Login / Signup

Flexible and durable wood-based triboelectric nanogenerators for self-powered sensing in athletic big data analytics.

Jianjun LuoZiming WangLiang XuAurelia Chi WangKai HanTao JiangQingsong LaiYu BaiWei TangFeng Ru FanZhong Lin Wang
Published in: Nature communications (2019)
In the new era of internet of things, big data collection and analysis based on widely distributed intelligent sensing technology is particularly important. Here, we report a flexible and durable wood-based triboelectric nanogenerator for self-powered sensing in athletic big data analytics. Based on a simple and effective strategy, natural wood can be converted into a high-performance triboelectric material with excellent mechanical properties, such as 7.5-fold enhancement in strength, superior flexibility, wear resistance and processability. The electrical output performance is also enhanced by more than 70% compared with natural wood. A self-powered falling point distribution statistical system and an edge ball judgement system are further developed to provide training guidance and real-time competition assistance for both athletes and referees. This work can not only expand the application area of the self-powered system to smart sport monitoring and assisting, but also promote the development of big data analytics in intelligent sports industry.
Keyphrases
  • big data
  • artificial intelligence
  • machine learning
  • cell wall
  • deep learning
  • health information
  • high school
  • social media