What Is New with the Internet of Things in Privacy and Data Protection? Four Legal Challenges on Sharing and Control in IoT

2017 ◽  
pp. 59-78 ◽  
Author(s):  
Ugo Pagallo ◽  
Massimo Durante ◽  
Shara Monteleone
Keyword(s):  
Internet Of Things ◽  
Data Protection ◽  
The Internet ◽  
Legal Challenges ◽  
And Control ◽  
The Internet Of Things

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 The spectrum of control: A social theory of the smart city

First Monday ◽  
2015 ◽  
Author(s):  
Jathan Sadowski ◽  
Frank Pasquale
Keyword(s):  
Internet Of Things ◽  
Social Theory ◽  
Smart City ◽  
Critical Infrastructure ◽  
The Internet ◽  
Control Mechanisms ◽  
Physical Objects ◽  
Smart Technologies ◽  
And Control ◽  
The Internet Of Things

There is a certain allure to the idea that cities allow a person to both feel at home and like a stranger in the same place. That one can know the streets and shops, avenues and alleys, while also going days without being recognized. But as elites fill cities with “smart” technologies — turning them into platforms for the “Internet of Things” (IoT): sensors and computation embedded within physical objects that then connect, communicate, and/or transmit information with or between each other through the Internet — there is little escape from a seamless web of surveillance and power. This paper will outline a social theory of the “smart city” by developing our Deleuzian concept of the “spectrum of control.” We present two illustrative examples: biometric surveillance as a form of monitoring, and automated policing as a particularly brutal and exacting form of manipulation. We conclude by offering normative guidelines for governance of the pervasive surveillance and control mechanisms that constitute an emerging critical infrastructure of the “smart city.”

scholarly journals The Digital Universe

2020 ◽  
Vol 2 (3) ◽  
pp. 9
Author(s):  
Matt Zwolenski ◽  
Lee Weatherill
Keyword(s):  
Sensor Networks ◽  
Information Security ◽  
Internet Of Things ◽  
Data Protection ◽  
Business Models ◽  
Unstructured Data ◽  
The Internet ◽  
Next Generation ◽  
The Internet Of Things ◽  
The Way

The Digital Universe, which consists of all the data created by PC, Sensor Networks, GPS/WiFi Location, Web Metadata, Web-Sourced Biographical Data, Mobile, Smart-Connected Devices and Next-Generation Applications (to name but a few) is altering the way we consume and measure IT and disrupting proven business models. Unprecedented and exponential data growth is presenting businesses with new and unique opportunities and challenges. As the ‘Internet of Things’ (IoT) and Third Platform continue to grow, the analysis of structured and unstructured data will drive insights that change the way businesses operate, create distinctive value, and deliver services and applications to the consumer and to each other. As enterprises and IT grapple to take advantage of these trends in order to gain share and drive revenue, they must be mindful of the Information Security and Data Protection pitfalls that lay in wait ─ hurdles that have already tripped up market leaders and minnows alike.

scholarly journals The Next Generation Internet of Things Architecture Towards Distributed Intelligence: Reviews, Applications, and Research Challenges

2020 ◽  
Author(s):  
Tanweer Alam ◽  
Baha Rababah ◽  
Rasit Eskicioglu
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Raw Data ◽  
Next Generation Internet ◽  
Distributed Intelligence ◽  
Research Challenges ◽  
Network Load ◽  
And Control ◽  
Edge Layer ◽  
The Internet Of Things

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.

scholarly journals Smart Monitoring and Control in the Future Internet of Things

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 27
Author(s):  
Franco Cicirelli ◽  
Antonio Guerrieri ◽  
Andrea Vinci
Keyword(s):  
Quality Of Life ◽  
Internet Of Things ◽  
Future Internet ◽  
The Internet ◽  
Monitoring And Control ◽  
The Future ◽  
And Control ◽  
The Internet Of Things

The Internet of Things (IoT) and related technologies are promising in terms of realizing pervasive and smart applications, which, in turn, have the potential to improve the quality of life of people living in a connected world [...]

scholarly journals IoT Masters Programs

2021 ◽  
pp. 53-57
Author(s):  
М.А. Держо ◽  
М.М. Лаврентьев ◽  
А.В. Шафаренко
Keyword(s):  
Internet Of Things ◽  
Cyber Security ◽  
Information Technologies ◽  
Systems Design ◽  
Team Development ◽  
The Internet ◽  
Development Effort ◽  
Applied Math ◽  
And Control ◽  
The Internet Of Things

В данной работе обсуждаются фундаментальные вопросы разработки программ магистратуры в области Интернета вещей (Internet of Things — IoT). Мы кратко сравниваем предложения Сколтеха и Стэнфорда и утверждаем, что наиболее гибкое решение достигается посредством вводного блока и четырех параллельных потоков учебных курсов: обработка сигналов и управление, обучение машин и искусственный интеллект (ИИ), программирование и схемотехника платформ с применением микроконтроллеров, и, наконец, сети и кибербезопасность. Вводный блок предполагается оснастить достаточным количеством предметов по выбору, чтобы поступающие выпускники бакалавриата из областей прикладной математики, информационных технологий и электроники/телекоммуникаций могли приобрести необходимые знания для освоения потоковых курсов. Мы утверждаем, что еще одним необходимым отличием программы IoT должен явиться междисциплинарный групповой дипломный проект значительного объема, также основанный на потоковых курсах. This paper discusses the fundamentals of postgraduate curriculum development for the area of the Internet of Things (IoT). We provide a brief contrasting analysis of Skoltech and Stanford Masters programs and argue that the most flexible way forward is via the introduction of a leveling-off, elective introductory stage, and four parallel course streams: signal processing and control; Artificial Intelligence (AI), and machine learning; microcontroller systems design; and networks and cyber security. The leveling-off stage is meant to provide sufficient electives for graduates of applied math, Information Technologies (IT), or electronics/telecom degrees to learn the necessary fundamentals for the stream modules. We argue that another distinguishing feature of an IoT masters program is a large project drawing on the stream modules and requiring a multidisciplinary, team development effort.

scholarly journals The Next Generation Internet of Things Architecture Towards Distributed Intelligence: Reviews, Applications, and Research Challenges

2020 ◽  
Author(s):  
Baha Rababah ◽  
Tanweer Alam ◽  
Rasit Eskicioglu
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Raw Data ◽  
Next Generation Internet ◽  
Distributed Intelligence ◽  
Research Challenges ◽  
Network Load ◽  
And Control ◽  
Edge Layer ◽  
The Internet Of Things

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.

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