Academic Associate in the context of Undergraduate Studies in courses:
Abstract
The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP’s roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era.
Abstract
Throughout human history, agriculture has undergone a series of progressive transfor-
mations based on ever-evolving technologies in an effort to increase productivity and profitability.
Over the years, farming methods have evolved significantly, progressing from Agriculture 1.0, which
relied on primitive tools, to Agriculture 2.0, which incorporated machinery and advanced farming
practices, and subsequently to Agriculture 3.0, which emphasized mechanization and employed
intelligent machinery and technology to enhance productivity levels. To further automate and
increase agricultural productivity while minimizing agricultural inputs and pollutants, a new ap-
proach to agricultural management based on the concepts of the fourth industrial revolution is being
embraced gradually. This approach is referred to as “Agriculture 4.0” and is mainly implemented
through the use of Internet of Things (IoT) technologies, enabling the remote control of sensors and
actuators and the efficient collection and transfer of data. In addition, fueled by technologies such
as robotics, artificial intelligence, quantum sensing, and four-dimensional communication, a new
form of smart agriculture, called “Agriculture 5.0,” is now emerging. Agriculture 5.0 can exploit
the growing 5G network infrastructure as a basis. However, only 6G-IoT networks will be able
to offer the technological advances that will allow the full expansion of Agriculture 5.0, as can be
inferred from the relevant scientific literature and research. In this article, we first introduce the
scope of Agriculture 5.0 as well as the key features and technologies that will be leveraged in the
much-anticipated 6G-IoT communication systems. We then highlight the importance and influence
of these developing technologies in the further advancement of smart agriculture and conclude with
a discussion of future challenges and opportunities.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.
Abstract
The rapidly increasing number of mobile devices and resource-intensive applications poses substantial obstacles to traditional centralized mobile cloud computing, resulting in increased latency and decreased service quality. Edge computing, which places server capabilities at access nodes, provides a promising solution to the aforementioned issues. However, maintaining operational edge service nodes at each access node can be costly and inefficient. We propose and evaluate a scheme that combines a heuristic service node selection algorithm with machine learning based computational load prediction, with the goal of minimizing latency and balancing load among service nodes. Simulation experiments demonstrate that the proposed scheme substantially enhances system performance, paving the way for a more efficient and responsive edge network infrastructure, particularly in 5G and 6G mobile communication environments.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.