Smart computing platforms, developed using advanced technologies that integrate emotion recognition, data protection or threat intelligence analysis related to AI-driven cybersecurity have become key factors in the domains of human–machine interaction and affective computing. By evaluating and adapting this knowledge, the main goal of this work was to design and implement a smart system capable of real-time emotion recognition using high-performance imaging sensors and complex facial expression analysis algorithms. All data related to facial recognition and emotions analyses are categorized using convolutional neural networks and linked to a unique QR code assigned to each individual, providing data management and identity protection against cyber threats. The particularity of this work resides in the development and implementation of a device capable of performing multiple tasks with high-speed response, precision, and the ability to handle large volume of data. The anti-spoofing system detects and prevents fraudulent attempts of inappropriate individuals, successfully classifying emotions.