At the confluence of artificial intelligence and edge computing in iot-based applications: A review and new perspectives
Given its advantages in low latency, fast response, context-aware services, mobility, and
privacy preservation, edge computing has emerged as the key support for intelligent …
privacy preservation, edge computing has emerged as the key support for intelligent …
Air-pollution prediction in smart city, deep learning approach
Over the past few decades, due to human activities, industrialization, and urbanization, air
pollution has become a life-threatening factor in many countries around the world. Among …
pollution has become a life-threatening factor in many countries around the world. Among …
TinyML: Enabling of inference deep learning models on ultra-low-power IoT edge devices for AI applications
Recently, the Internet of Things (IoT) has gained a lot of attention, since IoT devices are
placed in various fields. Many of these devices are based on machine learning (ML) models …
placed in various fields. Many of these devices are based on machine learning (ML) models …
[HTML][HTML] Deep-learning architecture for PM2. 5 concentration prediction: A review
S Zhou, W Wang, L Zhu, Q Qiao, Y Kang - Environmental Science and …, 2024 - Elsevier
Accurately predicting the concentration of fine particulate matter (PM 2.5) is crucial for
evaluating air pollution levels and public exposure. Recent advancements have seen a …
evaluating air pollution levels and public exposure. Recent advancements have seen a …
Machine learning techniques to predict the air quality using meteorological data in two urban areas in Sri Lanka
The effect of bad air quality on human health is a well-known risk. Annual health costs have
significantly been increased in many countries due to adverse air quality. Therefore …
significantly been increased in many countries due to adverse air quality. Therefore …
A hybrid spatiotemporal deep model based on CNN and LSTM for air pollution prediction
Nowadays, air pollution is an important problem with negative impacts on human health and
on the environment. The air pollution forecast can provide important information to all …
on the environment. The air pollution forecast can provide important information to all …
Multi-feature fusion and improved BO and IGWO metaheuristics based models for automatically diagnosing the sleep disorders from sleep sounds
A night of regular and quality sleep is vital in human life. Sleep quality has a great impact on
the daily life of people and those around them. Sounds such as snoring reduce not only the …
the daily life of people and those around them. Sounds such as snoring reduce not only the …
Estimation of missing air pollutant data using a spatiotemporal convolutional autoencoder
A key challenge in building machine learning models for time series prediction is the
incompleteness of the datasets. Missing data can arise for a variety of reasons, including …
incompleteness of the datasets. Missing data can arise for a variety of reasons, including …
Comprehensive survey on air quality monitoring systems based on emerging computing and communication technologies
In recent years, technologies related to indoor and outdoor air quality monitoring systems
have been growing rapidly, particularly computing and communication technologies …
have been growing rapidly, particularly computing and communication technologies …
Split BiRNN for real-time activity recognition using radar and deep learning
Radar systems can be used to perform human activity recognition in a privacy preserving
manner. This can be achieved by using Deep Neural Networks, which are able to effectively …
manner. This can be achieved by using Deep Neural Networks, which are able to effectively …