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Relevant bibliographies by topics / Context-Aware AI

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Academic literature on the topic 'Context-Aware AI'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Context-Aware AI"

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Vignati, Micael, and Matthew Johnson. "Team Context-Aware Collaborative AI Assistants." Proceedings of the AAAI Symposium Series 5, no. 1 (2025): 119–21. https://doi.org/10.1609/aaaiss.v5i1.35574.

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True collaboration or teamwork involves being aware of the team and its goals, adapting to the changing situations, communicating relevant information, identifying break-downs in common ground and repairing them, all to improve joint outcomes. At the heart of this type of collaborative agent are the capabilities needed to understand context and determine relevance. We introduce four key capabilities that enable our collaborative agents to be effective collaborators by understanding context and determining relevance.

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Ayush, Kumar Jha Shahi Raza Khan. "AI-Powered Context-Aware Blockchain Explorer." Career Point International Journal of Research(CPIJR) 1, no. 4 (2025): 53–72. https://doi.org/10.5281/zenodo.15137907.

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The rapid evolution of blockchain technology necessitates advanced tools for efficient exploration and analysis of distributed ledger data. An <strong>AI-Powered Context-Aware Blockchain Explorer</strong> enhances traditional blockchain explorers by integrating artificial intelligence to provide contextual insights, anomaly detection, and predictive analytics. This system leverages<strong> </strong><strong>natural language processing (NLP)</strong><strong> </strong>and<strong> </strong><strong>machine learning algorithms</strong><strong> to </strong>enable intelligent querying, pattern recogni

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D, Rangraju. "Context-Aware AI for Personalized Public Transit Recommendations." International Journal of Science, Engineering and Technology 13, no. 2 (2025): 1–7. https://doi.org/10.61463/ijset.vol.13.issue2.378.

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Researcher. "REVOLUTIONIZING AI INTERACTIONS: THE RISE OF CONTEXT-AWARE SYSTEMS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 5 (2024): 776–83. https://doi.org/10.5281/zenodo.13899474.

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This article explores the revolutionary advancements in context-aware AI systems and their profound impact on personalized interactions across various industries. It delves into the evolution of these systems, highlighting the integration of sophisticated deep learning models and large language models that have significantly improved their ability to understand and maintain context in extended conversations. The article discusses key developments such as multi-turn conversations, multimodal contextual understanding, and their applications in sectors like customer service, healthcare, and retai

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Geib, Christopher, Vikas Agrawal, Gita Sukthankar, Lokendra Shastri, and Hung Bui. "Architectures for Activity Recognition and Context-Aware Computing." AI Magazine 36, no. 2 (2015): 3–9. http://dx.doi.org/10.1609/aimag.v36i2.2578.

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Wu, Qiong, Zhiwei Zeng, Jun Lin, and Yiqiang Chen. "AI empowered context-aware smart system for medication adherence." International Journal of Crowd Science 1, no. 2 (2017): 102–9. http://dx.doi.org/10.1108/ijcs-07-2017-0006.

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Purpose Poor medication adherence leads to high hospital admission rate and heavy amount of health-care cost. To cope with this problem, various electronic pillboxes have been proposed to improve the medication adherence rate. However, most of the existing electronic pillboxes use time-based reminders which may often lead to ineffective reminding if the reminders are triggered at inopportune moments, e.g. user is sleeping or eating. Design/methodology/approach In this paper, the authors propose an AI-empowered context-aware smart pillbox system. The pillbox system collects real-time sensor dat

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Huang, Chen-Hao, Tzu-Chuan Chou, and Sheng-Hsiung Wu. "Towards Convergence of AI and IoT for Smart Policing." Journal of Global Information Management 29, no. 6 (2021): 1–21. http://dx.doi.org/10.4018/jgim.296260.

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With the fast growth of IoT and AI techniques, AIoT’s potential in creating and capturing business value is being increasingly acknowledged. AIoT is the practice of combining AI with IoT-based hardware to proactively predict what might happen and what action needs to be taken. However, research on this issue has been limited and what the key mechanisms for designing AIoT based context-aware services are in the real field is still underexplored. In this article, we bridge this gap by studying a case study of AIoT based context-aware system in law enforcement in terms of information system artif

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Raghupathi Kanala, Meghana Vijaya Raghavan, Gundala Jathin Kumar, Sushruth Bommagoni, and Arun Kumar Onteddu. "Context aware intelligence resume analyser using deep learning algorithms." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 738–46. https://doi.org/10.30574/wjaets.2025.15.2.0588.

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This research introduces an AI-powered resume analyzer that makes it easier for people to evaluate and polish their resumes. Using cutting-edge Natural Language Processing (NLP), deep learning, and powerful Large Language Models (LLMs), the system quickly pulls out key details—like skills, education, work experience, and projects—from resumes in formats like PDF or DOCX. Unlike older resume tools, this one is faster and smarter, offering unique features like a Skill Gap Analysis to see how well your qualifications match a job’s needs. It also includes a neural network that ranks your resume’s

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Ashish, S. S. "Model Context Protocol: A Context-Aware Framework for Enhancing Cybersecurity in Dynamic Environments." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem49289.

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Abstract— The rapid evolution of cyber threats and growing complexity of digital environments require adaptive, intelligent, and context-aware cybersecurity solutions. The Model Context Protocol (MCP) has emerged as an open standard that facilitates seamless, secure, and dynamic integration between AI-driven security agents and a wide range of data sources, tools, and systems. This paper examines the architecture, security principles, and transformative impact of MCP in strengthening cybersecurity within dynamic environments, with a focus on its context-aware capabilities, interoperability, an

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Al-Saedi, Ahmed A., Veselka Boeva, Emiliano Casalicchio, and Peter Exner. "Context-Aware Edge-Based AI Models for Wireless Sensor Networks—An Overview." Sensors 22, no. 15 (2022): 5544. http://dx.doi.org/10.3390/s22155544.

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Recent advances in sensor technology are expected to lead to a greater use of wireless sensor networks (WSNs) in industry, logistics, healthcare, etc. On the other hand, advances in artificial intelligence (AI), machine learning (ML), and deep learning (DL) are becoming dominant solutions for processing large amounts of data from edge-synthesized heterogeneous sensors and drawing accurate conclusions with better understanding of the situation. Integration of the two areas WSN and AI has resulted in more accurate measurements, context-aware analysis and prediction useful for smart sensing appli

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Dissertations / Theses on the topic "Context-Aware AI"

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Stegner, Wayne. "Context-Aware Malware Detection Using Topic Modeling." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin162766765703398.

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Marroquín, Cortez Roberto Enrique. "Context-aware intelligent video analysis for the management of smart buildings." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCK040/document.

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Les systèmes de vision artificielle sont aujourd'hui limités à l'extraction de données issues de ce que les caméras « voient ». Cependant, la compréhension de ce qu'elles voient peut être enrichie en associant la connaissance du contexte et la connaissance d'interprétation d'un humain.Dans ces travaux de thèse, nous proposons une approche associant des algorithmes de vision atificielle à une modélisation sémantique du contexte d'acquisition.Cette approche permet de réaliser un raisonnement sur la connaissance extraite des images par les caméras en temps réel. Ce raisonnement offre une réponse

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Hoopes, Daniel Matthew. "The ContexTable: Building and Testing an Intelligent, Context-Aware Kitchen Table." BYU ScholarsArchive, 2004. https://scholarsarchive.byu.edu/etd/12.

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The purpose of this thesis was to design and evaluate The ContexTable, a context-aware system built into a kitchen table. After establishing the current status of the field of context-aware systems and the hurdles and problems being faced, a functioning prototype system was designed and built. The prototype makes it possible to explore established, untested theory and novel solutions to problems faced in the field.

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Koile, Kimberle, Konrad Tollmar, David Demirdjian, Howard Shrobe, and Trevor Darrell. "Activity Zones for Context-Aware Computing." 2003. http://hdl.handle.net/1721.1/6720.

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Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or Euclidean distance various landmarks. A user?s concept of location, however, is often defined in terms of regions in which common activities occur. We show how to partition a space into such regions based on patterns of observed user location and motion. These regions, which we call activity zones, represent regions of similar user activity, and can be used to trigger application actions, retrieve information based on previous context, and present info

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Books on the topic "Context-Aware AI"

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Mittu, Ranjeev, Donald Sofge, and William F. Lawless. Computational Context: The Value, Theory and Application of Context with AI. Taylor & Francis Group, 2018.

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Book chapters on the topic "Context-Aware AI"

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Banipal, Indervir Singh, Shubhi Asthana, Sourav Mazumder, and Nadiya Kochura. "Context Aware Auto-AI Framework." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53963-3_44.

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Zimba, Michael, Maha Jouini, and Angella K. Ndaka. "Context-Aware Africa-Led Designing of Responsible Artificial Intelligence Technologies." In Trustworthy AI. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-75674-0_7.

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Abstract Artificial intelligence (AI) is a general purpose technology (GPT), which is currently enjoying increasing use in strategic decision-making and military affairs. The AI revolution brings significant changes into the current and future socio-economic national and international systems, with AI applications expected to tilt the global balance of power in favour of actors who strategically invest and use this emerging technology. AI-assisted automation is also changing prevailing socio-economic production models on the global scale, and sooner or later, these technologies are expected to

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Wei, Xiaoyan, Zebang Zhang, Zijian Yue, and Hsiang-Ting Chen. "Context-AI Tunes: Context-Aware AI-Generated Music for Stress Reduction." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-93418-6_22.

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Shi, Yilong, Hong Lin, and Yuqiang Li. "Context-Aware Recommender Systems Based on Item-Grain Context Clustering." In AI 2017: Advances in Artificial Intelligence. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63004-5_1.

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Khoshkangini, Reza, Maria Silvia Pini, and Francesca Rossi. "A Self-Adaptive Context-Aware Group Recommender System." In AI*IA 2016 Advances in Artificial Intelligence. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49130-1_19.

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Coppola, Paolo, Vincenzo Della Mea, Luca Di Gaspero, et al. "AI Techniques in a Context-Aware Ubiquitous Environment." In Computer Communications and Networks. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-599-4_8.

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Clodic, Aurelie, and Rachid Alami. "What Is It to Implement a Human-Robot Joint Action?" In Robotics, AI, and Humanity. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-54173-6_19.

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AbstractJoint action in the sphere of human–human interrelations may be a model for human–robot interactions. Human–human interrelations are only possible when several prerequisites are met, inter alia: (1) that each agent has a representation within itself of its distinction from the other so that their respective tasks can be coordinated; (2) each agent attends to the same object, is aware of that fact, and the two sets of “attentions” are causally connected; and (3) each agent understands the other’s action as intentional. The authors explain how human–robot interaction can benefit from the

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Ruiz Garcia, Manuel A., Erwin Rauch, Renato Vidoni, and Dominik T. Matt. "AI and ML for Human-Robot Cooperation in Intelligent and Flexible Manufacturing." In Implementing Industry 4.0 in SMEs. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70516-9_3.

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AbstractHuman–robot cooperation aims to increase the flexibilization of manufacturing systems. This requires safe human–machine interaction (e.g. with collaborative robots) as well as self and environment awareness capabilities to interact autonomously and smartly between humans and machines. Therefore, the goal of this chapter is to conceptualize and identify the set of real-time information processing and decision-making capabilities required for collaborative robots to be considered as a safe companion in the context of human–robot cooperation (HRC). In particular, the chapter provides an o

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Abdulla, Salwa, Suadad Muammar, and Khaled Shaalan. "Pre-training on Multi-modal for Improved Persona Detection Using Multi Datasets." In BUiD Doctoral Research Conference 2023. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56121-4_22.

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AbstractPersona identification helps AI-based communication systems provide personalized and situationally informed interactions. This paper introduces pre-training on CNN, BERT, and GPT models to improve persona detection on PMPC and ROCStories datasets. Two speakers with different personalities have dialogues in the PMPC dataset. The challenge is to match each speaker to their persona. The ROCStories dataset contains fictional character traits and activities. Our study uses transformer-based design to improve persona detection using ROCStories dataset external context. We compare our method

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Bulfoni Adolfo, Coppola Paolo, Della Mea Vincenzo, et al. "AI on the Move: Exploiting AI Techniques for Context Inference on Mobile Devices." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2008. https://doi.org/10.3233/978-1-58603-891-5-668.

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Context aware computing is a computational paradigm that has faced a rapid growth in the last few years, especially in the field of mobile devices. One of the promises of context-awareness in this field is the possibility of automatically adapting the functioning mode of mobile devices to the environment and the current situation the user is in, with the aim of improving both their efficiency (using the scarce resources in a more efficient way) and effectiveness (providing better services to the user). We propose a novel approach for providing a basic infrastructure for context-aware applicati

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Conference papers on the topic "Context-Aware AI"

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Wang, Shuang, Wei Bao, Zhongming Huang, Binbin Ye, Jiashun Tang, and Bo Xu. "Context-aware Online Federated Split Learning in 5G Networks." In 2024 5th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI). IEEE, 2024. https://doi.org/10.1109/iccbd-ai65562.2024.00087.

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Rosas, Erika, and Javier Prades. "CONTEXT-AWARE AI ASSISTANTS FOR HANDS-ON AND INTERACTIVE COMPUTING EDUCATION." In 17th International Conference on Education and New Learning Technologies. IATED, 2025. https://doi.org/10.21125/edulearn.2025.1347.

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Valenti, Emanuele, Silvia Piscetta, Yutao Ye, et al. "Context-Aware Automation: AI Based Mood Detection for Personalized Smart Homes." In 2025 8th International Conference on Communication Engineering and Technology (ICCET). IEEE, 2025. https://doi.org/10.1109/iccet65872.2025.11082620.

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Anik, Mahfuz Ahmed, Abdur Rahman, Azmine Toushik Wasi, and Md Manjurul Ahsan. "Preserving Cultural Identity with Context-Aware Translation Through Multi-Agent AI Systems." In Proceedings of the 1st Workshop on Language Models for Underserved Communities (LM4UC 2025). Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.lm4uc-1.7.

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Mandaliya, Sunil, and Priti Kulkarni. "Harnessing Context-Aware AI for Smarter DecisionMaking: A New Era in Business Intelligence." In 2024 First International Conference for Women in Computing (InCoWoCo). IEEE, 2024. https://doi.org/10.1109/incowoco64194.2024.10863128.

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Huynh, Gia Ky, and Wenjun Lin. "SmartCaption AI - Enhancing Web Accessibility with Context-Aware Image Descriptions Using Large Language Models." In 2024 International Conference on Computer and Applications (ICCA). IEEE, 2024. https://doi.org/10.1109/icca62237.2024.10928130.

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Memeti, Agon, Ibrahim Neziri, Neshat Ajruli, Krenar Huseini, Asri Nuhi, and Aqim Iljazi. "Context-Aware AI for Real-Time Content and Quiz Recommendations in Student Learning Environments." In 2025 3rd Cognitive Models and Artificial Intelligence Conference (AICCONF). IEEE, 2025. https://doi.org/10.1109/aicconf64766.2025.11063980.

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Rosario, Carl Danniel Pajara Del, Leah Mae Deloso Fernandez, Vivien Accad Agustin, Criselle Jose Centeno, Marilou Barsobia Mangrobang, and Dan Michael Cortez. "AI-Powered Intelligent Mindfulness-Based Cognitive Therapy Companion for Emotion Recognition and Context-Aware Therapy." In 2024 8th International Symposium on Innovative Approaches in Smart Technologies (ISAS). IEEE, 2024. https://doi.org/10.1109/isas64331.2024.10845635.

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Behravan, Majid, Krešimir Matković, and Denis Gračanin. "Generative AI for Context-Aware 3D Object Creation Using Vision-Language Models in Augmented Reality." In 2025 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR). IEEE, 2025. https://doi.org/10.1109/aixvr63409.2025.00018.

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Hasan, Md Amit, Md Shahin Alam Mozumder, Md Rokibul Hasan, Mohammad Balayet Hossain Sakil, Arifa Akter Eva, and Md Nahid Hasan. "CAMICS: A Context-Aware Multi-Intent Conversational System for Enhanced AI-Driven Customer Interaction Models." In 2025 International Conference on Emerging Smart Computing and Informatics (ESCI). IEEE, 2025. https://doi.org/10.1109/esci63694.2025.10988381.

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