AI-Enabled Safe and Scalable Pet Care: An Intelligent System for Real Time Health Monitoring and Care

Modern pet health management requires advanced solutions because the world demonstrates rising demand for companion animals. The current pet care systems operate without real-time data monitoring because they do not adapt to shifting diagnostic criteria. An AI-powered pet management system based on Internet of Things (IoT) links a secure cloud-edge computing system to offer these capabilities. A proposed system depends on strong machine learning techniques to deliver persistent health tracking while simultaneously analyzing behavioral patterns and carrying out automatic care operations. Through its IoT-connected smart sensors the system obtains real-time data which enables it to identify anomalies as soon as possible while providing tailored medical solutions. A modular distributed architecture design offers better system adaptability thus making possible seamless operations between multiple operational domains. Security is of utmost importance in the system so a combination of encryption layers works together with authentication protocols and monitored data channels serve to secure both privacy and data integrity. The experimental findings reveal that predictions about behavioral outcomes together with optimized resource usage and system protection function at superior rates than traditional methods do. A thorough analysis of both ethical practices and data security measures exists for automated pet supervision to facilitate responsible program execution. This recommended system gives remote accessibility together with multi-functional pet care operations to provide safe services which benefit all pet owners along with veterinarians and additional stakeholders. The future research agenda includes developing hybrid federated learning systems to deliver individualised diagnoses as well as using diversified health data from various sources to conduct more thorough examinations while striving to enable this monitoring method in various animal care settings. Such research creates the foundation for future pet management systems controlled by AI-embedded IoT automation to enhance animal welfare and user-driven convenience.