Industrial Videoscope Optimisation: Software Architecture Improvements, Implementation of OTA and Edge AI

Vadim Shilov


By Vadim Shilov,

Head of the Video Streaming Unit at Promwad 

Project in Nutshell: We helped our client launch their product, an industrial videoscope, into mass production and bring it to market on time. In a tight timeframe, we improved the software architecture to resolve spontaneous reboot and video stream freezing. In addition, we implemented OTA (over-the-air) updates to reduce maintenance and operating costs by up to 30%. 

Client & Challenge 

A provider of industrial inspection equipment asked us to fix a malfunction of a camera-based inspection system to move it to mass production in 3 months. The software developed by our client's partner was not production ready due to the following issues with the device: 

  • The application stopped after approximately 30 minutes of continuous use. 
  • The device spontaneously rebooted. 
  • The video quality deteriorated after prolonged use, with its interference shaking or freezing.


Recognising the urgency of the client's situation, we quickly allocated a dedicated team of three developers and a circuit design engineer. Our experts determined that although the hardware components were designed correctly, the main problem was on the software side of the camera-based vision system. 

Our problem-solving strategy was to work in three directions: 

  • Software optimisation. We addressed weaknesses in the software architecture by reorganising module communications and simplifying code organisation. We optimised data processing by using algorithms that are more efficient for the platform. This resulted in reduced CPU power consumption and levelled out the device performance.
  • Implement over-the-air (OTA) updates. With the new feature, devices can receive updates wirelessly, eliminating the need for physical connection or manual installation.
  • Improving functionality. Having discovered that the SoC manufacturer released a new SDK version with edge AI algorithms, we leveraged it to improve video quality and implement advanced noise reduction.

Bussines Value 

We solved critical problems with the software and expanded the capabilities of the industrial videoscope in a tight timeline. Thanks to timely improvements, our client launched mass production on time and brought the product to market as planned. 

By fixing problems in the architecture, we improved the device performance:

  • Implemented a noise cancellation feature based on AI algorithms.
  • Eliminated software failures: the overall failure rate was reduced to 1% during 12 hours of continuous operation.
  • Implemented OTA updates, reducing the need to update the system's software components manually. In addition, over-the-air firmware updates have reduced maintenance and operating costs by up to 30%. 

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