Real-Time Data Acquisition in SCADA Systems: A JavaWeb and Swarm Intelligence-Based Optimization Framework

This paper aims to improve the accuracy and efficiency of SCADA software design and testing for oil and gas pipelines. It proposes a JavaWeb-based SCADA software solution optimized by the Bird Foraging Search (BFS) algorithm combined with an Echo State Network (ESN) for enhanced testing and analysis. A multi-tiered distributed SCADA software architecture based on the Java EE framework was designed to provide real-time data acquisition, monitoring, control, and data analysis. The BFS algorithm was used to optimize the hyperparameters of the ESN model to improve testing accuracy and convergence speed. The BFS-ESN model was compared with other optimization algorithms such as PSO and DE. Experimental results show that the BFS-ESN model achieved a testing accuracy of 97.33% and faster convergence within 700 iterations. It outperformed other algorithms in both accuracy and convergence speed. The JavaWeb-based SCADA software design for oil and gas pipelines is feasible, and the BFS-ESN model significantly enhances the accuracy and efficiency of SCADA software testing. This approach demonstrates the potential for application in SCADA systems, with future research needed to simplify the model and extend its applicability for large-scale deployment.

@article{Sun2024,
  title     = {Real-Time Data Acquisition in SCADA Systems: A JavaWeb and Swarm Intelligence-Based Optimization Framework},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {11},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Lingyi Sun and Tieliang Sun and Ruojia Xin and Feng Yan and Yue Li and Hengyu Wang and Yecen Tian and Dongqing You and Yun Liu and Muhao Lv},
  doi       = {10.14569/IJACSA.2024.0151152},
  url       = {https://doi.org/10.14569/IJACSA.2024.0151152}
}