AIMC Topic: Internet of Things

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Revolutionizing biological digital twins: Integrating internet of bio-nano things, convolutional neural networks, and federated learning.

Computers in biology and medicine
Digital twins (DTs) are advancing biotechnology by providing digital models for drug discovery, digital health applications, and biological assets, including microorganisms. However, the hypothesis posits that implementing micro- and nanoscale DTs, e...

Use of Artificial Intelligence, Internet of Things, and Edge Intelligence in Long-Term Care for Older People: Comprehensive Analysis Through Bibliometric, Google Trends, and Content Analysis.

Journal of medical Internet research
BACKGROUND: The global aging population poses critical challenges for long-term care (LTC), including workforce shortages, escalating health care costs, and increasing demand for high-quality care. Integrating artificial intelligence (AI), the Intern...

Opportunistic access control scheme for enhancing IoT-enabled healthcare security using blockchain and machine learning.

Scientific reports
The healthcare industry, aided by technology, leverages the Internet of Things (IoT) paradigm to offer patient/user-related services that are ubiquitous and personalized. The authorized repository stores ubiquitous data for which access-level securit...

Prediction and detection of terminal diseases using Internet of Medical Things: A review.

Computers in biology and medicine
The integration of Artificial Intelligence (AI) with the Internet of Medical Things (IoMT) has revolutionized disease prediction and detection, but challenges such as data heterogeneity, privacy concerns, and model generalizability hinder its full po...

Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and frame theory: a systematic review.

Frontiers in public health
The escalating demand for chronic disease management has presented substantial challenges to traditional methods. However, the emergence of Internet of Things (IoT) and artificial intelligence (AI) technologies offers a potential resolution by facili...

IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition.

Scientific reports
Deaf and hard-of-hearing people utilize sign language recognition (SLR) to interconnect. Sign language (SL) is vital for hard-of-hearing and deaf individuals to communicate. SL uses varied hand gestures to speak words, sentences, or letters. It aids ...

A Multimodal Pain Sentiment Analysis System Using Ensembled Deep Learning Approaches for IoT-Enabled Healthcare Framework.

Sensors (Basel, Switzerland)
This study introduces a multimodal sentiment analysis system to assess and recognize human pain sentiments within an Internet of Things (IoT)-enabled healthcare framework. This system integrates facial expressions and speech-audio recordings to evalu...

Smart IoT-based snake trapping device for automated snake capture and identification.

Environmental monitoring and assessment
The threat of snakebites to public health, particularly in tropical and subtropical regions, requires effective mitigation strategies to avoid human-snake interactions. With the development of an IoT-based smart snake-trapping device, an innovative n...

Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities.

Scientific reports
Disabled persons demanding healthcare is a developing global occurrence. The support in longer-term care includes nursing, intricate medical, recovery, and social help services. The price is large, but advanced technologies can aid in decreasing expe...

Federated Learning for IoMT-Enhanced Human Activity Recognition with Hybrid LSTM-GRU Networks.

Sensors (Basel, Switzerland)
The proliferation of wearable sensors and mobile devices has fueled advancements in human activity recognition (HAR), with growing importance placed on both accuracy and privacy preservation. In this paper, the author proposes a federated learning fr...