ZhuoShi ZhiTong completed tens of millions of Pre-B+ financing, and AI vision big model broke through

China's intelligent transportation industry is developing rapidly, and it is expected to reach a trillion-level scale in 2025. Against the backdrop of accelerated iterations of multiple key technologies such as sensors , communications, and cloud computing, computer vision technology is at a crossroads where opportunities and challenges coexist. Whoever can break through the bottleneck of algorithm technology and achieve accurate intelligent perception of traffic scenes will be able to seize this trillion-level blue ocean.

Recently, ZhuoShi ZhiTong, one of the earliest enterprises in my country to deploy the industrialization application of computer vision technology, announced the completion of tens of millions of yuan in Pre-B+ round of financing. It is reported that this round of financing was jointly invested by CCCC Capital and Tengfei Capital, and the funds will be mainly used for market expansion, AI polishing and other technology research and development, AI training platform construction, and the upgrade and expansion of intelligent manufacturing production bases.

Founded in 2012, ZhuoShi ZhiTong can be regarded as a "veteran" in the field of computer vision in China. Over the past decade, the company has undergone a transformation from technology accumulation to commercial application, and its artificial intelligence technology has also completed the iterative upgrade from traditional pattern recognition to deep learning and then to large models.

Computer vision drives smart transportation

Unlike most visual startups of the same period, ZhuoShi ZhiTong has been targeting the transportation field from the beginning, and has taken the road side rather than the vehicle side as its entry point. By integrating multi-source data, it can achieve accurate perception of vehicles, roads, people and the environment, and provide digital traffic management tools for road management departments and regulatory units.

At present, the company has mastered technologies such as video vehicle detection, pedestrian recognition, and traffic anomaly time detection, and has formed a software product matrix represented by traffic event detection and digital twin highway system "Yunying", vehicle multi-dimensional feature recognition and structured recognition system "Yunxi", and city-level traffic management big data platform "Yuntong"; as well as integrated hardware product lines such as toll vehicle model recognition all-in-one machine "Xiaoshentong", dual-spectrum radar and vision fusion perception all-in-one machine "Atongmu", and tunnel intelligent robot "Feian".

Video image analysis is the core of intelligent transportation. Through the image recognition and understanding of road vehicles, pedestrians, and road conditions, it can realize functions such as traffic condition monitoring, event detection, and violation identification, making traffic management more refined, intelligent, and digital.

Traffic scenes are complex and changeable, and it is difficult for traditional algorithms to achieve a high recognition accuracy. With the advancement of deep learning and model computing technology, computer vision has ushered in a major breakthrough - the arrival of the era of large models, which can improve the recognition accuracy of complex scenes and unlock more innovative applications, and is expected to solve the "last mile" problem of image understanding.

Visual AI enables smart supervision

Digital twin is an important aspect of smart city construction. It uses virtual digital space to reflect and predict the physical transportation system with high precision, thus achieving the maximum digitalization of traffic management.

Building a digital twin system requires capabilities such as high-precision maps, accurate detection, and vehicle trajectory prediction, all of which require the support of visual AI, especially the accurate identification and positioning of traffic targets.

On the one hand, visual sensors such as cameras can cover all vehicles on the road, conduct behavior analysis and violation detection, and ensure traffic safety and management. On the other hand, digital models of vehicles and participating objects are established to conduct simulations in various scenarios and evaluate the operating status of the traffic system.

In the future, the digital twin system can also be combined with metaverse technology to assist traffic management through virtual-reality interaction, achieving immersive monitoring experience and decision-making support.

Seizing the strategic opportunity of visual AI

It can be seen that visual AI has become a key force in promoting intelligent transportation. It has greatly expanded the boundaries of image recognition and made in-depth understanding of complex traffic scenes possible.

Visual AI has become a battleground for promoting the digitalization and intelligence of transportation. It is leading a new chapter in the evolution of sensor technology and bringing revolutionary progress in smart traffic management. Relevant companies should follow the trend, increase investment in the research and development of visual AI algorithms, continuously improve the technical level, and actively expand application scenarios so that products can cover more aspects of traffic management and seize the vast market.