Call for Papers for the topics mentioned below :

• Domain-Specific Monitoring Applications:
  For Biomedical Systems: Deep learning for medical image/video analysis (e.g.,
  diagnostics, rehabilitation), AI-driven IoT for patient monitoring, biomedical

  instrumentation and signal processing.
  For Environmental Systems: Machine learning for species distribution modeling
  under climate change, acoustic/image-based monitoring of wildlife using sensor
  networks.
  Core Computational Intelligence Techniques:
  Image/Video & Signal Processing: Advanced computer vision and deep learning models for feature extraction, classification, and anomaly detection in both medical (e.g., MRI, X-ray) and ecological (e.g., camera trap, drone) imagery.
  Soft Computing & Optimization:Application of fuzzy logic, evolutionary algorithms, and swarm intelligence (PSO, ACO) for optimizing Wireless Sensor Network (WSN) deployment, energy efficiency, and data routing in remote monitoring scenarios.
  AI and Machine Learning: Development of hybrid and explainable AI models for
  predictive analytics, risk stratification (healthcare), and habitat suitability modeling
  (ecology).

  Cross-Cutting System Challenges:

  Cybersecurity for Monitoring Systems:Soft computing and AI-driven solutions for
  ensuring data privacy, integrity, and security in IoT-based biomedical and
  environmental networks.
  Optimization of Distributed Systems: Nature-inspired algorithms for enhancing the lifespan, coverage, and fault tolerance of WSNs and IoT devices deployed in
  challenging environments (e.g., dense forests, remote hospitals).
  Multi-modal Data Fusion: Integrating data from diverse sources (e.g., climatic
  variables with acoustic data, or patient vitals with medical imaging) using hybrid
  computational intelligence models.