Various human activities emit greenhouse gasses (GHGs) that contribute to global climate
change. These include the burning of fossil fuels for energy production, transportation, and …

Over the past few years, significant investments in smart traffic monitoring systems have
been made. The most important step in machine learning is detecting and recognizing …

Sleep-wake detection is of great importance for the measurement of sleep quality. In this
article, a novel ensemble deep learning framework is proposed to detect sleep-wake states …

The rapid growth of the Internet of Things (IoT) has led to its widespread adoption in various
industries, enabling enhanced productivity and efficient services. Integrating IoT systems …

Smart city challenges, like increased traffic, risk to public safety, effective law enforcement
and the smart environment challenges on improving personalized services such as health …

Non‐technical loss (NTL) is detrimental to the smart grid. Intelligent application of advanced
metering infrastructure (AMI) helps to solve NTL detection and classification. By using …

In this paper the importance of monitoring smart city with integration of sensors and Internet
of Things (IoT) is discussed with establishment of node control process. To describe the …

Abstract Multistep Human Density Prediction (MHDP) is an emerging challenge in urban
mobility with lots of applications in several domains such as Smart Cities, Edge Computing …

In this paper, we present an adaptive Reinforcement Learning (RL) agent training approach
which aims to provide a temperature control adaptable to various types of buildings. The …

Abstract Nowadays, the Internet of Things (IoT) and artificial intelligence (AI) is the emerging
field in which researchers are still finding new methods and techniques to reduce human …