scholarly journals ADLAuth: Passive Authentication Based on Activity of Daily Living Using Heterogeneous Sensing in Smart Cities

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2466 ◽  
Author(s):  
Maryam Naseer Malik ◽  
Muhammad Awais Azam ◽  
Muhammad Ehatisham-Ul-Haq ◽  
Waleed Ejaz ◽  
Asra Khalid
Keyword(s):  
Internet Of Things ◽  
User Authentication ◽  
Smart Cities ◽  
Activity Patterns ◽  
Wearable Sensors ◽  
Machine Learning Algorithms ◽  
Smart Devices ◽  
The Internet ◽  
Healthcare Applications ◽  
The Internet Of Things

The Internet of Things is a rapidly growing paradigm for smart cities that provides a way of communication, identification, and sensing capabilities among physically distributed devices. With the evolution of the Internet of Things (IoTs), user dependence on smart systems and services, such as smart appliances, smartphone, security, and healthcare applications, has been increased. This demands secure authentication mechanisms to preserve the users’ privacy when interacting with smart devices. This paper proposes a heterogeneous framework “ADLAuth” for passive and implicit authentication of the user using either a smartphone’s built-in sensor or wearable sensors by analyzing the physical activity patterns of the users. Multiclass machine learning algorithms are applied to users’ identity verification. Analyses are performed on three different datasets of heterogeneous sensors for a diverse number of activities. A series of experiments have been performed to test the effectiveness of the proposed framework. The results demonstrate the better performance of the proposed scheme compared to existing work for user authentication.

scholarly journals Smart Cities using Internet of Things: Recent Trends and Techniques

2019 ◽  
Vol 8 (9S) ◽  
pp. 24-28
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Wearable Sensors ◽  
The Internet ◽  
Human Beings ◽  
Smart Building ◽  
Recent Trends ◽  
The Internet Of Things ◽  
Smart Infrastructure

A Smart Cities focuses on the way we live. Smart governments are also acknowledged as augmentations of electronic governments based on the Internet of Things (IoT). There are many existing challenges in the environment such as, research in gadgets, framework and programming etc. Particularly, the Smart Cities are facing difficulties with IoT frameworks, systems administration, independent registration, wearable sensors, gadgets and systematization of aggregates including human beings as well as programming specialists. This paper incorporates role of Smart Cities in various domains such as smart infrastructure, smart building, smart security and so on. Moreover, the work depicts the IoT technologies for Smart Cities and the primary components along with the features of Smart Cities. This paper is based on technologies for Smart Cities which will benefit citizens by facilitating a platform for integrating all the resources and prompt communication of information. Furthermore, merits, demerits and main challenges of Smart Cities are discussed.

Artificial Intelligence powered Internet of Things and smart public service

2019 ◽  
Vol 38 (1) ◽  
pp. 165-179 ◽  
Author(s):  
Ying Ma ◽  
Kang Ping ◽  
Chen Wu ◽  
Long Chen ◽  
Hui Shi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Public Service ◽  
Smart Cities ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Content Type ◽  
Academic Fields ◽  
The Internet Of Things

Purpose The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent years as well. AI naturally combines with the Internet of Things in various ways, enabling big data applications, machine learning algorithms, deep learning, knowledge discovery, neural networks and other technologies. The purpose of this paper is to provide state of the art in AI powered IoT and study smart public services in China. Design/methodology/approach This paper reviewed the articles published on AI powered IoT from 2009 to 2018. Case study as a research method has been chosen. Findings The AI powered IoT has been found in the areas of smart cities, healthcare, intelligent manufacturing and so on. First, this study summarizes recent research on AI powered IoT systematically; and second, this study identifies key research topics related to the field and real-world applications. Originality/value This research is of importance and significance to both industrial and academic fields researchers who need to understand the current and future development of intelligence in IoT. To the best of authors’ knowledge, this is the first study to review the literature on AI powered IoT from 2009 to 2018. This is also the first literature review on AI powered IoT with a case study of smart public service in China.

scholarly journals Usages of Spark Framework with Different Machine Learning Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Mohamed Ali Mohamed ◽  
Ibrahim Mahmoud El-henawy ◽  
Ahmad Salah
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Internet Of Things ◽  
Large Data ◽  
Machine Learning Algorithms ◽  
Smart Devices ◽  
The Internet ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
The Internet Of Things

Sensors, satellites, mobile devices, social media, e-commerce, and the Internet, among others, saturate us with data. The Internet of Things, in particular, enables massive amounts of data to be generated more quickly. The Internet of Things is a term that describes the process of connecting computers, smart devices, and other data-generating equipment to a network and transmitting data. As a result, data is produced and updated on a regular basis to reflect changes in all areas and activities. As a consequence of this exponential growth of data, a new term and idea known as big data have been coined. Big data is required to illuminate the relationships between things, forecast future trends, and provide more information to decision-makers. The major problem at present, however, is how to effectively collect and evaluate massive amounts of diverse and complicated data. In some sectors or applications, machine learning models are the most frequently utilized methods for interpreting and analyzing data and obtaining important information. On their own, traditional machine learning methods are unable to successfully handle large data problems. This article gives an introduction to Spark architecture as a platform that machine learning methods may utilize to address issues regarding the design and execution of large data systems. This article focuses on three machine learning types, including regression, classification, and clustering, and how they can be applied on top of the Spark platform.

scholarly journals ARTIFICIAL INTELLIGENCE AS A SERVICE IN DISTRIBUTED MULTI ACCESS EDGE COMPUTING ON 5G EXTRACTING DATA USING IOT AND INCLUDING AR/VR FOR REAL-TIME REPORTING

2021 ◽  
Vol 9 (1) ◽  
pp. 912-931
Author(s):  
Pavan Madduru
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Virtual Machines ◽  
Smart Cities ◽  
Assistive Technologies ◽  
Edge Computing ◽  
Smart Devices ◽  
The Internet ◽  
Iot Applications ◽  
The Internet Of Things

To meet the growing demand for mobile data traffic and the stringent requirements for Internet of Things (IoT) applications in emerging cities such as smart cities, healthcare, augmented / virtual reality (AR / VR), fifth-generation assistive technologies generation (5G) Suggest and use on the web. As a major emerging 5G technology and a major driver of the Internet of Things, Multiple Access Edge Computing (MEC), which integrates telecommunications and IT services, provides cloud computing capabilities at the edge of an access network. wireless (RAN). By providing maximum compute and storage resources, MEC can reduce end-user latency. Therefore, in this article we will take a closer look at 5G MEC and the Internet of Things. Analyze the main functions of MEC in 5G and IoT environments. It offers several core technologies that enable the use of MEC in 5G and IoT, such as cloud computing, SDN / NFV, information-oriented networks, virtual machines (VMs) and containers, smart devices, shared networks and computing offload. This article also provides an overview of MEC's ​​role in 5G and IoT, a detailed introduction to MEC-enabled 5G and IoT applications, and future perspectives for MEC integration with 5G and IoT. Additionally, this article will take a closer look at the MEC research challenges and unresolved issues around 5G and the Internet of Things. Finally, we propose a use case that MEC uses to obtain advanced intelligence in IoT scenarios.

Analysis of Internet of Things Based on Characteristics, Functionalities, and Challenges

2021 ◽  
Vol 5 (1) ◽  
pp. 44-62
Author(s):  
Ganesh Khekare ◽  
Pushpneel Verma ◽  
Urvashi Dhanre ◽  
Seema Raut ◽  
Ganesh Yenurkar
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Fog Computing ◽  
Smart Devices ◽  
The Internet ◽  
Private Companies ◽  
Internet Availability ◽  
Near Future ◽  
The Internet Of Things

The internet of things (IoT) is transpiring technology. In the last decade, demand of IoT has been increased due to various things like the use of smart devices; increased demand for voice-based services; the concept of smart cities has been evolved; more requirements of processed data in fields of artificial intelligence and machine learning; fog computing, deep learning, etc. IoT is expected to reach the milestone of 30 billion IoT units at the end of the year 2020. Internet of things is the network of statutory things like houses, private companies, automobiles, and various objects integrated with sensors, actuators, software, electronic equipment, and internet availability that provides the facility to devices to interchange their data. The main contribution of this article is to provide state of art about the characteristics, functionalities, and challenges of the internet of things and the journey of IoT right from start to how it will make an impact on people's quality of life throughout the world in the near future.

scholarly journals A State of the Art Survey of Machine Learning Algorithms for IoT Security

2021 ◽  
pp. 12-34
Author(s):  
Alan Fuad Jahwar ◽  
Subhi R. M. Zeebaree
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Smart Cities ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Security Measures ◽  
Iot Security ◽  
Security Issues ◽  
The Internet Of Things

The Internet of Things (IoT) is a paradigm shift that enables billions of devices to connect to the Internet. The IoT's diverse application domains, including smart cities, smart homes, and e-health, have created new challenges, chief among them security threats. To accommodate the current networking model, traditional security measures such as firewalls and Intrusion Detection Systems (IDS) must be modified. Additionally, the Internet of Things and Cloud Computing complement one another, frequently used interchangeably when discussing technical services and collaborating to provide a more comprehensive IoT service. In this review, we focus on recent Machine Learning (ML) and Deep Learning (DL) algorithms proposed in IoT security, which can be used to address various security issues. This paper systematically reviews the architecture of IoT applications, the security aspect of IoT, service models of cloud computing, and cloud deployment models. Finally, we discuss the latest ML and DL strategies for solving various security issues in IoT networks.

scholarly journals Internet of Things Challenges and Opportunities

2020 ◽  
Author(s):  
Deekshaa Khanna
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Operating Mode ◽  
Smart Devices ◽  
The Internet ◽  
Huge Amount ◽  
Challenges And Opportunities ◽  
Smart Cars ◽  
Cloud Technologies ◽  
The Internet Of Things

Technology is evolving rapidly, and cheaper and smaller devices that vary in size, computational power using cloud technologies or operating mode become available. These devices are always connected to form a network in order to enhance communication and data transmission. Such devices are largely referred to as smart devices e.g., smart homes, smart cities, smart cars, etc. that are connected to a complex infrastructure known as the Internet of things. Internet of Things generates a huge amount of data that poses significant challenges for processing and analysis. This research paper outlines various challenges and opportunities that are in the field of the Internet of Things.

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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