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Journal articles on the topic 'AI in Smart Devices'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Journal, IJSREM. "Speech Recognition for Smart AI Devices." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 02 (2024): 1–10. http://dx.doi.org/10.55041/ijsrem28347.

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This article looks at the progress, challenges and future directions in the field of speech recognition for intelligent AI devices. Speech recognition technology has made significant progress over the years, enabling seamless interactions between humans and artificial intelligence. This article provides an in-depth analysis of modern speech recognition techniques used in smart AI devices and the potential applications and limitations of the technology. It also discusses the current challenges faced by developers and researchers and suggests possible solutions to overcome them. Keywords-Natural

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Wang, Yuhao. "Survey on Smart Wearable Devices: What Can AI Affect." Applied and Computational Engineering 116, no. 1 (2024): 148–53. https://doi.org/10.54254/2755-2721/2025.20431.

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In the modern era, as smartphone penetration is approaching saturation, wearable mobile devices have emerged as a significant technological trend. This article focuses on smart wearable devices and explores the critical role of artificial intelligence (AI) in their evolution. It analyzes their development history, technical characteristics, application scenarios, and future directions. By reviewing relevant research, it summarizes the application achievements and challenges of AI in smart wearable devices, such as in the fields of healthcare and education, as well as the data collection and al

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Wu, Jun Da, and Dong Min Lee. "A Study on the Design and Usability of AI Speaker Products : Focused on China's Market Environment and Users." Institute of Art & Design Research 27, no. 1 (2024): 219–31. http://dx.doi.org/10.59386/jadr.2024.27.1.219.

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This study highlights the potential of AI technology as a key driver of the Fourth Industrial Revolution, particukarly in transformig consumer habits around audio devices and creating interconnected smart home environments. It explores how AI can enhance user experience and human-machine interaction in product design, increasing the convenience and appeal of electronic audio devices. The paper also analyzes the impact of AI on product optimization, innovation, and market competitiveness, providing insights into the future of the smart audio device industry.

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S, Sandeep, Halashankar N. Patil, Arunkumar HS, Yathish S, and Prof Sandeep K V. "Review Paper on Energy Management for Home Automation Using AI." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (2022): 2050–51. http://dx.doi.org/10.22214/ijraset.2022.41059.

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Abstract: The smart energy management system was developed with the ability to record, store, and process power consumption data for all major home and industrial devices. Artificial intelligence technologies such as decision making and XG Boost have made advances in power electronics and energy engineering. These technologies provide powerful tools for designing, simulating, controlling, estimating, and fault diagnostic control of modern smart grids and renewable energy systems. AI technology has evolved rapidly over the past few decades, and its applications in modern industrial systems are

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Adebunmi Okechukwu Adewusi, Njideka Rita Chiekezie, and Nsisong Louis Eyo-Udo. "The role of AI in enhancing cybersecurity for smart farms." World Journal of Advanced Research and Reviews 15, no. 3 (2022): 501–12. http://dx.doi.org/10.30574/wjarr.2022.15.3.0889.

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The integration of advanced technologies into agriculture has given rise to smart farms, which leverage Internet of Things (IoT) devices, sensors, data management systems, and automation to optimize farming operations. However, the increasing digitization of agriculture introduces significant cybersecurity challenges, including vulnerabilities in IoT devices, data breaches, and threats to automated systems. Addressing these challenges is crucial to ensuring the security, efficiency, and sustainability of smart farms. Artificial Intelligence (AI) has emerged as a pivotal technology in enhancing

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Jyoti Bolannavar and Dr. Sumati Ramakrishna Gowda. "Smart Security : A Comprehensive Exploration of AI and IoT in Cybersecurity." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 635–40. http://dx.doi.org/10.32628/cseit2410447.

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This paper investigates the transformative roles of Artificial Intelligence (AI) and the Internet of Things (IoT) in cybersecurity, especially as the complexity and connectivity of digital networks intensify. The rapid adoption of IoT devices in industries and homes alike has significantly broadened the cyber threat landscape, introducing countless points of vulnerability. Cybercriminals now target the vast and often unsecured data generated by IoT devices, exploiting weak access controls, outdated software, and inadequate encryption. In response, AI has become a critical tool in modern cybers

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Seng, Kah Phooi, Li-Minn Ang, Eno Peter, and Anthony Mmonyi. "Machine Learning and AI Technologies for Smart Wearables." Electronics 12, no. 7 (2023): 1509. http://dx.doi.org/10.3390/electronics12071509.

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The recent progress in computational, communications, and artificial intelligence (AI) technologies, and the widespread availability of smartphones together with the growing trends in multimedia data and edge computation devices have led to new models and paradigms for wearable devices. This paper presents a comprehensive survey and classification of smart wearables and research prototypes using machine learning and AI technologies. The paper aims to survey these new paradigms for machine learning and AI for wearables from various technological perspectives which have emerged, including: (1) s

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Rajendran, Bipin. "Building a Smart and Green AI." Electrochemical Society Interface 32, no. 1 (2023): 47–48. http://dx.doi.org/10.1149/2.f09231if.

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How do we design cognitive computing systems that not only deliver well-calibrated and trustworthy decisions, but can also be deployed in the field, are capable of adapting or learning the features of unseen input streams in a secure manner, and operate within the energy budgets of battery-operated devices?

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Mugalakhod, Miss Sneha, and Miss Shweta M. Nirmanik. "AI Driven Smart Homes Energy Efficiency and Model." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 461–65. http://dx.doi.org/10.22214/ijraset.2022.45266.

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Abstract: Artificial intelligence (AI) has received immense attention from the research community and the industry, leading to AI being adopted in many real-world applications. The growing trend of deploying AI has dramatically changed the ergonomics of modern-day practices in many realms, including smart homes, healthcare, insurance, investment and banking, social services, infrastructure, and marketing. A smart home, often referred to as an intelligent home, comprises smart technologies supported by AI. Smart home has its applications in household appliances, home safety and security, lighti

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Guo, X., Z. Shen, X. Teng, and Z. Zhao. "Using virtual reality (VR) simulation to help developing a smart meeting space with AI Product to support moderator." IOP Conference Series: Materials Science and Engineering 1212, no. 1 (2022): 012005. http://dx.doi.org/10.1088/1757-899x/1212/1/012005.

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Abstract Smart building has a pivotal role in promoting the industrialization of buildings. Meeting room is a common type of public space. Developing a smart meeting space can play an important role in addressing the issue of research on smart building. In this paper, we develop a smart meeting space with AI product to support moderator. We create 3D model of the meeting room and import it into VR headset to having an experiment. 20 participants are engaged to answer questionnaire and have interview. The results of this study show that most of the participants think the meeting space we develo

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Mahesh, K. S. "AI Powered Smart Vision Calculator." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 3117–22. https://doi.org/10.22214/ijraset.2025.70869.

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The AI Powered Smart Vision Calculator is a gesture-based system developed to enhance mathematical problem-solving without the use of traditional input devices. It employs real-time hand tracking using MediaPipe and OpenCV to recognize user gestures, which are then interpreted into mathematical symbols through a fine-tuned Gemini-2B model implemented in TensorFlow. The front-end interface enables users to draw, submit, and solve equations through intuitive hand movements in the air. This system aims to improve accessibility, support educational engagement, and promote a natural mode of human-c

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Bi, Siguo, Cong Wang, Jilong Zhang, et al. "A Survey on Artificial Intelligence Aided Internet-of-Things Technologies in Emerging Smart Libraries." Sensors 22, no. 8 (2022): 2991. http://dx.doi.org/10.3390/s22082991.

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With the boom in artificial intelligence (AI) and Internet-of-Things (IoT), thousands of smart devices are interconnected with each other and deeply applied into human society. This prosperity has significantly improved public service and management, which were traditionally based on manual work. As a notable scenario, librarianship has embraced an era of “Smart Libraries” enabled by AI and IoT. Unlike existing surveys, our work comprehensively overviews the AI- and IoT-based technologies in three fundamental aspects: smart service, smart sustainability, and smart security. We then further hig

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Ciampi, Luca, Claudio Gennaro, Fabio Carrara, Fabrizio Falchi, Claudio Vairo, and Giuseppe Amato. "Multi-Camera Vehicle Counting Using Edge-AI." Expert Systems with Applications 207 (June 24, 2022): 117929. https://doi.org/10.5281/zenodo.8326476.

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This paper presents a novel solution to automatically count vehicles in a parking lot using images captured by smart cameras. Unlike most of the literature on this task, which focuses on the analysis of <em>single</em> images, this paper proposes the use of multiple visual sources to monitor a wider parking area from different perspectives. The proposed multi-camera system is capable of automatically estimating the number of cars present in the <em>entire</em> parking lot directly on board the edge devices. It comprises an on-device deep learning-based detector that locates and counts the vehi

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Dimitrov, Dimitar, and Iliyan Iliev. "THE RISK OF PERSONAL SMART DEVICES IN THE OPERATIONAL SECURITY FOR MILITARY BASES, PERSONNEL AND MISSIONS." ENVIRONMENT. TECHNOLOGY. RESOURCES. Proceedings of the International Scientific and Practical Conference 2 (June 8, 2025): 99–106. https://doi.org/10.17770/etr2025vol2.8616.

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The increasing integration of personal smart devices into military operations has significantly expanded the attack surface, introducing critical security vulnerabilities. This paper explores how smart devices can compromise operational security (OPSEC) through unauthorized data leaks, cyber exploitation, and geolocation tracking. It examines real-world incidents, including security breaches during the Russian-Ukrainian conflict and the exposure of military bases via fitness tracking applications. Additionally, the study analyses adversarial tactics that leverage AI-driven OSINT and behavioura

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Prof., Ashmita Ghongade Purnima Uprade Nandini Satghare Madhavi Moon Poonam Lengure Karan Raut. "AI & IoT Based Electronic Department System." International Journal of Advanced Innovative Technology in Engineering 10, no. 2 (2025): 128–33. https://doi.org/10.5281/zenodo.15412929.

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The smart department system is a part of digital appliances that can be used across various systems. It typically integrates Internet of Things (IoT) and Artificial Intelligence technologies to enhance efficiency, automate processes, optimize decision-making, and improve overall departmental performance. The system connects various smart devices, sensors, and AI-driven analytics to collect and process data. A smart department system is an intelligent, automated solution designed to improve the efficiency and effectiveness of a department within an organization, business, or institution.

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K, Soundharya, Kavitha S, Velmurugan T, Vishwa S, and Srikanth S. G. S. "Smart Home Automation." Data Analytics and Artificial Intelligence 4, no. 2 (2024): 83–87. http://dx.doi.org/10.46632/daai/4/2/13.

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The Smart Home Concept responds to the increasing need for integrating smart appliances and systems within residential environments. It includes a growing array of devices, services, and applications designed to simplify daily tasks and enhance the quality of life. Utilizing various technologies and standards, numerous device suppliers offer a wide range of solutions, including meters, actuators, sensors, and micro systems, which are integrated into the home environment. This advanced system incorporates sensors, artificial intelligence, and machine learning algorithms to develop an intelligen

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Jain, Dr Prerna, Prof Nidhi Pateria, Prof Gulafsha Anjum, Ashwini Tiwari, and Ayush Tiwari. "Edge AI and On-Device Machine Learning For Real Time Processing." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 05 (2023): 8137–46. http://dx.doi.org/10.15680/ijircce.2024.1205364.

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Edge Artificial Intelligence (Edge AI) and on-device machine learning represent significant advancements in computing paradigms, enabling real-time data processing directly at the edge of the network. This approach minimizes the need for centralized cloud-based processing, thereby reducing latency, enhancing privacy, and improving operational efficiency. This paper provides a comprehensive review of Edge AI and on-device machine learning, focusing on their applications, challenges, and future directions. Key applications include smart home devices, healthcare monitoring, autonomous vehicles, a

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Bargavi, Dr S. K. Manju, Hashir Muhammed, Harish P.S., and Dhanush D. "Edge Computing and AI for Real-time Analytics in Smart Devices." Asian Journal of Basic Science & Research 07, no. 02 (2025): 01–09. https://doi.org/10.38177/ajbsr.2025.7201.

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Edge computing and artificial intelligence (AI) are transforming real-time data analytics in smart devices by enabling low-latency, efficient, and decentralized processing. Traditional cloud-based approaches introduce high latency, bandwidth constraints, and security risks, making them less viable for real-time applications. This research explores Edge AI architectures, optimization techniques, and their integration with IoT to enhance real-time decision-making in smart devices. We analyze various AI models, including lightweight neural networks, federated learning, and quantization techniques

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Choi, Eulyong, and Soonshik Suh. "Elementary School Teachers’ Perception Survey on Smart Device based Teaching & Learning and AI Education." Journal of Field-based Lesson Studies 4, no. 2 (2023): 79–100. http://dx.doi.org/10.22768/jfls.2023.4.2.79.

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This study aimed to investigate and analyze the perceptions of elementary school teachers regarding the use of smart devices in classrooms and AI education, in order to identify stable strategies for the successful implementation of AI education. The study surveyed and analyzed the satisfaction levels of smart device-based classroom activities, as well as the perceived usefulness, acceptance, and interest in AI education. Additionally, the study aimed to examine the influence of satisfaction levels with smart device-based classroom activities on the perceived usefulness, acceptance, and intere

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Naeem, Sajid, Abid Ali, Khalid Memon, Mohammed Bavluwala, UP Shinde, and AV Patil. "A review of flexible high-performance supercapacitors for the internet of things (IoT) and artificial intelligence (ai) applications." Energy and Thermofluids Engineering 3 (May 17, 2023): 1–9. http://dx.doi.org/10.38208/ete.v3.734.

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The Internet of Things (IoT) is a new area of modern technology today. Transportation, agriculture, healthcare, manufacturing, wearables, smart grid, energy-saving technologies, smart homes, smart management systems, and other fields of engineering, technology, and real-time management all have IoT applications. Moreover, artificial intelligence (AI) has broad applications in the car industry, surveillance, security, education, entertainment, gaming, e-commerce, portable gadgets, robotics, medicinal devices, etc. They require efficient energy to operate for an extended period. These devices ne

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Peng, Wei, Wei Gao, and Jiajia Liu. "AI-Enabled Massive Devices Multiple Access for Smart City." IEEE Internet of Things Journal 6, no. 5 (2019): 7623–34. http://dx.doi.org/10.1109/jiot.2019.2902448.

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Ronak, Italia. "An Analysis of the Role of Artificial Intelligence in Consumer Electronics." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 6, no. 2 (2020): 1–11. https://doi.org/10.5281/zenodo.14282163.

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Artificial Intelligence (AI) has emerged as a transformative force in consumer electronics, revolutionizing device functionality, user interfaces, and overall user experience. This paper explores the historical evolution of consumer electronics and the early integration of AI, highlighting the pivotal role of AI in automating processes and enabling personalization. Applications of AI, including autonomous devices, smart wearables, entertainment systems, and home automation, are discussed alongside the technologies underpinning these advancements, such as machine learning, IoT, and edge computi

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Alabdulatif, Abdulatif, Ibrahim Khalil, and Mohammad Saidur Rahman. "Security of Blockchain and AI-Empowered Smart Healthcare: Application-Based Analysis." Applied Sciences 12, no. 21 (2022): 11039. http://dx.doi.org/10.3390/app122111039.

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A smart device carries a great amount of sensitive patient data as it offers innovative and enhanced functionalities in the smart healthcare system. Moreover, the components of healthcare systems are interconnected via the Internet, bringing significant changes to the delivery of healthcare services to individuals. However, easy access to healthcare services and applications has given rise to severe risks and vulnerabilities that hamper the performance of a smart healthcare system. Moreover, a large number of heterogeneous devices accumulate data that vary in terms of size and formats, making

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Saini, Lakshit, Premla Sagar Mishra, and Ms Shobhana Dashrath Patil. "Enhancing Predictive Maintenance in Smart Homes Devices using AI/ML on Microcontrollers." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 10 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem37783.

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As more and more smart home gadgets pop up, keeping them running is key. Smart upkeep using AI and machine learning tricks, can spot device problems before they happen. But the usual cloud- based setups have some snags, like delays and privacy worries. This study looks into putting AI and machine learning models right inside the smart home gadgets' tiny computers. This lets them handle upkeep on the spot, in real-time. By tweaking these models to work with limited resources, the research hopes to cut down on device downtime and make them last longer. It's a hands-on way to do smart upkeep with

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Sai Teja Boppiniti. "NOVEL SMART CONTACT LENSES WITH EMBEDDED AI FOR PIONEERING CONTINUOUS HEALTH TRACKING AND DISEASE DETECTION." International Journal of Innovations in Engineering Research and Technology 11, no. 9 (2024): 1–17. http://dx.doi.org/10.26662/ijiert.v11i9.pp1-17.

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Smart contact lenses equipped with embedded artificial intelligence (AI) represent a groundbreaking advancement in continuous health monitoring and disease detection. This paper explores the development and application of smart contact lenses that integrate real-time data collection with sophisticated AI algorithms to monitor various health parameters. By incorporating sensors and AI processing units directly into the lenses, these devices can continuously measure and analyze biometric data such as glucose levels, intraocular pressure, and ocular health indicators. The embedded AI system proce

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Pooyandeh, Mitra, and Insoo Sohn. "Edge Network Optimization Based on AI Techniques: A Survey." Electronics 10, no. 22 (2021): 2830. http://dx.doi.org/10.3390/electronics10222830.

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The network edge is becoming a new solution for reducing latency and saving bandwidth in the Internet of Things (IoT) network. The goal of the network edge is to move computation from cloud servers to the edge of the network near the IoT devices. The network edge, which needs to make smart decisions with a high level of response time, needs intelligence processing based on artificial intelligence (AI). AI is becoming a key component in many edge devices, including cars, drones, robots, and smart IoT devices. This paper describes the role of AI in a network edge. Moreover, this paper elaborates

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Ashish, S. Gawali Rupali S. Kalokar Monali M. Jawanjal Tanushri S. Dharmik Gaurav H. Bakade Chinmayee S. Deotare Sushmit S. Gaikwad. "AI and IoT based Home Automation System." International Journal of Advanced Innovative Technology in Engineering 10, no. 2 (2025): 191–95. https://doi.org/10.5281/zenodo.15425539.

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This paper aims to develop a smart home automation system that enables users to control electronic devices using hand gestures. By leveraging computer vision and deep learning techniques, a webcam captures hand gestures, which are processed using a Convolutional Neural Network (CNN) model for real-time classification. The recognized gestures are then transmitted to an ESP8266 microcontroller via Wi-Fi, triggering the corresponding on/off commands for connected IoT devices. This system enhances touchless interaction, offering an intuitive and accessible solution for smart home automation, parti

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Rakhmadi Rahman, Achmad Haikal Fikri, and Kelsia Nelsia. "Integrasi Artificial Intelegent Berbasis Sistem Operasi Android pada Smart Home." Jurnal Penelitian Teknologi Informasi dan Sains 2, no. 2 (2024): 184–94. http://dx.doi.org/10.54066/jptis.v2i2.2198.

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This study explores the integration of Artificial Intelligence (AI) into smart home systems using the Android operating system to enhance security, privacy, efficiency, and user comfort. Key security measures include data encryption, robust authentication methods, sandboxing, and AI integration, specifically leveraging Google Assistant for improved privacy controls. Maintenance strategies for smart homes emphasize energy management, device condition monitoring, and enhanced safety features. AI adaptation to user habits enhances productivity and situational awareness, while Android's role in co

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Moorthi, Prof M. Narayana. "Class Room Ambience Measurement using Ai Technique." International Journal of Engineering and Advanced Technology 11, no. 6 (2022): 150–54. http://dx.doi.org/10.35940/ijeat.f3768.0811622.

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The word SMART is popular in everyday activities which is meant for city, road, vehicles and home through the integration of IOT (Internet of Things) and ICT (Information and Communication Technology). It is possible by using the above, our everyday activities can be monitored and recorded using advanced devices in our work environment. It is suggested to have such tools in the education institutes to have better classroom and lab infrastructure for teaching and learning environments. Now a day’s many technologies exist and our aim is to integrate all the existing and new technologies to devel

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Prof., M. Narayana Moorthi. "Class Room Ambience Measurement using Ai Technique." International Journal of Engineering and Advanced Technology (IJEAT) 11, no. 6 (2022): 150–53. https://doi.org/10.35940/ijeat.F3768.0811622.

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<strong>Abstract:</strong> The word SMART is popular in everyday activities which is meant for city, road, vehicles and home through the integration of IOT (Internet of Things) and ICT (Information and Communication Technology). It is possible by using the above, our everyday activities can be monitored and recorded using advanced devices in our work environment. It is suggested to have such tools in the education institutes to have better classroom and lab infrastructure for teaching and learning environments. Now a day’s many technologies exist and our aim is to integrate all the exist

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Jang, DaeSung, and JongChan Kim. "Generative AI-Driven Multimodal Interaction System Integrating Voice and Motion Recognition." International Journal on Advanced Science, Engineering and Information Technology 15, no. 2 (2025): 617–24. https://doi.org/10.18517/ijaseit.15.2.20945.

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This research proposes a two-way interactive algorithm based on voice and motion recognition using generative AI technology to overcome the limitations of existing systems limited to simple command recognition. Current voice and motion recognition technologies are essential in enabling interaction between smart devices and users to enhance user experience. Still, they are mainly limited to recognizing and executing prescribed commands, which do not meet the diverse and complex needs of users. To solve these problems, this research aims to develop a technology that fuses and integrates voice an

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Nechita, Luiza Camelia, Dana Tutunaru, Aurel Nechita, et al. "AI and Smart Devices in Cardio-Oncology: Advancements in Cardiotoxicity Prediction and Cardiovascular Monitoring." Diagnostics 15, no. 6 (2025): 787. https://doi.org/10.3390/diagnostics15060787.

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The increasing prevalence of cardiovascular complications in cancer patients due to cardiotoxic treatments has necessitated advanced monitoring and predictive solutions. Cardio-oncology is an evolving interdisciplinary field that addresses these challenges by integrating artificial intelligence (AI) and smart cardiac devices. This comprehensive review explores the integration of artificial intelligence (AI) and smart cardiac devices in cardio-oncology, highlighting their role in improving cardiovascular risk assessment and the early detection and real-time monitoring of cardiotoxicity. AI-driv

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Battistoni, Pietro, Marianna Di Gregorio, Marco Romano, Monica Sebillo, and Giuliana Vitiello. "TactCube: An Intelligent Device to ‘converse’ with Smart Environments." Sensors 22, no. 14 (2022): 5235. http://dx.doi.org/10.3390/s22145235.

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Ambient Intelligence is a vision of daily life in which intelligent devices interact with humans to make their lives easier, and the technology is invisible. Artificial Intelligence (AI) governs this smart environment and must interact with humans to best meet their needs and demands. Although voice assistants are very popular and efficient as conversational AI, under some conditions they cannot be used. Therefore, this work proposed a complementary tactile and tangible interface to converse with AI, creating new Tactile Signs. A prototype of TactCube, a wireless cube-shaped device that can in

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Campolo, Claudia, Giacomo Genovese, Antonio Iera, and Antonella Molinaro. "Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications." Journal of Sensor and Actuator Networks 10, no. 1 (2021): 13. http://dx.doi.org/10.3390/jsan10010013.

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Several Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories. Although the traditional approach is to deploy such compute-intensive algorithms into the centralized cloud, the recent proliferation of low-cost, AI-powered microcontrollers and consumer devices paves the way for having the intelligence pervasively spread along the cloud-to-things continuum. The

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Zhou, Tianqi, Jian Shen, Sai Ji, Yongjun Ren, and Leiming Yan. "Secure and Intelligent Energy Data Management Scheme for Smart IoT Devices." Wireless Communications and Mobile Computing 2020 (September 1, 2020): 1–11. http://dx.doi.org/10.1155/2020/8842885.

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The renewable energy plays an increasingly important role in many fields such as lighting, automobile, and electric power. In order to make full use of the renewable energy, various smart Internet of Thing (IoT) devices are deployed. However, in the field of energy management, the two-way mismatch between the demand and the supply of the renewable energy will greatly affect the efficiency of the renewable energy. In addition, the security threat of the energy data and the privacy leakage of the user may hinder the further development of smart IoT devices. Therefore, how to achieve consistency

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Jain, Rachit. "Voice AI Risk Signaling: Using Home Assistant Devices to Detect Undeclared Property Hazards." American Journal of Engineering and Technology 06, no. 05 (2024): 43–48. https://doi.org/10.37547/tajet/volume06issue05-06.

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With the increase in smart home adoption, voice-enabled devices like Amazon Alexa, Google Home, and Apple Siri are becoming increasingly abundant. Most of the new homes use these smart devices, and the old ones are upgrading to integrate these voice-enabled assistants. This paper explores a novel study for using voice data, with user consent, to identify the undeclared or non-reported risks within residential properties. By analyzing the speech using the natural language patterns, complaint frequency, and targeted keywords signals, we propose an Artificial Intelligence-based model to measure u

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Yang, Taehun, Sang-Hoon Lee, and Soochang Park. "AI-Aided Individual Emergency Detection System in Edge-Internet of Things Environments." Electronics 10, no. 19 (2021): 2374. http://dx.doi.org/10.3390/electronics10192374.

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Recently, many disasters have occurred in indoor places. In order to rescue or detect victims within disaster scenes, vital information regarding their existence and location is needed. To provide such information, some studies simply employ indoor positioning systems to identify each mobile device of victims. However, their schemes may be unreliable, since people sometimes drop their mobile devices or put them on a desk. In other words, their methods may find a mobile device, not a victim. To solve this problem, this paper proposes a novel individual monitoring system based on edge intelligen

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Sundaram, Karthik Trichur. "Digital Transformation with AI/ML & Cybersecurity." International Journal of Computer Science and Mobile Computing 11, no. 11 (2022): 1–3. http://dx.doi.org/10.47760/ijcsmc.2022.v11i11.001.

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Artificial Intelligence (AI) and Machine Learning (ML) have impacted the manufacturing industry, especially in the industry 4.0 paradigm. It encourages the usage of smart devices, sensors, and machines for production. Moreover, AI techniques and ML algorithms give predictive insights into various manufacturing tasks, such as predictive maintenance, continuous inspection, process optimization, quality improvement, and more. However, there are many open concerns and challenges regarding cybersecurity in smart manufacturing.

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Choudhary, Sagar, Vijitha S, Dokku Durga Bhavani, Bhuvaneswari N, Mohit Tiwari, and Subburam S. "Edge AI Deploying Artificial Intelligence Models on Edge Devices for Real-Time Analytics." ITM Web of Conferences 76 (2025): 01009. https://doi.org/10.1051/itmconf/20257601009.

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Because of its on-the-go nature, edge AI has gained popularity, allowing for realtime analytics by deploying artificial intelligence models onto edge devices. Despite the promise of Edge AI evidenced by existing research, there are still significant barriers to widespread adoption with issues such as scalability, energy efficiency, security, and reduced model explainability representing common challenges. Hence, while this paper solves the Edge AI in a number of ways, with real use case of a deployment, modular adaptability, and dynamic AI model specialization. Our paradigm achieves low latenc

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Deepaisarn, Somrudee, Paphana Yiwsiw, Sirada Chaisawat, et al. "Automated Street Light Adjustment System on Campus with AI-Assisted Data Analytics." Sensors 23, no. 4 (2023): 1853. http://dx.doi.org/10.3390/s23041853.

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The smart city concept has been popularized in the urbanization of major metropolitan areas through the implementation of intelligent systems and technology to serve the increasing human population. This work developed an automatic light adjustment system at Thammasat University, Rangsit Campus, Thailand, with a primary objective of optimizing energy efficiency, while providing sufficient illumination for the campus. The development consists of two sections: the device control and the prediction model. The device control functionalities were developed with the user interface to enable control

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Kim, Seoyeon, and Yongkyung Cho. "A Study on the Importance of AI Smart Housing User Complaint Prevention Factors Using AHP." Residential Environment Institute Of Korea 21, no. 3 (2023): 37–47. http://dx.doi.org/10.22313/reik.2023.21.3.37.

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As interest in the 4th industrial revolution technology increases, the smart housing market where AI-based smart technology is grafted into cities is gradually growing. However, technological development is still being made centered on suppliers rather than users. Therefore, in this study, civil complaints that occurred while using the literature search and smart housing service were collected to analyze civil complaint elements, and the importance of civil complaint elements was derived through AHP. Through this, we tried to create a user-friendly base by preventing civil complaints about sma

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Sharma, Nidhi, and Suresh Kumar Kashyap. "Use of Digital Economies Ensuring Smart and Sustainable Manufacturing Systems for Industry 5.0." International Journal of Information Systems and Social Change 13, no. 1 (2022): 1–10. http://dx.doi.org/10.4018/ijissc.306965.

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Smart wearable technology is taken into account as a paradigm shift in healthcare and health insurance industry. More and more wrists are wrapped in smartwatches with advanced technology using serval applications connected to smart mobile phones and sensors to track and monitor the healthy lifestyle of the wearers. This paper aims at conducting a systematic review of literature related to smart wearables that engage people in ensuring sustainable healthy lifestyle. The increasing capability of automation with AI turned the robots to cobots and results in Industry 5.0 as a brand-new historic pe

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Dilip Mishra. "Risk Management and Performance Optimization in Solar Smart Grids with AI and IoT." Power System Technology 49, no. 1 (2025): 892–98. https://doi.org/10.52783/pst.1638.

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The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is revolutionizing the management of solar smart grids by enhancing risk management and performance optimization. AI-driven predictive maintenance utilizes real-time data from IoT sensors to anticipate equipment failures, thereby reducing energy losses and minimizing carbon footprints. In the United States, the Department of Energy's Artificial Intelligence for Interconnection (AI4IX) program has allocated $30 million to expedite the integration of renewable energy projects into the power grid using AI, aiming to

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Al Ridhawi, Ismaeel, Ouns Bouachir, Moayad Aloqaily, and Azzedine Boukerche. "Design Guidelines for Cooperative UAV-supported Services and Applications." ACM Computing Surveys 54, no. 9 (2022): 1–35. http://dx.doi.org/10.1145/3467964.

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Internet of Things (IoT) systems have advanced greatly in the past few years, especially with the support of Machine Learning (ML) and Artificial Intelligence (AI) solutions. Numerous AI-supported IoT devices are playing a significant role in providing complex and user-specific smart city services. Given the multitude of heterogeneous wireless networks, the plethora of computer and storage architectures and paradigms, and the abundance of mobile and vehicular IoT devices, true smart city experiences are only attainable through a cooperative intelligent and secure IoT framework. This article pr

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Jyoti Bolannavar and Dr. Sumati Ramakrishna Gowda. "Role of Artificial Intelligence in IoT." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 271–78. http://dx.doi.org/10.32628/cseit24106179.

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Artificial Intelligence (AI) and the Internet of Things (IoT) are two revolutionary technologies shaping modern industries. AI enables machines to learn from data and make autonomous decisions, while IoT connects devices, allowing them to communicate and exchange information. The convergence of these technologies, known as AIoT (Artificial Intelligence of Things), has immense potential to transform daily life and business operations. AI enhances IoT by adding intelligence to device networks, improving efficiency and automating processes. For example, AI-powered IoT systems can perform predicti

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Akash, Pednekar, and Bhelande Manish. "Using AI to Control User Appliance over the Internet." Recent Trends in Information Technology and its Application 4, no. 2 (2021): 1–5. https://doi.org/10.5281/zenodo.5005319.

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Home automation is becoming increasingly common as a result of its various benefits. The current state of affairs indicates that the home automation system is regulated by emails, messages, or other applications. That being said, in recent years, the scientific community and industry have made substantial investments in the area of Internet of Things (IoT). With the launch of devices such as Amazon Echo, Google Home, and Samsung Smart Stuff, among others, the Smart Home space has become a major focus. The development of an industry leads to the development of creative, cost-effective, and adva

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Pazmiño Ortiz, Leandro Antonio, Ivonne Fernanda Maldonado Soliz, and Vanessa Katherine Guevara Balarezo. "Advancing TinyML in IoT: A Holistic System-Level Perspective for Resource-Constrained AI." Future Internet 17, no. 6 (2025): 257. https://doi.org/10.3390/fi17060257.

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Resource-constrained devices, including low-power Internet of Things (IoT) nodes, microcontrollers, and edge computing platforms, have increasingly become the focal point for deploying on-device intelligence. By integrating artificial intelligence (AI) closer to data sources, these systems aim to achieve faster responses, reduce bandwidth usage, and preserve privacy. Nevertheless, implementing AI in limited hardware environments poses substantial challenges in terms of computation, energy efficiency, model complexity, and reliability. This paper provides a comprehensive review of state-of-the-

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Luo, Ziyang. "Protection of Acoustic Rights and Responses to Sound Infringement by Smart Energy Devices." Advances in Economics, Management and Political Sciences 168, no. 1 (2025): 36–44. https://doi.org/10.54254/2754-1169/2025.21506.

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With the advancement of artificial intelligence (AI) technology, the infringement of personal acoustic rights has become an increasingly severe issue. Objective factors, such as the ease of collecting voice data, have contributed to the frequent emergence of cases involving the infringement of personal acoustic rights through generative AI. In particular, the collection of voice data by smart energy devices has led to numerous legal and ethical issues. This paper examines the development and current status of legal frameworks protecting acoustic rights in Chinese law. It explores how the rise

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Ardianto, Yeheskiel Hency, and Indrastanti Ratna Widiasari. "IOT BASED SMART HOME SIMULATION (INTERNET OF THINGS)." JURTEKSI (Jurnal Teknologi dan Sistem Informasi) 10, no. 4 (2024): 795–802. https://doi.org/10.33330/jurteksi.v10i4.3361.

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Abstract: The development of Internet of Things (IoT) technology has significantly impacted life, particularly in creating more efficient and secure smart homes. Smart homes integrate various electronic devices to enhance comfort and energy efficiency. However, cost, integration complexity, and security issues remain. This study will simulate an IoT-based smart home system to analyse and evaluate device performance before real-world implementation. The simulation method involves testing connectivity and evaluating delay and packet loss using the ping method on each device. Results show the hig

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Khan, Laiba, Muhammad Azam, Misbah Altaf, Muhammad Zia-ul Rehman, Nighat Siddiqui, and Ammad Hussain. "A Critical Review of AI and IoT Integration in Smart Healthcare for Urban Innovation." Asian Bulletin of Big Data Management 5, no. 2 (2025): 27–34. https://doi.org/10.62019/mnyvy026.

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The rapid advancement of Artificial Intelligence (AI) and the Internet of Things (IoT) is transforming the concept of smart cities by enhancing the quality of life through technology-driven solutions. Among the most significantly impacted sectors is healthcare. AI-powered smart healthcare systems now enable real-time patient monitoring, early disease prediction, and faster medical decision-making. Wearable devices and mobile technologies offer continuous health tracking and telemedicine services, while emerging technologies like 6G sensing promise even greater improvements. This paper critical

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