Optimization Methods for Adaptive and Dynamic Particle ‎Swarms for Accurate Real-Time Localization in Healthcare ‎Settings-A Comprehensive Survey - Ruxana, A.H.Jainab; Malathy , Dr. S. (International Journal of Basic and Applied Sciences, 2025)
Localization in healthcare facilities has the potential to enhance various medical treatments. Therefore, suitable enabling communication ‎technology is necessary for an accurate locating system in this setting. Unfortunately, many problems with commonly used technologies like ‎WiFi, Bluetooth, and RFID make them unsuitable for hospital localization. These problems include expensive implementation costs, weak ‎signals, inaccurate estimates, and possible interference with medical devices. This paper finds new solutions since existing technologies are ‎becoming more expensive to adopt and maintain and are not accurate enough for use in dynamic medical settings. To achieve precise control ‎over the robot’s movement, cutting-edge sensors and control systems are combined. The study and creation of a system known as ‎advancements in sensor technology and optimization of control algorithms accompany dynamic accuracy compensation. The fundamental ‎principle behind this paper is to obtain better operational precision by continuously adjusting the controller’s settings based on the real-time ‎data gathered by sensors.Particle Swarm Optimization (PSO) improves the model’s overall performance by fine-tuning the ‎hyperparameters.When it comes to life-saving equipment, this improved precision is crucial for meeting the requirement for exact ‎positioning in complex and ever-changing healthcare settings. The findings show that PSO makes the model much better, which gives a ‎solid foundation for building high-tech Healthcare localization systems. Compared to more traditional positioning techniques, the suggested ‎localization algorithm outperforms them in terms of localization error and location estimation‎.