Abstract: Children today confront a growing number of threats in both digital and physical surroundings, including exposure to dangerous content, cyberbullying, and exploitation. Traditional defenses are often inadequate due to the magnitude and complexity of modern threats. This study investigates how scalable, proactive, and intelligent protection solutions provided by artificial intelligence (AI) might enhance kid safety. The study's objectives are to identify AI-based child protection techniques, evaluate their effectiveness, and raise awareness of privacy and ethical concerns. The literature review, system architecture design, and analysis of current AI-driven child protection tools are all combined in a mixed-methods approach. We examine methods such as natural language processing for content filtering, computer vision for online interaction monitoring, and machine learning for behavior prediction.

Downloads: | DOI: 10.17148/IJIREEICE.2025.131005