Hikmicro's AI algorithm detects leaks with thermal imaging technology

With SuperScene and SuperScene+, Hikmicro is bringing two advanced, AI-supported systems to industrial applications that automate inspection processes and sustainably improve operational safety. While conventional thermographic or acoustic inspection methods usually rely on manual evaluation and trained personnel, these new systems rely on intelligent algorithms that automatically detect and classify typical defect patterns and anomalies. SuperScene uses deep learning methods to analyze large volumes of infrared data and independently identifies signs of energy loss, air leaks or moisture ingress - for example in production halls, electrical systems or pipe systems. This technology helps to optimize operations, particularly in industrial infrastructures where energy efficiency, maintenance cycles and system availability are crucial. Its use not only reduces inspection effort and operating costs, but also improves the long-term reliability of technical systems.

SuperScene+ is tailored to demanding applications, especially for analyzing control panels and electronic assemblies. Using a combination of AI-supported image recognition, precise temperature difference analyses (Delta-T) and predefined inspection templates, sources of faults such as overloaded fuses, cold solder joints or overheated conductor tracks can be precisely identified. Micro temperature sensors detect differences of up to 0.5 °C. The automated zone analysis enables significantly faster testing, even for complex components. Color-coded warnings support technicians in making quick decisions and increase inspection quality. Both systems provide a clear example of how AI-supported diagnostics can contribute to standardization, increased efficiency and error prevention in the industry. SuperScene and SuperScene+ not only bring technological precision to everyday maintenance, but also make intelligent maintenance scalable and future-proof.