KSB Device Machine learning Research Section
The KSB Device Machine learning Research Section is performing R&D with the aim of developing and standardization of technologies that enable machine learning-based inference on the resource constrained devices such as light-weight devices, mobile devices, industrial gateways, resulting in applying to industrial domains.
Major R&D technologies include the IoE specialized Machine learning(ML)/Deep learning(DL) algorithm technology, the light-weight machine learning technology that can be mounted on the resource constrained devices, and the light-weight Machine learning/Deep learning standardization technologies. It also includes the development of the leak detection sensor in the plant domain and technologies for AI-based leak detection services such as data gathering, preprocessing, and Machine learning/Deep learning modeling.
⬥ Main Research Areas
- Development of ML/DL Algorithm Technology and Application of Industry
- Development of lightweight machine learning/reasoning technology with devices, and standardization and application of industry
- Development of plant piping leakage diagnostic sensor and artificial intelligence service
- Collecting data, pre-processing, and develops machine learning/deep learning models for the plant leakage diagnosis
Director HONG, Yong Geun