scholarly journals An Agent-Based Approach to Realize Emergent Configurations in the Internet of Things

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1347 ◽  
Author(s):  
Fahed Alkhabbas ◽  
Romina Spalazzese ◽  
Paul Davidsson
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
The Internet ◽  
Daily Lives ◽  
Agent Based ◽  
Design Time ◽  
Underlying Processes ◽  
The Internet Of Things

The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability.

scholarly journals IMPROVING INTERNET OF THINGS PARKING SYSTEMS

2021 ◽  
Vol 19 (3) ◽  
pp. 163
Author(s):  
Dušan Bogićević
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Information Needs ◽  
Vehicle Classification ◽  
The Internet ◽  
Parking Space ◽  
Automated Systems ◽  
The Internet Of Things

Edge data processing represents the new evolution of the Internet and Cloud computing. Its application to the Internet of Things (IoT) is a step towards faster processing of information from sensors for better performance. In automated systems, we have a large number of sensors, whose information needs to be processed in the shortest possible time and acted upon. The paper describes the possibility of applying Artificial Intelligence on Edge devices using the example of finding a parking space for a vehicle, and directing it based on the segment the vehicle belongs to. Algorithm of Machine Learning is used for vehicle classification, which is based on vehicle dimensions.

scholarly journals Management of Software-Defined Networking Powered by Artificial Intelligence

2021 ◽  
Author(s):  
Jehad Ali ◽  
Byeong-hee Roh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
Heterogeneous Networks ◽  
Software Defined Networking ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Underlying Network ◽  
And Control ◽  
The Internet Of Things

Separating data and control planes by Software-Defined Networking (SDN) not only handles networks centrally and smartly. However, through implementing innovative protocols by centralized controllers, it also contributes flexibility to computer networks. The Internet-of-Things (IoT) and the implementation of 5G have increased the number of heterogeneous connected devices, creating a huge amount of data. Hence, the incorporation of Artificial Intelligence (AI) and Machine Learning is significant. Thanks to SDN controllers, which are programmable and versatile enough to incorporate machine learning algorithms to handle the underlying networks while keeping the network abstracted from controller applications. In this chapter, a software-defined networking management system powered by AI (SDNMS-PAI) is proposed for end-to-end (E2E) heterogeneous networks. By applying artificial intelligence to the controller, we will demonstrate this regarding E2E resource management. SDNMS-PAI provides an architecture with a global view of the underlying network and manages the E2E heterogeneous networks with AI learning.

scholarly journals IoT for Smart Environment Monitoring Based on Python: A Review

2021 ◽  
pp. 57-70
Author(s):  
Saad Hikmat Haji ◽  
Amira B. Sallow
Keyword(s):  
Water Pollution ◽  
Machine Learning ◽  
Internet Of Things ◽  
Environmental Monitoring ◽  
Sensor Technology ◽  
The Internet ◽  
Smart Environment ◽  
Environment Monitoring ◽  
The Internet Of Things

Air pollution, water pollution, and radiation pollution are significant environmental factors that need to be addressed. Proper monitoring is crucial with the goal that by preserving a healthy society, the planet can achieve sustainable development. With advancements in the internet of things (IoT) and the improvement of modern sensors, environmental monitoring has evolved into a smart environment monitoring (SEM) system in recent years. This article aims to have a critical overview of significant contributions and SEM research, which include monitoring the quality of air , water pollution, radiation pollution, and agricultural systems. The review is divided based on the objectives of applying SEM methods, analyzing each objective about the sensors used, machine learning, and classification methods. Moreover, the authors have thoroughly examined how advancements in sensor technology, the Internet of Things, and machine learning methods have made environmental monitoring into a truly smart monitoring system.

Review of the Role of the Internet of Things (IoT) on the Consumer Market

2021 ◽  
pp. 180-198
Author(s):  
Yong Kyu Lee
Keyword(s):  
Internet Of Things ◽  
Wearable Devices ◽  
The Internet ◽  
Consumer Market ◽  
Daily Lives ◽  
Information And Communication ◽  
Iot Devices ◽  
The Internet Of Things

This chapter reviews the internet of things (IoT) as a key component of a smart city and how it is applied to consumers' daily lives and business. The IoT is a part of information and communication technology (ICT) and is considered a powerful means to improve consumers' quality of life. The “thing” could be any object which has internet capability, such as wearable devices and smart TVs/phones/speakers. Several studies have identified driving factors that have led consumers to adopting them, but also concerns of consumers' resistance to IoT devices. The three major fields of application of IoT technologies were selected to review the role of the IoT in consumers' daily lives and business.

scholarly journals Technology and More-Than-Human Design

Design Issues ◽  
2020 ◽  
Vol 36 (4) ◽  
pp. 33-44 ◽  
Author(s):  
Elisa Giaccardi ◽  
Johan Redström
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
The Internet ◽  
User Centered Design ◽  
Human Centered Design ◽  
Design Methodologies ◽  
The Everyday ◽  
The Internet Of Things ◽  
User Centered

Are we reaching the limits of what human-centered and user-centered design can cope with? Developing new design methodologies and tools to unlock the potentials of data technologies such as the Internet of Things, Machine Learning and Artificial Intelligence for the everyday job of design is necessary but not sufficient. There is now a need to fundamentally question what happens when human-centered design is unable to effectively give form to technology, why this might be the case, and where we could look for alternatives.

scholarly journals Implementación de Aplicaciones Informáticas en la Industria Agrícola del Aguacate

2019 ◽  
pp. 13-23
Author(s):  
Raquel Ochoa-Ornelas ◽  
Daniel Fajardo-Delgado ◽  
María Guadalupe Sánchez-Cervantes ◽  
Jonathan Osornio-Mendoza
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Mobile Applications ◽  
Digital Technologies ◽  
The Internet ◽  
Agile Methodologies ◽  
Large Databases ◽  
Incremental Strategy ◽  
The Internet Of Things

Agriculture 4.0, conceived as a kind of industry, is built by integrating a set of digital technologies such as the Internet of things, Artificial Intelligence, and the management of large databases (or Big Data). This industry implies a transformation of the production infrastructure that allows increasing the agricultural productivity and the quality of the products efficiently and sustainably. These changes require the implementation of digital technologies for the collection, analysis and communication of information, allowing timely decision making. This article deals with the implementation of a platform that includes both desktop, Web and mobile applications and Internet of things tools for the control of production and marketing in avocado orchards. The development of a prototype of the platform is described under agile methodologies and following an iterative and incremental strategy. Finally, the tests that determine the integral functionality of the platform prototype and experimental results are presented.

Analogizing the Internet of Things

2020 ◽  
Author(s):  
Scott J. Shackelford
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
Space Exploration ◽  
The Internet ◽  
New Frontier ◽  
The Internet Of Things

As any new frontier opens or industry matures, it’s natural to search for analogies and historical precedents to guide both our actions and perceptions. President Kennedy famously compared space exploration to seafaring.1 The rise of artificial intelligence and machine learning discussed further...

scholarly journals A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 880
Author(s):  
Imran ◽  
Zeba Ghaffar ◽  
Abdullah Alshahrani ◽  
Muhammad Fayaz ◽  
Ahmed Mohammed Alghamdi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Quality Of Service ◽  
Internet Of Things ◽  
Software Defined Networking ◽  
Machine Learning Techniques ◽  
The Internet ◽  
Resources Management ◽  
Learning Techniques ◽  
The Internet Of Things

In recent years, rapid development has been made to the Internet of Things communication technologies, infrastructure, and physical resources management. These developments and research trends address challenges such as heterogeneous communication, quality of service requirements, unpredictable network conditions, and a massive influx of data. One major contribution to the research world is in the form of software-defined networking applications, which aim to deploy rule-based management to control and add intelligence to the network using high-level policies to have integral control of the network without knowing issues related to low-level configurations. Machine learning techniques coupled with software-defined networking can make the networking decision more intelligent and robust. The Internet of Things application has recently adopted virtualization of resources and network control with software-defined networking policies to make the traffic more controlled and maintainable. However, the requirements of software-defined networking and the Internet of Things must be aligned to make the adaptations possible. This paper aims to discuss the possible ways to make software-defined networking enabled Internet of Things application and discusses the challenges solved using the Internet of Things leveraging the software-defined network. We provide a topical survey of the application and impact of software-defined networking on the Internet of things networks. We also study the impact of machine learning techniques applied to software-defined networking and its application perspective. The study is carried out from the different perspectives of software-based Internet of Things networks, including wide-area networks, edge networks, and access networks. Machine learning techniques are presented from the perspective of network resources management, security, classification of traffic, quality of experience, and quality of service prediction. Finally, we discuss challenges and issues in adopting machine learning and software-defined networking for the Internet of Things applications.

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

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