Research

The laboratory has established an IoT-based health big data application platform by integrating big data from clinical practice, IoT terminals, and public health. This platform enables the analysis and prediction of chronic disease and maternal and infant health data.

This project is a National Key Research and Development Program project. The technologies used primarily involve multi-source data collaborative sensing, including: ① an adaptive composite filter based on hardware and software collaborative filtering; ② a biometric point extraction method based on dynamic thresholds; and ③ simplified calculations, suppression of dynamic noise interference, and ensuring data accuracy. Related results have been published in journals and conferences such as IEEE TII and IOTJ.

This achievement has won awards including the National Maker Competition Champion, the First Prize of the 9th Wu Wenjun Artificial Intelligence Science and Technology Progress Award, and the Second Prize of Guangdong Provincial Science and Technology Progress Award.