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Revolutionizing indoor air quality monitoring through IoT innovations: a comprehensive systematic review and bibliometric analysis

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Environmental science and Pollution Research 2024年第32期31卷 44463-44488页

作者： Tan, Huiyi Othman, Mohd Hafiz Dzarfan Kek, Hong Yee Chong, Wen Tong Nyakuma, Bemgba Bevan Wahab, Roswanira Abdul Teck, Gabriel Ling Hoh Wong, Keng Yinn Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Faculty of Mechanical Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Department of Mechanical Engineering Faculty of Engineering Universiti Malaya Kuala Lumpur50603 Malaysia Department of Chemical Sciences Faculty of Science and Computing Pen Resource University P. M. B Gombe State Gombe0198 Nigeria Department of Chemistry Faculty of Sciences Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Universiti Teknologi Malaysia Skudai Johor81310 Malaysia

Indoor air quality (IAQ) in the built environment is significantly influenced by particulate matter, volatile organic compounds, and air temperature. Recently, the Internet of Things (IoT) has been integrated to improve IAQ and safeguard human health, comfort, and productivity. This review seeks to highlight the potential of IoT integration for monitoring IAQ. Additionally, the paper details progress by researchers in developing IoT/mobile applications for IAQ monitoring, and their transformative impact in smart building, healthcare, predictive maintenance, and real-time data analysis systems. It also outlines the persistent challenges (e.g., data privacy, security, and user acceptability), hampering effective IoT implementation for IAQ monitoring. Lastly, the global developments and research landscape on IoT for IAQ monitoring were examined through bibliometric analysis (BA) of 106 publications indexed in Web of science from 2015 to 2022. BA revealed the most significant contributing countries are India and Portugal, while the top productive institutions and researchers are Instituto Politecnico da Guarda (10.37% of TP) and Marques Goncalo (15.09% of TP), respectively. Keyword analysis revealed four major research themes: IoT, pollution, monitoring, and health. Overall, this paper provides significant insights for identifying prospective collaborators, benchmark publications, strategic funding, and institutions for future IoT-IAQ researchers. Graphical Abstract: (Figure presented.). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： COVID-19

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WAEI: An Intelligent Chatbot for Helping Fighting the Pandemic Infodemic 1

WAEI: An Intelligent Chatbot for Helping Fighting the Pandem...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Almurtadha, Yahya Ghaleb, Mukhtar Alomari, Mohamed Ahmed Al-Balatah, Ibrahim Ahmed Faculty of Computers and Information Technology University of Tabuk Tabuk Saudi Arabia Faculty of Computing and Information Technology University of Bisha Bisha Saudi Arabia Universiti Teknikal Malaysia Melaka Melaka Malaysia Faculty of Science and Engineering Al-Hikma University Sana’a Yemen

ISBN: (纸本)9798331533557

The World Health Organization (WHO) began warning of a possible upcoming epidemic called monkeypox, while humanity is still suffering from the consequences of the latest epidemic. In addition to various health issues caused by the Covid-19 pandemic, an "infodemic" accompanied the virus that led to the spread of many fake news about the virus and possible medication treatments. This fake news led to the emergence of huge mass panic causing stress and anxiety and might lead to death. This paper proposes an intelligent Chatbot called WAEI (Arabic term means awareness in English) to increase the awareness of pandemic risks, methods of prevention, and precautionary measures. WAEI fight the infodemic by producing responses based on its knowledgebase that was formed from credible sources, namely the WHO. The Chatbot uses Natural Language Understanding (NLU) to infer its responses. 308 volunteers evaluated the proposed chatbot. The volunteers’ responses were statistically analyzed to measure whether the Chatbot is resourceful, coherent, and achieves user satisfaction. Precision, recall and F1 metrics shows improvement in accuracy, which reach 83% accuracy in responding to users’ inquiry. WAEI is of great value and has been proposed at the right time for the health sectors as it gives a good experience in using technology and smart systems to quickly handle infodemic effectively by providing necessary awareness for any potential foreseen diseases. © 2024 IEEE.

关键词： Chatbots

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ConceptX: A Framework for Latent Concept Analysis 37

ConceptX: A Framework for Latent Concept Analysis

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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Alam, Firoj Dalvi, Fahim Durrani, Nadir Sajjad, Hassan Khan, Abdul Rafae Xu, Jia Qatar Computing Research Institute HBKU Research Complex Qatar Faculty of Computer Science Dalhousie University Canada School of Engineering and Science Stevens Institute of Technology United States

ISBN: (纸本)9781577358800

The opacity of deep neural networks remains a challenge in deploying solutions where explanation is as important as precision. We present ConceptX, a human-in-the-loop framework for interpreting and annotating latent representational space in pre-trained Language Models (pLMs). We use an unsupervised method to discover concepts learned in these models and enable a graphical interface for humans to generate explanations for the concepts. To facilitate the process, we provide auto-annotations of the concepts (based on traditional linguistic ontologies). Such annotations enable development of a linguistic resource that directly represents latent concepts learned within deep NLP models. These include not just traditional linguistic concepts, but also task-specific or sensitive concepts (words grouped based on gender or religious connotation) that helps the annotators to mark bias in the model. The framework consists of two parts (i) concept discovery and (ii) annotation platform. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Linguistics

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A Creative Research in the Field of Urban Fire Detection 5

A Creative Research in the Field of Urban Fire Detection

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5th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Feng, Junming Wang, Ruixiang Xi, Chenyang Peng, Jiayu Harbin Institute of Technology Faculty of Computing Harbin China Harbin Institute of Technology School of Information Science and Engineering Harbin China Harbin Institute of Technology School of Software Harbin China

ISBN: (纸本)9798350373820

As the most common disaster in human daily production and life, fire is very likely to threaten people's life and property safety. In order to avoid fire, this paper designs and implements a fire detection system based on video and YOLOv5 model, and describes the improvement of YOLOv5 compared with the previous generation YOLO model. Collect fire images through the network, use image processing technology to enhance the data, make fire data set and divide the data set by setting aside method. Then the self-made fire data set is used to train the fire detection model based on YOLOv5 model, and the model is improved by adding transfer learning, multi-scale training and other technologies to improve the fire detection rate, and the corresponding weight files are obtained. Finally, the training method of the model and the ability of the model to detect fire are expounded, and the innovative application of the model in the field of fire detection is realized. © 2024 IEEE.

关键词： Fires

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Adaptive control systems for dual axis tracker using clear sky index and output power forecasting based on ML in overcast weather conditions

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Energy and AI 2024年第4期18卷 240-257页

作者： Nursultan Koshkarbay Saad Mekhilef Ahmet Saymbetov Nurzhigit Kuttybay Madiyar Nurgaliyev Gulbakhar Dosymbetova Sayat Orynbassar Evan Yershov Ainur Kapparova Batyrbek Zholamanov Askhat Bolatbek Faculty of Physics and Technology Al-Farabi Kazakh National University71 Al-FarabiAlmaty 050040Kazakhstan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVIC 3122Australia Power Electronics and Renewable Energy Research Laboratory Department of Electrical EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia

The use of artificial intelligence in renewable energy systems increases energy generation and improves energy system *** control system of many solar trackers is designed for maximum radiation power conditions and shows decent performance indicators,but during rapidly changing weather conditions or cloudy days,the performance of the solar trackers is reduced due to moving parts and low *** studies show that the horizontal configuration produces more energy with scattered solar radiation than solar tracking *** work shows the possibility of using solar tracking systems under different weather conditions and cloudy *** achieve the goals,a new adaptive control system for dual-axis solar trackers with astronomical tracking was developed,which differs from traditional controls in the use of horizontal configurations under certain weather *** assessment of spatio-temporal weather conditions was carried out using the Clear Sky Index(CSI)and was complemented by forecasting the panel’s power *** study found that at 0.4 CSI values,the horizontal configuration exhibits higher power output than solar tracking systems,providing the potential to use the threshold for adaptive *** developed system is more efficient by 18.3%,14.9%,and 10.01%than the horizontal configuration,single-axis,and dual-axis solar trackers.

关键词： Dual-axis and single-axis tracker Horizontal configuration Solar tracker Clear sky index Adaptive control Forecasting

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Non-Destructive Surface Roughness Analysis for Polymer-Based Products: Integrating Laser Speckle Contrast and Stylus Profilometry

Non-Destructive Surface Roughness Analysis for Polymer-Based...

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International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)

作者： Adam Jones Samuel Eurfyl Davies Kang Li Faculty of Computing Engineering and Science University of South Wales United Kingdom

ISBN: (数字)9798350362107

ISBN: (纸本)9798350362114

This study introduces a novel approach for measuring surface roughness in polymer-based samples using laser speckle photometry principles, offering potential for non-contact and non-destructive in-process measurements. A methodology for characterising surface roughness offline for polymer samples is outlined, utilising stylus profilometry, a technique not commonly employed in polymer manufacturing. Investigations into the reliability and stability of laser speckle on polymer-based products with various shape profiles were conducted, resulting in successful outcomes through mean intensity matching techniques. This enabled the correlation of surface roughness with two laser speckle statistical parameters: laser speckle contrast and binary digitization techniques. This research provides valuable insights for advancing surface roughness measurement techniques in polymer manufacturing processes.

关键词： Shape Surface emitting lasers Measurement by laser beam Speckle Laser stability Surface roughness Rough surfaces Manufacturing Polymers Surface treatment

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Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning

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Intelligent Automation & Soft computing 2023年第5期36卷 1915-1930页

作者： Rab Nawaz Bashir Imran Sarwar Bajwa Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel ABahaddad Khalid Ali Almarhabi Department of Computer Science COMSATS University IslamabadVehari CampusPakistan Department of Computer Science and IT Islamia University BahawalpurPakistan Department of Software Engineering Superior University Lahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be deﬁned by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.

关键词： Leaching fraction saline soil evapotranspiration machine learning calibrated evapotranspiration artiﬁcial intelligence blaney criddle method

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Multi-Criteria Decision-Making for Energy Management in Smart Homes Using Hybridized Neuro-Fuzzy Approach

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Distributed Generation and Alternative Energy Journal 2024年第1期39卷 83-109页

作者： Anbazhagu, U.V. Koti, Manjula Sanjay Muthukumaran, V. Geetha, V. Munrathnam, Meram Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology SRM Nagar Kattankulathur TN Chennai India Department of MCA Dayananda Sagar Academy of Technology and Management Bangalore560082 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur Campus 603 203 India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics Rajiv Gandhi University of Knowledge Technologies R.k.Valley Idupulapaya Andhra Pradesh Kadapa516330 India

The necessity for smart energy oversight solutions has arisen in response to the rising popularity of energy-efficient home automation and other energy-saving technologies. Optimizing smart home energy use using multi-criteria decision-making (MCDM) is a proven methodology. However, the procedure for making decisions and MCDM’s capacity to handle various criteria are typically limiting factors. Hybrid methods, which integrate multiple decision-making approaches like Fuzzy Logic (FL) and Modular Neural Networks (MNN), could potentially be able to circumvent these restrictions and boost energy management systems’ efficacy and precision. This investigation presents a hybrid Neuro-Fuzzy (H-NF) method for MCDM in regulating energy for smart homes by combining FL with an MNN. The suggested approach would optimize energy use in smart homes by considering several parameters, notably cost, ease of use, and environmental effects. In addition, this study aims to examine how the H-NF model fares in comparison to other methods of making important decisions in terms of several performance metrics. The suggested hybridized approach has the potential to deliver more precise and effective decision-making processes for energy management in smart homes, allowing users to optimize their energy consumption while preserving comfort and lowering environmental impact. © 2024 Taylor and Francis Inc.. All rights reserved.

关键词： Decision making

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DaC-GANSAEBF:Divide and Conquer-Generative Adversarial Network-Squeeze and Excitation-Based Framework for Spam Email Identification

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Computer Modeling in engineering & sciences 2025年第3期142卷 3181-3212页

作者： Tawfeeq Shawly Ahmed A.Alsheikhy Yahia Said Shaaban M.Shaaban Husam Lahza Aws I.Abu Eid Abdulrahman Alzahrani Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArar91431Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border UniversityArar73213Saudi Arabia Department of Information Technology College of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information and Communication Technology College of Computing StudiesArab Open UniversityKuwait BranchKuwait City13033Al-SafatState of Kuwait Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia

Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security *** spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data *** address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam *** framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual *** approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated *** model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the *** findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection *** framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.

关键词： Email spam fraud light dual attention squeeze and excitation divide and conquer-generative adversarial network-squeeze and excitation-based framework security

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Smart Walker With Return-To-User Functionality via Kalman Filter-Based Tracking

Smart Walker With Return-To-User Functionality via Kalman Fi...

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IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

作者： Isaac Asante Lau Bee Theng Mark Tee Kit Tsun Faculty of Engineering Computing and Science Swinburne University of Technology Kuching Malaysia

ISBN: (数字)9798350340204

ISBN: (纸本)9798350340211

This paper presents a smart walker designed to address mobility issues for individuals with various impairments. The prototype comes with autonomous and manual navigation options; it uses an NVIDIA Jetson Orin Nano with ROS 2 Humble, integrates sensors such as the Intel RealSense D455 camera for depth data and an MPU6050 IMU for orientation, and it is equipped with person-tracking algorithms for autonomous navigation, with face recognition to maintain focus on the target user. Commands are communicated between the Jetson Nano and Arduino Mega 2560, which controls motor functions and the mecanum wheels. The forward-looking aspect is that the prototype retrofits standard walkers for easier commercialisation and replication. The design addresses the need for dynamic obstacle detection, basic fall prevention, as well as return-to-user autonomous navigation – all of which are necessary for user independence and safety in various environments.

关键词： Industries Navigation Face recognition Prototypes Wheels Manuals Safety Kalman filters Older adults Autonomous robots

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