Personalized Automation of Electrical and Electronic Devices Using Sensors and Artificial Intelligence—“The Intelligizer System”

2018 ◽  
pp. 523-537
Author(s):  
Anish Batra ◽  
Guneet Singh Sethi ◽  
Suman Mann
Keyword(s):  
Artificial Intelligence ◽  
Electronic Devices

scholarly journals Heat Transfer and Its Innovative Applications

Inventions ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 4
Author(s):  
Ping-Hei Chen ◽  
Hyung Cho
Keyword(s):  
Heat Transfer ◽  
Artificial Intelligence ◽  
High Speed ◽  
Heat Dissipation ◽  
Outer Space ◽  
Electronic Devices ◽  
Daily Lives ◽  
Autonomous Cars

Innovative and high-end techniques have been recently developed in academic institutes and are gradually being employed in our daily lives for improving living quality, namely, artificial intelligence (AI) technology, autonomous cars, hyper-loop for high-speed transportation, miniaturization of electronic devices, heat dissipation from cooling films to outer space, and so on [...]

scholarly journals Relations between Electronics, Artificial Intelligence and Information Society through Information Society Rules

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 514
Author(s):  
Matjaž Gams ◽  
Tine Kolenik
Keyword(s):  
Artificial Intelligence ◽  
Information Society ◽  
Electronic Devices ◽  
Human Interaction ◽  
Human Capabilities ◽  
Human Skills ◽  
Programming Software ◽  
Production Prices ◽  
Modest Level ◽  
Do So

This paper presents relations between information society (IS), electronics and artificial intelligence (AI) mainly through twenty-four IS laws. The laws not only make up a novel collection, currently non-existing in the literature, but they also highlight the core boosting mechanism for the progress of what is called the information society and AI. The laws mainly describe the exponential growth in a particular field, be it the processing, storage or transmission capabilities of electronic devices. Other rules describe the relations to production prices and human interaction. Overall, the IS laws illustrate the most recent and most vibrant part of human history based on the unprecedented growth of device capabilities spurred by human innovation and ingenuity. Although there are signs of stalling, at the same time there are still many ways to prolong the fascinating progress of electronics that stimulates the field of artificial intelligence. There are constant leaps in new areas, such as the perception of real-world signals, where AI is already occasionally exceeding human capabilities and will do so even more in the future. In some areas where AI is presumed to be incapable of performing even at a modest level, such as the production of art or programming software, AI is making progress that can sometimes reflect true human skills. Maybe it is time for AI to boost the progress of electronics in return.

Artificial intelligence: an attempt to automate remote device follow-up

EP Europace ◽  
2021 ◽  
Vol 23 (Supplement_3) ◽  
Author(s):  
HDS Ferreira ◽  
F Ferrer ◽  
N Cabanelas ◽  
T Nelumba ◽  
AR Ferreira ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Language Processing ◽  
Remote Monitoring ◽  
Optical Character Recognition ◽  
Current System ◽  
Electronic Devices ◽  
Cardiac Resynchronization ◽  
Cardiac Implantable Electronic Devices

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Artificial intelligence (AI) through machine learning (ML) refers to the simulation of human intelligence with the capacity for achieving goals within computers. In electrophysiology, ML has many applications in electrocardiography, intracardiac mapping and cardiac implantable electronic devices (CIEDs). Remote monitoring (RM) of patients equipped with CIEDs associates the analysis of event reports and calendar-based remote follow-ups (FU). ML applications have allowed for risk stratification, improved arrhythmia localisation and streamlined remote monitoring which may significantly reduce the workload faced by electrophysiologists. Aim To develop a system that automates cardiac implantable electronic devices remote follow-up. Methods and Results We created a Java software application, that uses the latest optical character recognition techniques combined with artificial intelligence and natural language processing to extract information from PDF reports of RM of CIEDs from different manufacturers. The current version is HIPAA (Health Insurance Portability and Accountability Act) complaint and runs on local computers only. Using the current system, we were able to run and extract data from 30 remote follow-up PDF reports of Cardiac Implantable Defibrillators (ICDs) and Cardiac Resynchronization Therapy with Defibrillator (CRT-Ds). Time taken from data extraction to conversion of all 30 device PDFs was under 5 minutes. Process and data extracted are presented in the figure below. (Figure 1) Conclusion This machine learning algorithm proved that it is possible to facilitate and automate remote follow-up of cardiac implantable electronic devices. In a near future this will allow to us to efficiently increase productivity, by speeding and facilitating interpretation of remote device follow-ups, leading to improvements in patientcare and precision cardiovascular medicine. Furthermore, in the current and future pandemics it may help prevent unnecessary in-person medical visits, avoiding additional, unnecessary strain on an already overburdened and overwhelmed healthcare system, and saving costs. Abstract Figure 1

Advances of flexible pressure sensors toward artificial intelligence and health care applications

2015 ◽  
Vol 2 (2) ◽  
pp. 140-156 ◽  
Author(s):  
Yaping Zang ◽  
Fengjiao Zhang ◽  
Chong-an Di ◽  
Daoben Zhu
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Electronic Devices ◽  
Pressure Sensors ◽  
Health Care Industry ◽  
Organic Electronic Devices ◽  
Organic Electronic ◽  
Care Industry ◽  
Health Care Applications ◽  
Flexible Pressure Sensors

Incorporating flexible pressure sensors with organic electronic devices allows their promising applications in artificial intelligence and the health care industry.

scholarly journals Applications of Machine Learning in Cardiac Electrophysiology

2020 ◽  
Vol 9 (2) ◽  
pp. 71-77
Author(s):  
Rahul G Muthalaly ◽  
Robert M Evans ◽  
◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Diagnostic Accuracy ◽  
Cardiac Electrophysiology ◽  
Electronic Devices ◽  
Cardiac Implantable Electronic Devices ◽  
Supervised And Unsupervised Learning ◽  
The World ◽  
Applications Of Machine Learning

Artificial intelligence through machine learning (ML) methods is becoming prevalent throughout the world, with increasing adoption in healthcare. Improvements in technology have allowed early applications of machine learning to assist physician efficiency and diagnostic accuracy. In electrophysiology, ML has applications for use in every stage of patient care. However, its use is still in infancy. This article will introduce the potential of ML, before discussing the concept of big data and its pitfalls. The authors review some common ML methods including supervised and unsupervised learning, then examine applications in cardiac electrophysiology. This will focus on surface electrocardiography, intracardiac mapping and cardiac implantable electronic devices. Finally, the article concludes with an overview of how ML may impact on electrophysiology in the future.

scholarly journals Compositional Grounded Language for Agent Communication in Reinforcement Learning Environment

2019 ◽  
Vol 2 (3) ◽  
pp. 1
Author(s):  
K. Lannelongue ◽  
M. De Milly ◽  
R. Marcucci ◽  
S. Selevarangame ◽  
A. Supizet ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Electronic Devices ◽  
Common Language ◽  
Human Language ◽  
Significant Progress ◽  
The Past ◽  
Collective Goal ◽  
Exchange Channel ◽  
The Subject

In a context of constant evolution of technologies for scientific, economic and social purposes, Artificial Intelligence (AI) and Internet of Things (IoT) have seen significant progress over the past few years. As much as Human-Machine interactions are needed and tasks automation is undeniable, it is important that electronic devices (computers, cars, sensors…) could also communicate with humans just as well as they communicate together. The emergence of automated training and neural networks marked the beginning of a new conversational capability for the machines, illustrated with chat-bots. Nonetheless, using this technology is not sufficient, as they often give inappropriate or unrelated answers, usually when the subject changes. To improve this technology, the problem of defining a communication language constructed from scratch is addressed, in the intention to give machines the possibility to create a new and adapted exchange channel between them. Equipping each machine with a sound emitting system which accompany each individual or collective goal accomplishment, the convergence toward a common ‘’language’’ is analyzed, exactly as it is supposed to have happened for humans in the past. By constraining the language to satisfy the two main human language properties of being ground-based and of compositionality, rapidly converging evolution of syntactic communication is obtained, opening the way of a meaningful language between machines.

scholarly journals Portable and wearable self-powered systems based on emerging energy harvesting technology

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Chen Xu ◽  
Yu Song ◽  
Mengdi Han ◽  
Haixia Zhang
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Energy Harvesting ◽  
Electronic Devices ◽  
Potential Candidate ◽  
Self Powered

AbstractA self-powered system based on energy harvesting technology can be a potential candidate for solving the problem of supplying power to electronic devices. In this review, we focus on portable and wearable self-powered systems, starting with typical energy harvesting technology, and introduce portable and wearable self-powered systems with sensing functions. In addition, we demonstrate the potential of self-powered systems in actuation functions and the development of self-powered systems toward intelligent functions under the support of information processing and artificial intelligence technologies.

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