Language: Английский

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