Cyber-Physical Platform Development for Multivariable Artificial Pancreas Systems

2015 ◽  
Vol 6 (3) ◽  
pp. 1-16 ◽  
Author(s):  
Caterina Lazaro ◽  
Erdal Oruklu ◽  
Ali Cinar
Keyword(s):  
Artificial Pancreas ◽  
Data Access ◽  
Time Data ◽  
Distributed Sensor ◽  
Multiple Sensors ◽  
Glucose Levels ◽  
Sensor Platform ◽  
Prediction And Control ◽  
Platform Development ◽  
And Control

This paper describes a distributed sensor platform for a new breed of artificial pancreas devices. In recent work, a multi-variable adaptive algorithm has been proposed which incorporates physical activity of the patients for accurate prediction and control of glucose levels. In order to facilitate this algorithm, the authors integrate a smartphone and multiple sensors including activity trackers and a glucose monitor into a distributed system. The proposed sensor platform provides real-time data access for the artificial pancreas control algorithm hosted on a remote device.

The Artificial Pancreas in Cyborg Bodies

2020 ◽  
pp. 412-430
Author(s):  
Anthony Ryan Hatch ◽  
Julia T. Gordon ◽  
Sonya R. Sternlieb
Keyword(s):  
Glucose Sensor ◽  
Social Inequalities ◽  
Infusion Pump ◽  
Artificial Pancreas ◽  
Small Scale ◽  
Glucose Levels ◽  
Loop Design ◽  
Access To Health ◽  
Do It Yourself ◽  
And Control

The new artificial pancreas system includes a body-attached blood glucose sensor that tracks glucose levels, a worn insulin infusion pump that communicates with the sensor, and features new software that integrates the two systems. The artificial pancreas is purportedly revolutionary because of its closed-loop design, which means that the machine can give insulin without direct patient intervention. It can read a blood sugar and administer insulin based on an algorithm. But, the hardware for the corporate artificial pancreas is expensive and its software code is closed-access. Yet, well-educated, tech-savvy diabetics have been fashioning their own fully automated do-it-yourself (DIY) artificial pancreases for years, relying on small-scale manufacturing, open-source software, and inventive repurposing of corporate hardware. In this chapter, we trace the corporate and DIY artificial pancreases as they grapple with issues of design and accessibility in a content where not everyone can become a diabetic cyborg. The corporate artificial pancreas offers the cyborg low levels of agency and no ownership and control over his or her own data; it also requires access to health insurance in order to procure and use the technology. The DIY artificial pancreas offers patients a more robust of agency but also requires high levels of intellectual capital to hack the devices and make the system work safely. We argue that efforts to increase agency, radically democratize biotechnology, and expand information ownership in the DIY movement are characterized by ideologies and social inequalities that also define corporate pathways.

Industry 4.0 Digital Technologies for data collection and control

2021 ◽  
pp. 43-58
Author(s):  
S. S. Yudachev ◽  
P. A. Monakhov ◽  
N. A. Gordienko
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Software Defined Radio ◽  
Block Diagram ◽  
Data Access ◽  
Gnu Radio ◽  
Time Data ◽  
Object A ◽  
Data Propagation ◽  
And Control

This article describes an attempt to create open source LabVIEW software, equivalent to data collection and control software. The proposed solution uses GNU Radio, OpenCV, Scilab, Xcos, and Comedi in Linux. GNU Radio provides a user-friendly graphical interface. Also, GNU Radio is a software-defined radio that conducts experiments in practice using software rather than the usual hardware implementation. Blocks for data propagation, code deletion with and without code tracking are created using the zero correlation zone code (ZCZ, a combination of ternary codes equal to 1, 0, and –1, which is specified in the program). Unlike MATLAB Simulink, GNU Radio is open source, i. e. free, and the concepts can be easily accessed by ordinary people without much programming experience using pre-written blocks. Calculations can be performed using OpenCV or Scilab and Xcos. Xcos is an application that is part of the Scilab mathematical modeling system, and it provides developers with the ability to design systems in the field of mechanics, hydraulics and electronics, as well as queuing systems. Xcos is a graphical interactive environment based on block modeling. The application is designed to solve problems of dynamic and situational modeling of systems, processes, devices, as well as testing and analyzing these systems. In this case, the modeled object (a system, device or process) is represented graphically by its functional parametric block diagram, which includes blocks of system elements and connections between them. The device drivers listed in Comedi are used for real-time data access. We also present an improved PyGTK-based graphical user interface for GNU Radio. English version of the article is available at URL: https://panor.ru/articles/industry-40-digital-technology-for-data-collection-and-management/65216.html

scholarly journals Quality Prediction and Control of Assembly and Welding Process for Ship Group Product Based on Digital Twin

Scanning ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Lei Li ◽  
Di Liu ◽  
Jinfeng Liu ◽  
Hong-gen Zhou ◽  
Jiasheng Zhou
Keyword(s):  
Quality Control ◽  
Welding Process ◽  
Quality Prediction ◽  
Twin Data ◽  
Time Data ◽  
Digital Twin ◽  
Twin Model ◽  
Prediction And Control ◽  
And Control ◽  
Group Product

In view of the problems of lagging and poor predictability for ship assembly and welding quality control, the digital twin technology is applied to realize the quality prediction and control of ship group product. Based on the analysis of internal and external quality factors, a digital twin-based quality prediction and control process was proposed. Furthermore, the digital twin model of quality prediction and control was established, including physical assembly and welding entity, virtual assembly and welding model, the quality prediction and control system, and twin data. Next, the real-time data collection based on the Internet of Things and the twin data organization based on XML were used to create a virtual-real mapping mechanism. Then, the machine learning technology is applied to predict the process quality of ship group products. Finally, a small group is taken as an example to verify the proposed method. The results show that the established prediction model can accurately evaluate the welding angular deformation of group products and also provide a new idea for the quality control of shipbuilding.

scholarly journals A New Sensor Platform for Investigating Turbulence in Stratified Coastal Environments

2013 ◽  
Vol 30 (8) ◽  
pp. 1789-1802 ◽  
Author(s):  
Damien Bouffard ◽  
Ulrich Lemmin
Keyword(s):  
Richardson Number ◽  
Field Research ◽  
Data Access ◽  
Turbulent Energy ◽  
Small Scale ◽  
Time Data ◽  
Stratified Lakes ◽  
Turbulence Structures ◽  
Sensor Platform ◽  
Scale Turbulence

Abstract Characterizing and quantifying vertical exchange processes is essential for understanding physical and biological dynamics in stratified lakes and oceans. Unfortunately, the role of mixing is still poorly understood because of the challenges of conducting field research on small-scale turbulence, especially in the vicinity of a thermocline. This study presents a new moored sensor platform that was designed to investigate small-scale turbulence structures in time and space. The objective is to determine all terms of the turbulent energy equation separately and simultaneously. The platform is equipped with a microstructure package for measuring shear, temperature, and temperature gradients, as well as with a vertical array of high-precision thermistor probes and acoustic Doppler velocimeters. The platform can be moved vertically in the water column using a bottom-resting winch that is connected to a shore station by a 1800-m-long communication cable. This cable allows real-time data access and control of the winch, and thus optimization of the measurement strategy. A field study in Lake Geneva, located between Switzerland and France, shows that this system is ideally suited for the analysis of the dynamics of baroclinic motions, such as internal Kelvin waves. First results indicate a clear relationship between low Richardson number and elevated dissipation, and suggest a mean flux Richardson number Rf = 0.14 ± 0.4. However, this measurement campaign was not as conclusive for the reason of the variability of Rf.

An insight into Case Management and Challenges in Veteran Suicide Prevention

2020 ◽  
pp. 14-25
Author(s):  
Tamara Green
Keyword(s):  
Case Management ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Digital Transformation ◽  
Prevention Science ◽  
Historical Records ◽  
Military Members ◽  
Prediction And Control ◽  
And Control ◽  
Insight Into

Much of the literature, policies, programs, and investment has been made on mental health, case management, and suicide prevention of veterans. The Australian “veteran community is facing a suicide epidemic for the reasons that are extremely complex and beyond the scope of those currently dealing with them.” (Menz, D: 2019). Only limited work has considered the digital transformation of loosely and manual-based historical records and no enablement of Artificial Intelligence (A.I) and machine learning to suicide risk prediction and control for serving military members and veterans to date. This paper presents issues and challenges in suicide prevention and management of veterans, from the standing of policymakers to stakeholders, campaigners of veteran suicide prevention, science and big data, and an opportunity for the digital transformation of case management.

Situational Strategic Awareness Monitoring Surveillance System–Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials

2020 ◽  
Vol 2020 (3) ◽  
pp. 60408-1-60408-10
Author(s):  
Kenly Maldonado ◽  
Steve Simske
Keyword(s):  
Surveillance System ◽  
Cost Effective ◽  
Government Agencies ◽  
Electronic Systems ◽  
Time Data ◽  
Potential Threat ◽  
Intelligent Surveillance ◽  
World Markets ◽  
Programming Software ◽  
And Control

The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.

A case study of wear-type rail corrugation prediction and control using speed variation

2009 ◽  
Vol 325 (1-2) ◽  
pp. 85-105 ◽  
Author(s):  
P.A. Meehan ◽  
P.A. Bellette ◽  
R.D. Batten ◽  
W.J.T. Daniel ◽  
R.J. Horwood
Keyword(s):  
Rail Corrugation ◽  
Speed Variation ◽  
Prediction And Control ◽  
And Control

scholarly journals Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2146
Author(s):  
Manuel Andrés Vélez-Guerrero ◽  
Mauro Callejas-Cuervo ◽  
Stefano Mazzoleni
Keyword(s):  
Artificial Intelligence ◽  
Upper Limb ◽  
Main Trend ◽  
Motor Rehabilitation ◽  
Rehabilitation Process ◽  
Upper Limb Rehabilitation ◽  
Multiple Sensors ◽  
Meta Analyses ◽  
Limb Rehabilitation ◽  
And Control

Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.

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