scholarly journals Real-Time Capable Sensor Data Analysis-Framework for Intelligent Assistance Systems

2021 ◽  
Author(s):  
Ulrich H.P. Fischer ◽  
Sabrina Hoppstock ◽  
Peter Kußmann ◽  
Isabell Steuding
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Sensor Data ◽  
Industrialized Countries ◽  
Cognitive Limitations ◽  
Age Cohort ◽  
Real Time Visualization ◽  
Frame Work

In the industrialized countries, the very old part of the population has been growing rapidly for many years. In the next few years in particular, the age cohort over 65 will increase significantly. This goes hand in hand with illnesses and other physical and cognitive limitations. In order to enable these people to remain in their own homes for as long as possible despite physical and cognitive restrictions, technologies are being used to create ambient assisted living applications. However, most of these systems are neither medically verified nor are latencies short enough, for example, to avoid falls. In order to overcome these problems, a promising approach is to use the new 5G network technology. Combined with a suitable sensor data analysis frame work, the fast care project showed that a real-time situation picture of the patient in the form of an Avatar could be generated. The sensor structure records the heart rate, the breathing rate, analyzes the gait and measures the temperature, the VOC content of the room air, and its humidity. An emergency button has also been integrated. In a laboratory demonstrator, it was shown that the infrastructure realizes a real-time visualization of the sensor data over a heterogeneous network.

scholarly journals Fast care – real-time sensor data analysis framework for intelligent assistance systems

2017 ◽  
Vol 3 (2) ◽  
pp. 743-747
Author(s):  
Albert Hein ◽  
Florian Grützmacher ◽  
Christian Haubelt ◽  
Thomas Kirste
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Assisted Living ◽  
Ad Hoc ◽  
Ambient Assisted Living ◽  
Situation Model ◽  
Sensor Data ◽  
Analysis Framework ◽  
Assistance Systems ◽  
Assistive Systems

AbstractMain target of fast care is the development of a real-time capable sensor data analysis framework for intelligent assistive systems in the field of Ambient Assisted Living, eHealth, Tele Rehabilitation, and Tele Care. The aim is to provide a medically valid integrated situation model based on a distributed, ad-hoc connected, energy-efficient sensor infrastructure suitable for daily use. The integrated situation model combining physiological, cognitive, and kinematic information about the patient is grounded on the intelligent fusion of heterogeneous sensor data on different levels. The model can serve as a tool for quickly identifying risk and hazards as well as enable medical assistance systems to autonomously intervene in real-time and actively give telemedical feedback.

scholarly journals Fast care

2017 ◽  
Vol 3 (2) ◽  
pp. 739-742
Author(s):  
Sabrina Hoppstock ◽  
Peter Kußmann ◽  
Ulrich H.P. Fischer-Hirchert
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Assisted Living ◽  
Ad Hoc ◽  
Ambient Assisted Living ◽  
Latency Period ◽  
Sensor Data ◽  
Analysis Framework ◽  
Project Fast

AbstractThe project fast care is working on a real-time capable sensor data analysis-framework in the fields of "Ambient Assisted Living" (AAL), "Human-Technology Interaction" (MTI) and "eHealth". The aim is to provide a medical valid - integrated real-time picture of the patient’s situation by using an ad hoc interconnected sensor – actor infrastructure with a latency period of less than 10 ms.

scholarly journals Environmentally-Powered WSN for Urban-Scale Mapping and Assessment of Air Quality in Qatar

2020 ◽  
Author(s):  
Hasan Tariq ◽  
Farid Touati
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Assisted Living ◽  
Quality Index ◽  
Electrochemical Sensors ◽  
Ambient Assisted Living ◽  
Quality Measurement ◽  
Air Quality Index ◽  
Cross Sensitivity ◽  
Index Mapping

Environmental monitoring has gained significant importance in outdoor air quality measurement and assessment for fundamental survival as well as ambient assisted living. In real-time outdoor urban scale, instantaneous air quality index estimation, the electrochemical sensors warm-up time, cross-sensitivity computation-error, geo-location typography, instantaneous capacity or back up time; and energy efficiency are the six major challenges. These challenges lead to real-time gradient anomalies that effect the accuracy and pro-longed lags in air quality index mapping campaigns for state and environmental/meteorological agencies. In this work, a gradient-aware, multi-variable air quality-sensing node is proposed with event-triggered sensing based on position, gas magnitudes, and cross-sensitivity interpolation. In this approach, temperature, humidity, pressure, geo-position, photovoltaic power, volatile organic compounds, particulate matter (2.5), ozone, Carbon mono-oxide, Nitrogen dioxide, and Sulphur dioxide are the principle variables. Results have shown that the proposed system optimized the real-time air quality monitoring for the chosen geo-spatial cluster (Qatar University).

scholarly journals A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Alexandros Andre Chaaraoui ◽  
Francisco Flórez-Revuelta
Keyword(s):  
Real Time ◽  
Action Recognition ◽  
Assisted Living ◽  
Learning Algorithm ◽  
Ambient Assisted Living ◽  
Human Action Recognition ◽  
Human Action ◽  
Sequence Matching ◽  
Low Dimensional ◽  
Video Frequency

This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled.

scholarly journals SMS: A Secure Healthcare Model for Smart Cities

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1135
Author(s):  
Gautami Tripathi ◽  
Mohd Abdul Ahad ◽  
Sara Paiva
Keyword(s):  
Real Time ◽  
Assisted Living ◽  
Smart City ◽  
Smart Cities ◽  
Ambient Assisted Living ◽  
Critical Time ◽  
Personal Data ◽  
Healthcare Management ◽  
Real Time Analysis ◽  
Healthcare Model

Technological innovations have enabled the realization of a utopian world where all objects of everyday life, as well as humans, are interconnected to form an “Internet of Things (IoT).” These connected technologies and IoT solutions have led to the emergence of smart cities where all components are converted into a connected smart ecosystem. IoT has envisioned several areas of smart cities including the modern healthcare environment like real-time monitoring, patient information management, ambient-assisted living, ambient-intelligence, anomaly detection, and accelerated sensing. IoT has also brought a breakthrough in the medical domain by integrating stake holders, medical components, and hospitals to bring about holistic healthcare management. The healthcare domain is already witnessing promising IoT-based solutions ranging from embedded mobile applications to wearable devices and implantable gadgets. However, with all these exemplary benefits, there is a need to ensure the safety and privacy of the patient’s personal and medical data communicated to and from the connected devices and systems. For a smart city, it is pertinent to have an accessible, effective, and secure healthcare system for its inhabitants. This paper discusses the various elements of technology-enabled healthcare and presents a privacy-preserved and secure “Smart Medical System (SMS)” framework for the smart city ecosystem. For providing real-time analysis and responses, this paper proposes to use the concept of secured Mobile Edge Computing (MEC) for performing critical time-bound computations on the edge itself. In order to protect the medical and personal data of the patients and to make the data tamper-proof, the concept of blockchain has been used. Finally, this paper highlights the ways to capture and store the medical big data generated from IoT devices and sensors.

scholarly journals Multivariate Sensor Data Analysis for Oil Refineries and Multi-mode Identification of System Behavior in Real-time

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 64389-64405 ◽  
Author(s):  
Athar Khodabakhsh ◽  
Ismail Ari ◽  
Mustafa Bakir ◽  
Ali Ozer Ercan
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Sensor Data ◽  
System Behavior ◽  
Mode Identification ◽  
Oil Refineries ◽  
Multi Mode
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