AHCI RESEARCH GROUP

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OUR RESEARCH

Scientific Publications

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2025

B, C. E. Pardo; R, O. I. Iglesias; A, M. D. León; M., C. G. Quintero

EverydAI: Virtual Assistant for Decision-Making in Daily Contexts, Powered by Artificial Intelligence Journal Article

In: Systems, vol. 13, no. 9, 2025, ISSN: 20798954 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).

Abstract | Links | BibTeX | Tags: Artificial intelligence, Augmented Reality, Behavioral Research, Decision making, Decisions makings, Digital avatar, Digital avatars, Information overloads, Informed decision, Interactive computer graphics, Language Model, Large language model, large language models, Natural language processing systems, Natural languages, Object Detection, Object recognition, Objects detection, recommendation systems, Recommender systems, Three dimensional computer graphics, Virtual assistants, Virtual Reality, web scraping, Web scrapings

@article{pardo_b_everydai_2025,

title = {EverydAI: Virtual Assistant for Decision-Making in Daily Contexts, Powered by Artificial Intelligence},

author = {C. E. Pardo B and O. I. Iglesias R and M. D. León A and C. G. Quintero M.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105017115803&doi=10.3390%2Fsystems13090753&partnerID=40&md5=475327fffcdc43ee3466b4a65111866a},

doi = {10.3390/systems13090753},

issn = {20798954 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Systems},

volume = {13},

number = {9},

abstract = {In an era of information overload, artificial intelligence plays a pivotal role in supporting everyday decision-making. This paper introduces EverydAI, a virtual AI-powered assistant designed to help users make informed decisions across various daily domains such as cooking, fashion, and fitness. By integrating advanced natural language processing, object detection, augmented reality, contextual understanding, digital 3D avatar models, web scraping, and image generation, EverydAI delivers personalized recommendations and insights tailored to individual needs. The proposed framework addresses challenges related to decision fatigue and information overload by combining real-time object detection and web scraping to enhance the relevance and reliability of its suggestions. EverydAI is evaluated through a two-phase survey, each one involving 30 participants with diverse demographic backgrounds. Results indicate that on average, 92.7% of users agreed or strongly agreed with statements reflecting the system’s usefulness, ease of use, and overall performance, indicating a high level of acceptance and perceived effectiveness. Additionally, EverydAI received an average user satisfaction score of 4.53 out of 5, underscoring its effectiveness in supporting users’ daily routines. © 2025 Elsevier B.V., All rights reserved.},

note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},

keywords = {Artificial intelligence, Augmented Reality, Behavioral Research, Decision making, Decisions makings, Digital avatar, Digital avatars, Information overloads, Informed decision, Interactive computer graphics, Language Model, Large language model, large language models, Natural language processing systems, Natural languages, Object Detection, Object recognition, Objects detection, recommendation systems, Recommender systems, Three dimensional computer graphics, Virtual assistants, Virtual Reality, web scraping, Web scrapings},

pubstate = {published},

tppubtype = {article}

}