Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The advancement of AI-powered personal assistants
has significantly enhanced human-computer interaction by en
abling task automation, personalized assistance, and real-time
communication. However, existing virtual assistants such as Siri,
Alexa, and Google Assistant face limitations in security, privacy,
and multi-user adaptability. Many rely on cloud-based processing
and single-factor authentication, making them vulnerable to data
breaches and unauthorized access. Additionally, they often lack
multi-user support, regional language adaptability, and mobile
automation capabilities, limiting their effectiveness across diverse
demographics.
This research proposes an AI-based personal assistant that
integrates face recognition-based authentication to provide secure
and personalized access. Unlike conventional assistants, which
depend on cloud computing, this system implements privacy
preserving edge computing, reducing reliance on external servers
while improving data security and computational efficiency.
The assistant supports multi-language interactions (English &
Malayalam), ensuring inclusivity, and offers mobile automation
features such as making calls via voice commands. Additionally,
it automates various tasks, including email management, web
searches, WhatsApp automation, and system control, providing
a seamless and user-friendly experience.
Developed using Python, NLP, SQLite, and deep learning
models, this system prioritizes biometric-driven authentication,
enhanced security, and real-time adaptability. Experimental eval
uations demonstrate improved authentication accuracy, faster
task execution, reduced latency, and enhanced privacy protection
compared to traditional AI assistants. By integrating secure
biometric authentication, intelligent automation, and mobile
functionality, this research aims to develop a next-generation
AI assistant that is privacy-focused, efficient, and adaptable to
modern digital environments.
Keywords:
Artificial Intelligence, Face Recognition, Natural Language Processing, AI Assistant, Task Automation, Biometric Authentication, Multilingual Support.
Cite Article:
"A Personal Virtual AI Assistant", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.c33-c38, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503207.pdf
Downloads:
000294
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator