Xinghan

What Is Dahua Xinghan?

Xinghan refers to a range of Large-Scale AI Models from Dahua that provide advanced analytics capabilities for complex surveillance scenarios. These models are deployed in selected Dahua systems and expand conventional video analytics with more powerful, context-aware intelligence. Dahua distinguishes between Vision, Multimodal, and Language Models, which are made available on different system components such as cameras or recorders depending on the intended application.

Dahua Xinghan Large-Scale AI Model 2.0: Vision, Multimodal and Language

Vision (V-Series) – Vision-Centric AI for Precise Detection

• Perimeter Protection: Reliable perimeter monitoring and intrusion detection, even under challenging conditions.
• WizTracking: Real-time tracking of objects or people for enhanced security.
• Crowd Map: Analysis and visualisation of crowds to support traffic and security management.
• Scene Self-Adaptation (SSA): Automatic adaptation of surveillance parameters to changing environmental conditions.

Multimodal (M-Series) – Intelligent Fusion for Comprehensive Solutions

• WizSeek: Rapid retrieval of visual data through text-based queries.
• Text-Defined Alarms: Automated alarms triggered by text descriptions or predefined rules.

Language – Natural Language Understanding for Intelligent Control

The integrated language models enable natural language processing for automated reporting, rule verification, and interactive control. They analyse text commands and defined requirements, convert them into actionable instructions, and support seamless communication between humans and machines.

What Practical Benefits Do Dahua Xinghan Technologies Offer?

Dahua’s Xinghan models combine multiple technological capabilities designed to efficiently process complex surveillance footage, deliver enhanced situational understanding, and enable a broader range of practical applications.

• High-Precision Processing of Large Data Volumes delivers reliable results even in complex real-world environments, with fewer false alarms and more actionable outputs.
• Real-Time Monitoring of Dynamic Scenes enables continuous observation and evaluation of changing environments, with self-learning optimisation that can adapt to different deployment conditions and user requirements.
• Unified Model Architecture replaces fragmented task-specific AI models with a scalable framework that shortens development cycles and avoids repeated system rebuilds.
• Multimodal Perception extends beyond purely visual processing, providing deeper real-time understanding of behaviour, context, and operational activity.
• Deeply Integrated Industry Knowledge combines visual and numerical data for more precise multimodal coordination and turns complex workflows into orchestrated closed-loop AI processes.

Xinghan models are deployed across a range of industrial environments where large volumes of data need to be processed in real time. In smart traffic applications, for example, they can simultaneously identify traffic build-ups, wrong-way driving, and traffic violations, while in industrial parks and energy facilities they are used to monitor security zones, detect unauthorised access, and monitor critical operating conditions. In sectors such as mining or public safety, they also support the protection of large-scale areas through early detection of people in hazardous zones, unusual movement patterns, and other potential safety risks.