返回
Advanced Context-Aware Computing for Human Machine Interaction in Consumer Electronics
DOI:10.1109/MCE.2024.3456965.png)
摘要
En 中文
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.
Keyword:
Hidden Markov models
Real-time systems
Adaptation models
Data models
Consumer electronics
Accuracy
Sensor fusion
期刊
IF:
4.1
论文数:
1.3K
被引数:
1.8K
机构
引用论文
Dual deep Q-learning network guiding a multiagent path planning approach for virtual fire emergency scenarios
APPLIED INTELLIGENCE
IF3.5
Data Driven Neural Speech Enhancement for Smart Healthcare in Consumer Electronics Applications面向消费电子应用的智能医疗的数据驱动神经语音增强
A survey on the use of machine learning methods in context-aware middlewares for human activity recognition在上下文感知的中间件中使用机器学习方法进行人体活动识别的调查
A Comprehensive Survey on Artificial Intelligence Empowered Edge Computing on Consumer Electronics人工智能为消费电子产品的边缘计算提供了全面的调查
没有更多内容

