Abstract The Artificial Intelligence of Things (AIoT), a combination of the Internet of Things
(IoT) and Artificial Intelligence (AI), plays an increasingly important role in smart agriculture …

In this study, we introduce FLIBD, a novel strategy for managing Internet of Things (IoT) Big
Data, intricately designed to ensure privacy preservation across extensive system networks …

Predictive maintenance (PdM) combines the Internet of Things (IoT) technologies with
machine learning (ML) to predict probable failures, which leads to the necessity of …

The integration of IoT and cloud poses increased security challenges. Implementing security
mechanisms in IoT systems is challenging due to the availability of limited resources, large …

Seamless Internet of Things (IoT) connections expose many vulnerabilities in wireless
networks, and IoT devices inevitably face many malicious active attacks. automatic …

In recent years, smart healthcare, artificial intelligence (AI)‐aided diagnostics, and
automated surgical robots are just a few of the innovations that have emerged and gained …

Background Deep Learning is an AI technology that trains computers to analyze data in an
approach similar to the human brain. Deep learning algorithms can find complex patterns in …

Background Anxiety is known as one of the most common health disorders affecting a large
part of the population with a high social and personal impact, which affects about 25% of …

The massive collection and transmission of various crop and livestock data in smart
agriculture leads to serious security concerns. Furthermore, many Internet of Things (IoT) …

This research paper delves into the security concerns within Internet of Things (IoT)
networks, emphasizing the need to safeguard the extensive data generated by …