Bridging Domains with Artificial Intelligence and Machine Learning

Abstract

Human Activity Recognition (HAR), which automatically recognizes and categorizes human actions from sensor data, is influenced by Artificial Intelligence (AI) and Machine Learning (ML). This study examines HAR applications in healthcare, transportation, and smart homes, using AI and ML for activity recognition and analysis. In healthcare, AI enhances medical imaging, disease diagnosis, tailored medicine, and patient monitoring, improving outcomes and care provision. In transportation, AI revolutionizes autonomous vehicles, improving traffic flow, pedestrian detection, collision detection, and road safety. For smart homes, AI enables automation, anomaly detection, and energy efficiency, creating a safer and more comfortable living space. Future research in healthcare will focus on advanced ML models for integrating diverse medical data sources, such as genetics and wearable technology, to enable precision medicine and proactive care. In transportation, efforts will aim at developing autonomous vehicles that can manage challenging urban areas and inclement weather, paving the path for safer and more effective transportation systems. For smart homes, future research will focus on improving AI systems’ understanding of human preferences and behavior to deliver intuitive automation. This study intends to provide a thorough examination of the most recent advancements and research in these domains.