Dielectica traverses through the literature on this device – and summarizes as they appear.
Correspondence prepared by: Sayan Bayan, S. N. Bose National Centre for Basic Sciences, Kolkata, sayan.bayan@gmail.com (14th September, 2020 08:30 IST)
KOLKATA: In everyday life for most of the inhabitant purposes, handwriting based signatures are used to authenticate individuals to maintain security as well as privacy. However, the forgery signature based scams have emerged as a common ground behind many of the big losses in monetary transactions or other security matters in daily life applications. Thus, signature authentication via handwriting recognition is a key challenge and must be addressed by the scientific community seriously.
In this context, the research group of Prof. Zhong Lin Wang from the Georgia Institute of Technology, USA, has come up with a signature identification platform that has promising ability in security defense, and private information protection applications. According to the report recently published in the scientific journal ‘Nano Energy’, Prof. Wang and coworkers have demonstrated the handwriting recognition ability of a device called ‘triboelectric nanogenerator’ that runs without any external power supply.1 Prof. Wang is regarded as the inventor of triboelectric nanogenerator which works in the coupled principle of contact electrification and electrostatic induction.2 In such nanogenerator system, mechanical stimulus induces a current flow and can power up small electronic gadgets.
It is quite obvious that any kind of writing or drawing exerts mechanical pressure on the writing platform and such mechanical pressure can be used to generate electric power leading to a self-powered system. Further, the combination of signal processing and machine learning technologies with a triboelectric nanogenerator endows the ability to recognize the handwriting of different people. The research group has demonstrated that such self-powered writing pads can recognize writings of English words, Chinese characters as well as Arabic numerals with classification accuracies of 99.66%, 91.36% and 93.63%, respectively. It is expected such triboelectric nanogenerator based smart systems can play a vital role for protecting personal information in various segments of modern life in the near future.
Sources:
1Nano Energy 77 (2020) 105174. DOI: 10.1016/j.nanoen.2020.105174
2Nano Energy 1 (2012) 328. DOI: 10.1016/j.nanoen.2012.01.004