Special Issue "Future Generation of Artificial Intelligence and Intelligent Internet of Things"

Submission Deadline: 15 November 2021 (closed)
Guest Editors
Dr. Rajesh Kaluri, Vellore Institute of Technology, India.
Dr. Dharmendra Singh Rajput, Vellore Institute of Technology, India.
Dr. Thippa Reddy G, Vellore Institute of Technology, India.
Dr. Celestine Iwendi, Higher education Academy United Kingdom Bangor College China/Bangor University, United Kingdom.


Artificial Intelligence expands the livelihood of every human with ease. It mainly helps the people who are visually impaired, deaf & dumb, and old age people. It is been widely used with the Internet of Things and making all the works much simpler and creating smart environments. The ability to learn the convolutional methods of Artificial Intelligence brought many benefits to the Internet of Things (IoT). A new wave of IoT devices will bridge the gap between the physical and digital world to improve the quality and productivity of human life, society, and industries.
The potential of AI and IoT is impacting all the sectors from making smart homes to launching a rocket. Research in this area is basically focused on the ability to develop intelligent systems capable of interacting with the devices among themselves without human intervention. A recent survey mentions that “IoT smart objects are expected to reach 314 billion entities deployed globally by the end of 2022”. Similarly, while the number of connected devices already exceeds the number of humans on the planet by over 2 times, for most enterprises, simply connecting their systems and devices remains the first priority.
Artificial Intelligence and the Internet of Things are at the forefront of technological advances that represent a potential transformational mega-trend. The technologies, frameworks of AI-based IoT and their associated management paradigm are already rapidly impacting many industries. Moreover, Artificial Intelligence marks the IoT as an Intelligent system in the numerous applications Industrial Internet, Logistics and Supply Chain Management Systems, Health care, Education, automotive digital technology, and Inventory Management.

• This special issue will aim to bring the complete exploration of the past and current frameworks of the Internet of Things which are applied with Artificial Intelligence techniques.
• It aims to gather recent research works in emerging artificial intelligence methods for processing and storing the data generated from the Internet of Things.
• It provides detailed coverage of the applications, techniques, algorithms, platforms, and tools from the Internet of Things and AI systems.
• Improvement of a marketplace for applications and services to foster an IoT ecosystem.

• Artificial intelligence in expert systems
• Revolution of Industry 4.0 to Industry 5.0
• Internet of Nano Things (IoNT)
• Industrial Internet of Things (IIoT)
• Internet of Medical Things (IoMT)
• Soft computing techniques in IoT based AI systems
• Next-generation enterprise systems
• Interoperability Development Testing of IoT
• Security and privacy issues in IoT AI systems
• Smart Agriculture using IoT
• IoT in Smart Healthcare
• IoT in Smart Robotics
• Smart Learning Management System & Technology
• IoT for Blockchain and Bitcoin
• Artificial Intelligence in Cloud-based IoT
• Machine Learning for Internet of Things
• Fuzzy Systems for the Internet of Things
• Deep Learning for Internet of Things
• Future challenges and applications of Intelligent IOT based AI

Published Papers
  • Attention-Based Deep Learning Model for Early Detection of Parkinson's Disease
  • Abstract Parkinson's disease (PD), classified under the category of a neurological syndrome, affects the brain of a person which leads to the motor and non-motor symptoms. Among motor symptoms, one of the major disabling symptom is Freezing of Gait (FoG) that affects the daily standard of living of PD patients. Available treatments target to improve the symptoms of PD. Detection of PD at the early stages is an arduous task due to being indistinguishable from a healthy individual. This work proposed a novel attention-based model for the detection of FoG events and PD, and measuring the intensity of PD on the… More
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  • Generating Type 2 Trapezoidal Fuzzy Membership Function Using Genetic Tuning
  • Abstract Fuzzy inference system (FIS) is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs. The system starts with identifying input from data, applying the fuzziness to input using membership functions (MF), generating fuzzy rules for the fuzzy sets and obtaining the output. There are several types of input MFs which can be introduced in FIS, commonly chosen based on the type of real data, sensitivity of certain rule implied and computational limits. This paper focuses on the construction of interval type 2 (IT2) trapezoidal shape MF from fuzzy C Means (FCM) that is used for… More
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  • Comparative Study of Transfer Learning Models for Retinal Disease Diagnosis from Fundus Images
  • Abstract While the usage of digital ocular fundus image has been widespread in ophthalmology practice, the interpretation of the image has been still on the hands of the ophthalmologists which are quite costly. We explored a robust deep learning system that detects three major ocular diseases: diabetic retinopathy (DR), glaucoma (GLC), and age-related macular degeneration (AMD). The proposed method is composed of two steps. First, an initial quality evaluation in the classification system is proposed to filter out poor-quality images to enhance its performance, a technique that has not been explored previously. Second, the transfer learning technique is used with various… More
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  • Handover Mechanism Based on Underwater Hybrid Software-Defined Modem in Advanced Diver Networks
  • Abstract For the past few decades, the internet of underwater things (IoUT) obtained a lot of attention in mobile aquatic applications such as oceanography, diver network monitoring, unmanned underwater exploration, underwater surveillance, location tracking system, etc. Most of the IoUT applications rely on acoustic medium. The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate, attenuation, limited bandwidth, limited battery, limited memory, connectivity problem, etc. One of the significant applications of IoUT include monitoring underwater diver networks. In order to perform a reliable and energy-efficient… More
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