Systematic Mapping

Systematic mapping studies rigorously analyze existing research literature to synthesize knowledge within a specific domain. Current research focuses on diverse applications, including real-time mapping in challenging environments (e.g., using SIFT features and GPU acceleration for visual SLAM), inferring complex relationships from textual data (e.g., using large language models to analyze psychotherapy sessions or patent documents), and automating anomaly detection in industrial settings (e.g., employing machine learning algorithms with IoT data). These studies provide valuable overviews of existing methodologies, identify research gaps, and inform the development of improved models and techniques across various scientific and engineering disciplines.