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Complex & Intelligent Systems - Special Issue on

Swarm and Evolutionary Intelligence for sensor and IoT-based large scale healthcare applications


IoT and Sensor Networks that includes bio sensors, chemical sensors, physical sensors have emerged as a very efficient and effective tool in the healthcare service sector as the integration of IoT devices with medical applications is expected to improve the quality of service. In the last two decades, IoT and Sensor Networks have been applied for various e-Health applications and thus improve the diagnostic tools.

Evolutionary and swarm intelligence has grown extensively and are quite effective for solving complex problems. In recent times with the emergence of sensor technology, cloud computing, and IoT platform there is a substantial change in the healthcare domain from many perspectives that includes monitoring, testing, diagnosis, prognosis. suggests treatment and follow up. The system has become quite complex in nature, and most of the solutions suffer from the drawbacks of inaccuracy, lack of convergence and exponential time complexity making it difficult for providing real-time solutions. Hence, these systems are generally replaced by intelligence based systems which are much superior to the conventional systems. Intelligent techniques are mostly hybrid in nature and include Artificial Neural Networks (ANN), fuzzy theory, evolutionary algorithms, swarm and memetic computing. Though most of the techniques have been proved to be quite sound both theoretically and empirically, the potential of these algorithms are not fully explored for practical applications like healthcare. IoT based healthcare system are now evolving and the present day research is slowly moving towards deployment and testing in large scale. Large scale deployment and testing leads to complex issues. Most of the algorithms are proved to be NP-Hard or complete problems and there do not exist any know polynomial time complexity algorithm for this. When the system becomes large the complexity increases exponentially. Swarm and Evolutionary algorithms have been proved to be quite effective in these type of scenarios. Researchers need to address the problem in totality instead of addressing the issues in isolation. 

This special issue will bring the scientific community working on all these areas for applications related to healthcare, to a common platform. 

Scope of the special issue

The goal of this Special Issue is to publish original manuscripts that address broad challenges on both theoretical and application aspects of intelligent algorithms like evolutionary intelligence, swarm intelligence, memetic computing, artificial intelligence in healthcare, biomedical, health informatics, medical imaging and processing, health advisory among few others. This Special Issue provides a good and unique platform to scholars and researchers to contribute original research articles as well as review articles that will showcase the continuous effort on the application of intelligent algorithmic approaches to solve eHealth and medical informatics problems using various sensors and IoT platform with a focus on complex large scale systems, energy aware computation. reliable communication involving patients, care givers, healthcare professionals, and healthcare administrators.

Recommended Topics

Topics to be discussed in this special issue include (but are not limited to) the following:

  • Evolutionary intelligence with focus on practical applications
  • Swarm and memetic computing for largescale computing system 
  • Bio-inspired computing and its applications on healthcare 
  • Sensors and IoT architectures for health monitoring
  • Assisted living IoT for active and healthy aging
  • Contactless sensing for healthcare and assisted living 
  • Interoperability and robustness of data for IoT-based eHealth system
  • Cyber-physical system infrastructure for eHealth system
  • Safety, Security, and Ethics in IoT-based eHealth system
  • Intelligent sensing technologies for eHealth system
  • Power-Aware green computing in sensor networks
  • Activity Recognition for Resource Management Capabilities
  • Crowd Sourcing for Ecological Pervasive Computing
  • Sustainable Systems with Deep Learning over Pervasive Intelligence
  • Scalable systems for data visualization
  • Deep learning and machine learning algorithms for Fog, Edge and Pervasive Computing
  • Eco-Friendly Pervasive Devices/Smart IoTs and RFIDs
  • Reliability and robust pervasive communications
  • Low Power Wearable Devices and IoT applications
  • Intelligent Optimization for large-scale mobile intelligence applications
  • Cloud, Fog and Edge computing for IoT-based eHealth system
  • Big Data Analytics based IoT technologies in eHealth system
  • e-Health Services and Applications using IoT-based eHealth system
  • Exploiting 5G/6G communication for IoT based eHealth System

Publication schedule (key dates)

Manuscript Submission Deadline: 15th November 2020
Initial Decision: 31st December 2020
Revised Manuscript Due: 31st February 2021
Decision Notification: 31st March 2021    
Final Manuscript Due: 15th April 2021



Guest Editors

1.    Prof. Suresh Chandra Satapathy  (Handling Editor)
Professor
School of Computer Science and Engineering
KIIT University, Orissa.
suresh.satapathyfcs@kiit.ac.in, sureshsatapathy@ieee.org

2.    Prof. Siba Kumar Udgata
Professor
School of Computer and Information Sciences
University of Hyderabad, India
Email: udgata@uohyd.ac.in

3.    Prof. Yu-Dong Zhang
Professor
School of Informatics
University of Leicester, UK
Email: yudongzhang@ieee.org


 

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