Intelligent transformation of engineering inspection, "Qican" seeks seed round financing
Founding Team and Development Blueprint
In the traditional engineering inspection industry, the transformation towards automation and intelligence has become an irreversible trend. Jiangsu Qican Technology Co., Ltd. emerged in response to this trend. The intelligent inspection and Internet of Things (IoT) solutions it launched are committed to driving the industry's shift from relying on manual experience to data - driven precise monitoring.
The project originated in response to the national call for vigorously developing new - quality productivity. Based on his more than ten - year in - depth accumulation in the field of geotechnical engineering, the founder, Sun Wei, keenly perceived the urgent need of the engineering inspection industry to improve efficiency and accuracy. Traditional inspection methods often suffer from low efficiency, limited accuracy, and data lag. Therefore, Sun Wei led the team to officially launch the project this year, aiming to provide more efficient and safe solutions for the industry by integrating cutting - edge technologies such as machine vision, IoT, and artificial intelligence.
Currently, the project is still in its initial stage of development, but the R & D of the core product has been successfully completed. The team has gathered professional talents from universities such as Nanjing Tech University and Zhejiang University. Among them, Dr. Mei Guoxiong, Sun Wei's tutor and a specially - appointed professor of the Changjiang Scholars Program, serves as a technical advisor. This R & D team composed of doctors and masters ensures the project's technical foundation and innovation vitality.
The unique technological advantage is the core competitiveness of the project. The self - developed machine vision displacement measurement system can achieve non - contact, high - precision real - time measurement of structures, effectively replacing traditional equipment such as levels and theodolites. Through artificial intelligence image recognition and sub - pixel processing technology, the system converts video data into accurate displacement data and realizes real - time data transmission and analysis through IoT technology. This solution can be widely applied to the automated monitoring of various engineering scenarios such as bridges, tunnels, slopes, and foundation pits.
In terms of market prospects, the engineering inspection industry has a large scale, and the replacement of traditional manual inspection by automation has become a clear trend. With the continuous expansion of the global machine vision market, applying advanced technologies to the engineering inspection field has broad development space. The project has a clear business model, mainly achieving profitability through selling intelligent monitoring instruments and equipment and providing subsequent inspection and analysis services.
Looking to the future, the company plans to accelerate technological iteration and market promotion through the first - round financing. The funds will be mainly used for R & D and production, talent introduction, and market expansion. The company's long - term strategy is to gradually establish a full - life - cycle database from design, construction to operation, and ultimately build an expert system in the field of engineering safety to provide solid technical support for ensuring the safety of urban infrastructure.
II. A comparative analysis of the machine vision displacement measurement system and traditional inspection equipment is as follows:
Accuracy: The machine vision displacement measurement system can achieve a displacement measurement accuracy of 0.1mm or even higher through high - resolution cameras (such as those with tens of millions of pixels) and sub - pixel algorithms. It can simultaneously measure horizontal displacement, settlement, and vibration frequency. In contrast, the static settlement measurement accuracy of a level is usually ±1mm, which is greatly affected by environmental temperature and liquid - level fluctuations. The angle measurement accuracy of a theodolite is about ±1" - ±5", and the calculation of horizontal displacement relies on trigonometric functions, resulting in relatively low indirect accuracy. Moreover, they need to be used in combination (such as using a level to measure height difference + a total station to measure coordinates).
Efficiency: The machine vision displacement measurement system has a millisecond - level response and supports continuous dynamic monitoring without manual intervention. A single shot can cover multiple measurement points. On the other hand, a level requires point - by - point leveling, and a theodolite requires multiple station transfers, which is time - consuming. The efficiency is affected by the operator's proficiency, and the number of daily measurement points is limited.
Cost: The machine vision displacement measurement system is an embedded all - in - one machine, which does not require an external industrial computer or gateway and is easy to install. Although the initial investment is high, the maintenance cost is low, making it suitable for projects with multiple measurement points (it has the best cost - performance ratio when there are more than 50 measurement points). In contrast, traditional inspection equipment has a complex system, requiring gateways, control cabinets, and line installation, and is troublesome to repair and maintain. The labor cost, wiring cost, and false - alarm cost increase with the expansion of the project scale. When there are many measurement points, the total cost of the machine vision system is lower than that of traditional equipment, and the long - term benefits are significant.
Market Scale of the Construction Engineering Inspection Industry
In 2025, the market scale of China's inspection industry exceeded 470 billion yuan, nearly doubling compared to 2020, with a compound annual growth rate of 12.4%. Among them, construction engineering inspection, as the leading segment, had an income scale of 76.194 billion yuan in 2023, accounting for 16.32% of the total revenue of inspection and testing services, and its average annual growth rate remained above 20%. With the popularization of technologies such as drone inspection and intelligent sensing devices, the proportion of automated inspection is expected to increase from less than 15% in 2022 to 25% in 2025. The main driving factors include mandatory policy requirements and the surging demand for the renovation of old buildings. It is predicted that the proportion of automation in the construction engineering inspection field will exceed 50% by 2030.