Design And Analysis Of Compact Microstrip Filtenna For Internet Of Things Applications

The rapid growth of online education has created a need for reliable and secure assessment systems. Traditional online examinations lack proper monitoring, leading to increased academic dishonesty. This paper introduces Smart Assess, an intelligent online assessment system that integrates artificial intelligence for monitoring and evaluation. The system uses behavioural analysis techniques such as keystroke dynamics, facial tracking, and interaction patterns to ensure authenticity. Additionally, a predictive integrity model is proposed to detect potential cheating behaviours in real time. The system improves fairness, scalability, and efficiency in online assessments. Experimental results indicate that AI-based monitoring significantly enhances integrity compared to traditional systems [1][2].

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-01
DOI
https://doi.org/10.5281/zenodo.19277234
Primary Topic
User Authentication and Security Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Design And Analysis Of Compact Microstrip Filtenna For Internet Of Things Applications

Dr.k. Brindha, Nishad Mohammed N
Zenodo (CERN European Organization for Nuclear Research)
User Authentication and Security Systems
article

Design And Analysis Of Compact Microstrip Filtenna For Internet Of Things Applications

Dr.k. Brindha, Nishad Mohammed N
article en

Abstract

The rapid growth of online education has created a need for reliable and secure assessment systems. Traditional online examinations lack proper monitoring, leading to increased academic dishonesty. This paper introduces Smart Assess, an intelligent online assessment system that integrates artificial intelligence for monitoring and evaluation. The system uses behavioural analysis techniques such as keystroke dynamics, facial tracking, and interaction patterns to ensure authenticity. Additionally, a predictive integrity model is proposed to detect potential cheating behaviours in real time. The system improves fairness, scalability, and efficiency in online assessments. Experimental results indicate that AI-based monitoring significantly enhances integrity compared to traditional systems [1][2].

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 4%
User Authentication and Security Systems
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