Hikvision’s “Guanlan” Models Power Next-Gen Traffic Incident Detection
As intelligent transportation systems rapidly evolve, the ability to accurately detect traffic incidents and improve response times is paramount. Enter Hikvision, with its new generation of traffic incident detection products, powered by the company’s “Guanlan” large-scale AI models. a&s China recently put these products to the test, and here’s what they found.
Comprehensive Coverage: From Edge to Backend
Hikvision’s new incident detection series offers a full suite of solutions, including the all-in-one radar-camera system (iDS-TCS802-HS-L), the incident detection camera (iDS-TCS800-H), and the incident detection terminal (iDS-TSS300-H) and server (iDS-TSS500-H).
The radar-camera system combines the best of both worlds: high-precision millimeter-wave radar and an 8-megapixel CMOS low-light camera. Designed for challenging weather conditions and complex environments, this system offers a range of intelligent functions, including parking violation detection, lane crossing/change recognition, and pedestrian monitoring. It can seamlessly switch between event detection, campus testing, and road warning modes, making it a versatile tool for various applications.
The incident detection camera is a robust 8-megapixel high-definition intelligent traffic camera built to withstand harsh conditions. Its industrial-grade metal body and modular structure ensure efficient heat dissipation and impact resistance, while its dustproof, waterproof, and surge-proof design makes it suitable for diverse traffic scenarios. Equipped with a starlight-grade sensor and intelligent fill-light technology, the camera captures clear images, including license plates, even at night. The camera’s built-in deep learning algorithm supports license plate recognition and full object structurization, enabling accurate detection of traffic events like lane crossing and wrong-way driving.
The incident detection terminal takes things a step further, supporting simultaneous connection to multiple cameras. It handles traffic incident detection, video quality diagnosis, and even road defect identification. This device can identify road damage like cracks and potholes, as well as detect anomalies such as damaged guardrails and missing traffic signs, significantly enhancing road safety.
At the core of the system is the incident detection server. Fueled by deep learning algorithms, the server can identify illegal parking, road damage, spilled objects, and more. It also collects traffic parameters, performs video structure analysis, and diagnoses video quality, making it ideal for managing complex urban traffic scenarios.
Unleashing the Power of “Guanlan”
Traditional traffic incident detection algorithms often struggle in complex situations, relying on manually labeled data and resulting in high false alarm rates, especially in rain or at night. Hikvision’s incident detection products overcome these limitations by leveraging the Transformer architecture under Guanlan, offering several key advantages:
1. **Global Feature Extraction:** Unlike traditional convolutional networks, the large-scale models based on the Transformer architecture provide more accurate identification of incidents such as spillage and illegal parking. They effectively filter out distractions like tree shadows, water stains, road markings, and signs. In parking detection, these models accurately differentiate between parked and slow-moving vehicles, using factors like dwell time and deviation from lane lines to minimize false positives.
2. **Multimodal Fusion Perception:** By integrating millimeter-wave radar and AI image processing technology, the radar-camera system can swiftly detect illegally parked vehicles and monitor motor vehicles within a 350-meter range.
3. **Continuous Algorithm Evolution:** The system supports pre-training of algorithms using industry knowledge. Tests have demonstrated that applying large-scale models significantly improves the accuracy of defect detection, such as identifying cracks and potholes.
Seamless Integration with New and Existing Infrastructure
Hikvision’s incident detection products support multiple protocols, including ISAPI, GB28181, and SDK, allowing for quick integration with mainstream platforms. The server supports on-demand expansion of storage and computing modules. Edge devices focus on real-time incident detection, while the backend handles multi-source data correlation, ensuring low-latency response times. The terminal/server seamlessly integrates with existing camera systems and storage devices, enabling the reuse of legacy resources. Whether for new projects or retrofitting existing systems, this series offers excellent compatibility and flexibility.
Key Product Features
1. The incident detection camera adapts to various installation requirements in complex traffic scenarios.
2. The all-in-one radar-camera system combines radar technology and high-definition video, achieving deep integration across a wide range of applications.
3. A single incident detection terminal can connect with multiple pre-installed cameras to meet dynamic monitoring needs in various use cases.
4. The incident detection server simultaneously implements traffic incident detection, traffic parameter collection, video quality diagnosis, road damage detection, and traffic facility damage detection.
5. The system seamlessly integrates with existing video surveillance systems and storage devices, enabling the reuse of legacy resources.
6. Based on the Transformer architecture of Hikvision’s Guanlan large-scale models, the products enable global feature modeling and radar and vision fusion perception, leading to accurate scene recognition and incident detection.
a&s Verdict
Hikvision’s new generation of traffic incident detection products, empowered by large-scale AI capabilities, are redefining intelligent transportation. As AI begins to truly “understand” roads, the entire paradigm of traffic management is being reshaped. Hikvision’s incident detection products demonstrate that large-scale AI models are indeed the future of smart transportation, driving traffic management from a reactive approach to active incident detection and prevention.