Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildings

Energy and Buildings, Journal Year: 2023, Volume and Issue: 284, P. 112851 - 112851

Published: Feb. 10, 2023

Language: Английский

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Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Sensors, Journal Year: 2023, Volume and Issue: 23(7), P. 3752 - 3752

Published: April 5, 2023

As the most popular technologies of 21st century, artificial intelligence (AI) and internet things (IoT) are effective paradigms that have played a vital role in transforming agricultural industry during pandemic. The convergence AI IoT has sparked recent wave interest (AIoT). An system provides data flow to techniques for integration interpretation as well performance automatic image analysis prediction. adoption AIoT technology significantly transforms traditional agriculture scenario by addressing numerous challenges, including pest management post-harvest issues. Although is an essential driving force smart agriculture, there still some barriers must be overcome. In this paper, systematic literature review presented highlight current progress, its applications, advantages. concept, from devices systems techniques, discussed. increasing trend article publication regarding topics based on database search process. Lastly, challenges modern also

Language: Английский

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Privacy-Preserving Security of IoT Networks: A Comparative Analysis of Methods and Applications

Cyber Security and Applications, Journal Year: 2025, Volume and Issue: unknown, P. 100084 - 100084

Published: Jan. 1, 2025

Language: Английский

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Harnessing the Internet of Behavior (IoB) for Food Safety and Quality

Advances in psychology, mental health, and behavioral studies (APMHBS) book series, Journal Year: 2025, Volume and Issue: unknown, P. 271 - 300

Published: Jan. 22, 2025

In this chapter, we propose a conceptual model to utilize the Internet of Behavior (IoB) for improving food safety and quality. This chapter aims at providing an exhaustive insight on what can cannot be done with behavioral data increase protocols, in other words constructive debrief theoretical foundations potential applications surrounding IoB. By means literature reviews models, presents how IoB effectively enhance quality assurance capabilities while confronting several issues view creating emerging research area academia as well supporting industry best practices

Language: Английский

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A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors

Sensors, Journal Year: 2025, Volume and Issue: 25(4), P. 1006 - 1006

Published: Feb. 8, 2025

Integrating machine learning algorithms leveraged by advanced data acquisition systems is emerging as a pivotal approach in predictive maintenance. This paper presents the deployment of such an integration on industrial air compressor unit. research combines updated concepts from Internet Things, learning, multi-sensor collection, structured mining, and cloud-based analysis. To this end, temperature, pressure, flow rate were acquired sensors contact with compressor. The observed sent to Structured Query Language database. Then, Linear Regression model was fitted training data, optimized stored for real-time inference. Afterward, passed through model, if exceeded determined threshold, warning email operator. Adopting Things enhances surveillance specialists, decreasing failure damage probabilities. achieved 98% accuracy Mean Squared Error metric our regression model. By analyzing gathered implemented system demonstrates capabilities predict potential equipment failures promising accuracy, facilitating shift reactive proactive maintenance strategies. findings reveal substantial improvements efficiency, uptime, cost savings.

Language: Английский

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A Step toward Next-Generation Advancements in the Internet of Things Technologies

Sensors, Journal Year: 2022, Volume and Issue: 22(20), P. 8072 - 8072

Published: Oct. 21, 2022

The Internet of Things (IoT) devices generate a large amount data over networks; therefore, the efficiency, complexity, interfaces, dynamics, robustness, and interaction need to be re-examined on scale. This phenomenon will lead seamless network connectivity capability provide support for IoT. traditional IoT is not enough support. Therefore, we designed this study systematic analysis next-generation advancements in We propose catalog that covers most recent advances An overview from perspectives big data, science, science disciplines also connecting technologies given. highlight conceptual view IoT, key concepts, growth, trends. discuss importance integration along with applications such as artificial intelligence, machine learning, blockchain, federated etc. Finally, various challenges issues architecture, integration, provenance, important cloud edge computing, article aid readers other researchers an understanding IoT's developments tell how they apply real world.

Language: Английский

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Innovative Approaches in Hotel Management: Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) to Enhance Operational Efficiency and Sustainability

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7279 - 7279

Published: Aug. 24, 2024

The integration of artificial intelligence (AI) and the internet things (IoT) is bringing revolutionary changes to hospitality industry, enabling advancement sustainable practices. This research, conducted using a quantitative methodology through surveys hotel managers in Republic Serbia, examines perceived contribution AI IoT technologies operational efficiency business sustainability. Data analysis structural equation modeling (SEM) has determined that significantly improve efficiency, which positively impacts results indicate these not only optimizes resource management but also contributes achieving global sustainability goals, including reducing carbon footprint preserving environment. study provides empirical evidence synergistic effects on sustainability, offering practical recommendations for proposing an innovative framework enhancing It highlights need future research focus long-term address challenges related data privacy implementation costs.

Language: Английский

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Analysis on Various Aspects of Internet of Nano-Things (IoNT), Its Integration in Machine Learning, and Its Diverse Applications

Advances in chemical and materials engineering book series, Journal Year: 2024, Volume and Issue: unknown, P. 297 - 315

Published: March 1, 2024

The internet of things (IoT) concept has long been regarded as a crucial driver the Fourth Industrial Revolution, having potential to change way we live. However, incorporation nanotechnology promises increase its impact significantly more. proliferation intelligent settings implies application interconnection and use internet. As result, emerged. nano (IoNT) is made possible by development IoT idea, new communication networks paradigm based on IoT, that is, capable interconnecting nano-scale devices via existing networks. arose from connecting these with nano-things network nanoconnected devices, objects, or organisms unique IDs wirelessly transport data cloud over computer cellular network. Data delivery, caching, energy usage are three most important topics in IoNT today.

Language: Английский

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Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT

Electronics, Journal Year: 2023, Volume and Issue: 12(4), P. 1034 - 1034

Published: Feb. 19, 2023

Resource management is a key issue that needs to be addressed in the future smart Internet of Things (IoT). This paper focuses on Federated Learning (FL)-based resource mechanism IoT. It incorporates blockchain technology guarantee security FL model parameters exchange. We propose an IoT framework incorporating and federated learning technologies; then, specific FL-based with trust assurance algorithm given. use Support Vector Machine (SVM) classifier detect malicious nodes order avoid impact performance algorithm. Finally, we perform simulation verify SVM classification effect proposed performance. The results show SVM-based node identification accuracy can acceptable. Moreover, obtains better when are excluded from selected participant.

Language: Английский

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Use of IoT with Deep Learning for Classification of Environment Sounds and Detection of Gases

Computers, Journal Year: 2025, Volume and Issue: 14(2), P. 33 - 33

Published: Jan. 22, 2025

The need for safe and healthy air quality has become critical as urbanization industrialization increase, leading to health risks environmental concerns. Gas leaks, particularly of gases like carbon monoxide, methane, liquefied petroleum gas (LPG), pose significant dangers due their flammability toxicity. LPG, widely used in residential industrial settings, is especially hazardous because it colorless, odorless, highly flammable, making undetected leaks an explosion risk. To mitigate these dangers, modern detection systems employ sensors, microcontrollers, real-time monitoring quickly identify dangerous levels. This study introduces IoT-based system designed comprehensive monitoring, with a focus on detecting LPG butane leaks. Using sensors the MQ6 detection, MQ135 quality, DHT11 temperature humidity, system, managed by Arduino Mega, collects data sends ThingSpeak platform analysis visualization. In cases elevated levels, triggers alarm notifies user through IFTTT. Additionally, includes microphone CNN model analyzing audio data, enabling thorough assessment identifying specific sounds related ongoing activities, reaching accuracy 96%.

Language: Английский

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