Advanced Context-Aware Computing for Human Machine Interaction in Consumer Electronics

The evolution of context-aware computing (CAC) from its traditional roots to advanced implementations marks a significant milestone in human–machine interactions. With the rise of smart devices and Internet of Things technologies, there is a greater need for advanced systems that can adapt to diverse contexts in consumer electronics. Therefore, an advanced CAC approach is proposed to redefine human–machine interaction for more intuitive, personalized, and adaptable contexts. This approach utilizes cutting-edge technologies, such as machine learning and sensor fusion, for real-time and accurate context recognition as well as enables more seamless and responsive interactions for enhancing user experiences by delivering contextually relevant content and services.

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Publication Details

Journal
IEEE Consumer Electronics Magazine
Published
2024-09-10
DOI
https://doi.org/10.1109/mce.2024.3456965
Citations
1
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.25

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article

Advanced Context-Aware Computing for Human Machine Interaction in Consumer Electronics

Uttam Ghosh, Debashis Das, Mohammed S. Al-Numay, Pushpita Chatterjee
1 citations
IEEE Consumer Electronics Magazine
Context-Aware Activity Recognition Systems
0.25
article

Advanced Context-Aware Computing for Human Machine Interaction in Consumer Electronics

Uttam Ghosh, Debashis Das, Mohammed S. Al-Numay, Pushpita Chatterjee
article en
1 citations

Abstract

The evolution of context-aware computing (CAC) from its traditional roots to advanced implementations marks a significant milestone in human–machine interactions. With the rise of smart devices and Internet of Things technologies, there is a greater need for advanced systems that can adapt to diverse contexts in consumer electronics. Therefore, an advanced CAC approach is proposed to redefine human–machine interaction for more intuitive, personalized, and adaptable contexts. This approach utilizes cutting-edge technologies, such as machine learning and sensor fusion, for real-time and accurate context recognition as well as enables more seamless and responsive interactions for enhancing user experiences by delivering contextually relevant content and services.

IEEE Consumer Electronics MagazineVol. 14(2)
Meharry Medical College (US), King Saud University (SA)
National Science Foundation
Openalex Percentile: Top 48%
Context-Aware Activity Recognition Systems
0.25
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Advanced Context-Aware Computing for Human Machine Interaction in Consumer Electronics — Uttam Ghosh, Debashis Das, et al. · IEEE Consumer Electronics Magazine (2024) | TGRS Research Map | TGRS