Year: 2025
Type: article
Abstract: Traditional surveillance systems are becoming inadequate for modern security and health monitoring needs. This survey explores the integration of AI and ML in next-generation CCTV systems, transforming them from passive monitors to intelligent, proactive solutions. Key advancements include biometric authentication for secure identification, behavior analysis for detecting suspicious activities, and health monitoring for emergencies like falls or medical distress. To address privacy concerns, the study reviews encryption, data anonymization, and customizable monitoring parameters to ensure compliance with ethical standards. Using real-time analytics and adaptive designs, AI-driven surveillance is reshaping security and healthcare in public spaces, workplaces, and medical environments, fostering safer communities while respecting privacy.
Institution: B.M.S. College of Engineering
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4412475903