Overcoming Obstacles in the Advancement of Industry 5.0 With the Digital Innovation

Author:

Kumari Y. Saritha1,Sheoliha Neelam2,Rajitha Akula3,Reddy Uma4,Singla Atul5,Tomar Yesha6

Affiliation:

1. JNTUA College of Engineering, India

2. Delhi Institute of Higher Education, India

3. Institute of Aeronautical Engineering, Dundigal, India

4. New Horizon College of Engineering, India

5. Lovely Professional University, India

6. Doon University, India

Abstract

Various industrial eras have seen a transformation due to emerging technologies. Numerous innovative technologies, such as cobots, cloud computing, virtual reality, big data, and artificial intelligence (AI) have emerged as a result of Industry 5.0. Three guiding principles—human centricity, flexibility, and sustainability—direct Industry 5.0. The process of identifying human diseases remains difficult despite the “smart healthcare industry 5.0” and information technology improvements. Precise forecasting of human ailments, particularly fatal cancers, is essential for individuals' well-being in the intelligent healthcare sector 5.0. The proposed model is further supported by a fused weighted deep extreme machine learning (FDEML) strategy for enhanced lung disease prediction. The suggested FDEML system has confirmed to be the most reliable diagnosis of cancer sickness in the smart healthcare sector 5.0. The proposed FDEML approach surpassed the most sophisticated published techniques, receiving a score of 97.1%.

Publisher

IGI Global

Reference36 articles.

1. Prediction of Diabetes Empowered With Fused Machine Learning

2. Peer-to-peer energy trading among smart homes

3. Alzaabi, H. O. (2021). Intelligent Energy Consumption for Smart Homes using Fused Machine Learning Technique [Doctoral dissertation, The British University in Dubai].

4. Innovation in the Era of IoT and Industry 5.0: Absolute Innovation Management (AIM) Framework

5. Clustering and Bayesian Networks

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3