AI-driven Solution

We are dedicated to deeply integrating artificial intelligence into critical industrial and societal domains, developing intelligent solutions designed for the future. Nanotag Technology has established a specialized AI research and development team composed of leading scientists in artificial intelligence and experienced software engineers. This team is committed to advancing AI-driven solutions for industrial applications. Together, we have built a comprehensive R&D framework spanning AI-powered image recognition, sensor fusion, data security, and edge computing—laying the foundation for the next generation of applied AI in industry.

In the area of asset marking and identification, we are developing advanced multi-modal vision models based on deep convolutional neural networks (CNNs). These models are designed to accurately extract micro-structured codes—such as microdot identifiers and laser-etched IDs—across a variety of materials, curved surfaces, and complex backgrounds. This technology supports precise, scalable identification of physical assets throughout manufacturing, logistics, and supply chain environments, ensuring every item is uniquely and traceably tagged.

For anti-counterfeiting, we are building an AI-driven, multi-layered recognition and verification platform. Leveraging forensic imaging, fine-grained feature extraction, and time-series traceability algorithms, the system automatically analyzes and authenticates physical security elements such as encrypted micro-markings, protective layers, and covert laser engravings. We are also advancing “AI + encrypted tagging” technologies, embedding invisible structural data into product labels, packaging, documentation, and surfaces. This creates a strong link between physical products and their digital records, enabling remote verification, batch authentication, and risk analysis at scale—ideal for brand protection, regulatory compliance, and combating grey market activities.

In the field of asset protection and physical security, we are combining AI with robotics to create autonomous patrol and monitoring systems equipped with intelligent perception, real-time path planning, and automated response. These systems integrate high-precision visual analytics, LiDAR-based mapping, and multi-sensor data fusion to deliver 24/7 surveillance across factory floors, storage facilities, and secure perimeters. Our AI models are capable of detecting unusual behavior, unauthorized access, and object displacement in real time, triggering instant alerts and enabling remote intervention. We are also exploring AI-enhanced video sentry systems, designed to move beyond passive monitoring toward intelligent, predictive security infrastructure.

In healthcare and data privacy, we are developing AI models built with differential privacy mechanisms and federated learning architectures. These technologies enable secure and decentralized data processing, allowing AI to assist in diagnostics, health monitoring, and behavioral analysis—without exposing sensitive personal data. This approach is also being applied to intelligent eldercare, with non-contact monitoring systems that detect behavioral anomalies, provide fall alerts, and model physiological trends to improve quality of life and safety for aging populations.

We are actively investing in the next phase of these core AI technologies, with key R&D directions including model compression for lightweight deployment, edge AI architecture optimization, and adaptive sensor fusion across heterogeneous environments. Our goal is to deliver truly deployable, self-learning intelligent systems for the real world—empowering high-impact applications in manufacturing, anti-counterfeiting, healthcare, safety, and aging society support.