Special Issues

Intelligent Systems for Diversified Application Domains

Submission Deadline: 20 February 2023 (closed) View: 36

Guest Editors

Dr. Sita Rani, Gulzar Group of Institutions, India.
Dr. J.P.C. Rodrigues, Federal University of Piaui ( UFPI), Portugal.
Dr. Ashish Khanna, Maharaja Agrasen Institute of Technology, India.

Summary

In the current era, we are surrounded by intelligent systems and machines. Due to rapid development, these systems have captured almost every sphere of day-to-day life. These are specialized technologically developed models that observe and reciprocate to the surrounding environment. The most dominating technology of the time, i.e., Artificial Intelligence is playing a significant role in the design of intelligent systems. But they are conflux of other subject area too likewise Machine Learning, Deep Learning, Algorithms, Numerical Methods, Pattern Recognition, Data Analytics, and Data Structures. Along with, IoT-based smart applications and models also contribute enormously in the development of intelligent machines. The fundamental aim of these systems is to communicate with human users and other peer-systems in highly evolving and dynamic phenomenal and social environment. Robots are one of the common examples of intelligent systems that can observe, make decisions, and work accordingly to complete the tasks in the physical environment. Intelligent systems and models have been deployed in a variety of domains like Healthcare, Intelligent Transportation, Avionics, Surveillance, Education, Industry 5.0, Entertainment, and Agriculture. Uncertainty about the gathered information and decisions, high degree of dynamism, high time complexity, and mapping of data/information from one format to another are soma of the major challenges faced the design and development of these systems.

 

This special issue is aimed to bring together the research and state-of-art review papers on algorithms, technologies, challenges, and possible future research directions in the design and development of intelligent models and systems in diversified application domains, broadly any paper presenting new development in the in the area of intelligent systems.

 

The main topics focused under this special issue include (but not limited to) the following:

 

• Algorithms and Technologies in the Design of Intelligent Systems

• Intelligent Applications in Smart Agriculture

• Intelligent Models and Systems for Healthcare

• Artificial Intelligence and Image Processing in Disease Diagnosis

• Design and Deployment of Efficient Intelligent Educational Models

• Design of Intelligent Transportation System to Administer Traffic Challenges

• Intelligent Systems and Applications in Industrial Automation

• Intelligent Systems for Big Data Analytics

• Design and Implementation of Intelligent Avionics Systems

• Design and Deployment Challenges in Intelligent Systems


Keywords

Artificial Intelligence, Agriculture, Avionics, Big Data Analytics, Healthcare Industry 5.0, Intelligent Systems, Internet of Things, Machine Learning.

Published Papers


  • Open Access

    ARTICLE

    Point Cloud Based Semantic Segmentation Method for Unmanned Shuttle Bus

    Sidong Wu, Cuiping Duan, Bufan Ren, Liuquan Ren, Tao Jiang, Jianying Yuan, Jiajia Liu, Dequan Guo
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2707-2726, 2023, DOI:10.32604/iasc.2023.038948
    (This article belongs to the Special Issue: Intelligent Systems for Diversified Application Domains)
    Abstract The complexity of application scenarios and the enormous volume of point cloud data make it difficult to quickly and effectively segment the scenario only based on the point cloud. In this paper, to address the semantic segmentation for safety driving of unmanned shuttle buses, an accurate and effective point cloud-based semantic segmentation method is proposed for specified scenarios (such as campus). Firstly, we analyze the characteristic of the shuttle bus scenarios and propose to use ROI selection to reduce the total points in computation, and then propose an improved semantic segmentation model based on Cylinder3D,… More >

  • Open Access

    ARTICLE

    Predicting Lumbar Spondylolisthesis: A Hybrid Deep Learning Approach

    Deepika Saravagi, Shweta Agrawal, Manisha Saravagi, Sanjiv K. Jain, Bhisham Sharma, Abolfazl Mehbodniya, Subrata Chowdhury, Julian L. Webber
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2133-2151, 2023, DOI:10.32604/iasc.2023.039836
    (This article belongs to the Special Issue: Intelligent Systems for Diversified Application Domains)
    Abstract Spondylolisthesis is a chronic disease, and a timely diagnosis of it may help in avoiding surgery. Disease identification in x-ray radiographs is very challenging. Strengthening the feature extraction tool in VGG16 has improved the classification rate. But the fully connected layers of VGG16 are not efficient at capturing the positional structure of an object in images. Capsule network (CapsNet) works with capsules (neuron clusters) rather than a single neuron to grasp the properties of the provided image to match the pattern. In this study, an integrated model that is a combination of VGG16 and CapsNet… More >

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