Doctor unpredicted prescription handwriting prediction using triboelectric smart recognition

AbstractAbstractBackground Handwriting digits and character recognition have become more important in the digitized world due to the practical applications and to pass information. Different recognition systems have been developed and proposed to be used in different fields where high classification efficiency is needed. Still, there has the issue of lowering the recognition rate.Aim The main objective of this study is to construct an energy-efficient IoT model for doctor unpredicted prescription handwriting prediction that allows the medical words for recognition system to ensure efficient medicine service with the help of a smart recognition system.Methods The integration of IoT for recognizing handwriting characters is more efficient and robust than other techniques. This approach of proposing and constructing an energy-efficient model for doctor unpredicted prescription handwriting prediction allows medical word recognition with the help of triboelectric smart recognition.Results The result yields the digital twin for finding the character, health, and usage monitoring systems for individual prescription with the energy-efficient IoT-related ROI per Optical character recognition, Sensitivity analysis, Accuracy, Sensitivity, and specificity.Interpretation The observational investigation predicts that this article discusses the proposed technique's design and architecture, which proves its methodology's effectiveness, architecture, and successful implementation of its technology.Keywords: Character recognitionhandwriting predictioninternet of thingsmedical word recognitionneural networktriboelectric smart recognition Authors' contributionsAll authors contributed to the design and methodology of this study, the assessment of the outcomes, and the writing of the manuscript.Additional informationNotes on contributorsP. ManivannanManivannan Parthasarathi received his Ph.D. from Anna University, Chennai, India. He is an Assistant Professor (Senior) at SASTRA University, working on Image Processing, Machine learning, and Data Mining.Nidhi AgarwalNidhi Agarwal received the BTech degree in Computer Science & Information Technology engineering in 2004 from U.P.T.U. and M. Tech degree in Computer engineering in 2011. Cleared NTA NET in Computer Applications & Engineering in June 2019. She has 18+ years of total teaching experience with B. Tech, M. Tech students and 2 years of research experience. She is pursuing PhD degree in the Department of Computer Engineering, IGDTUW, Delhi approved by Govt of N.C.T of Delhi since August 2019 and also serving as Assistant Professor in the Department of CSE at Galgotias University, Greater-Noida, India. She has around 10 research papers in SCI/E and Scopus indexed journals. She has around 15 papers in IEEE/Scopus indexed conferences. She has authored 1 book, 4 book chapters from the CSE domain and has 4 patents in her name. She has reviewed many research papers in international journals and conferences of repute. She has received many awards at national and institutional level based on her academics and research work. Her research interests include fuzzy logic, Soft Computing, Artificial Intelligence, Machine Learning, Deep Learning, Software Engineering, Agile Methodologies.Rahul PradhanRahul Pradhan is a researcher in the field of Statistics, language models, and various allied fields. He was a vast experience in teaching and research, he took courses such as databases, statistics, data analysis, and search engines. He had published papers in peer-reviewed journals, and conferences and had a patent to his accolades. He had also consultant to few companies in domain of data analysis, & blockchain.Bala Anand MuthuBala Anand Muthu received Ph. D from Anna University, India and working as an Associate Professor in the Department of Computer Science & Engineering at Tagore Institute of Engineering & Technology, India. His area of interest includes Big Data Analytics, Social Networks, Internet of Things, Cloud Computing in Healthcare and Environment applications.M. M. KamruzzamanM. M. Kamruzzaman received his B.E. and M.S degree in Computer Science and Engineering and PhD in Information and Communication Technology. At present he is working at Jouf university, KSA. He worked as a Post-Doctoral Research Fellow at Shenzhen University, China. He is a member of Editorial Board of several international journals. He is also serving as a TPC and reviewer of few international journal and conferences. His areas of interest include 5G, AI, Deep Learning, Image Processing, RS, GIS, Cloud Computing and Big Data.Akila VictorAkila Victor is currently working as an Associate Professor in School of Computer Science and Engineering in Vellore Institute of Technology, Vellore. She has completed Ph.D. at VIT University, Vellore, India in 2018. Her research interest includes Image Processing, computer vision, object detection, medical image processing, infrared imaging and machine learning. She has published more than 15 research papers in reputed international Journals and book chapters. She is a life member of CSI.R. MervinDr.Mervin Retnadhas Mary is an Assistant Professor at Saudi Electronic University, Saudi Arabia. She received her Ph.D. in Computer Science and Engineering in the research area of Question Answering System in the field of Natural Language Processing in 2019. She is having 22 years of teaching experience in various institutions in India and published 37 research articles in various National conferences, International Conferences, and International Journals also it includes 2 Patents and 2 Book chapters.