scholarly journals Design and Implementation of a Connection between Augmented Reality and Sensors

Robotics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 3
Author(s):  
Marlon Aguero ◽  
Dilendra Maharjan ◽  
Maria del Pilar Rodriguez ◽  
David Dennis Lee Mascarenas ◽  
Fernando Moreu
Keyword(s):  
Augmented Reality ◽  
Data Collection ◽  
Real Time ◽  
Strain Gauge ◽  
Low Cost ◽  
Contextual Information ◽  
Wireless Sensor ◽  
Infrastructure Management ◽  
Data Collection And Analysis ◽  
The Way

Wireless sensor networks (WSN) are used by engineers to record the behavior of structures. The sensors provide data to be used by engineers to make informed choices and prioritize decisions concerning maintenance procedures, required repairs, and potential infrastructure replacements. However, reliable data collection in the field remains a challenge. The information obtained by the sensors in the field frequently needs further processing, either at the decision-making headquarters or in the office. Although WSN allows data collection and analysis, there is often a gap between WSN data analysis results and the way decisions are made in industry. The industry depends on inspectors’ decisions, so it is of vital necessity to improve the inspectors’ access in the field to data collected from sensors. This paper presents the results of an experiment that shows the way Augmented Reality (AR) may improve the availability of WSN data to inspectors. AR is a tool which overlays the known attributes of an object with the corresponding position on the headset screen. In this way, it allows the integration of reality with a virtual representation provided by a computer in real time. These additional synthetic overlays supply data that may be unavailable otherwise, but it may also display additional contextual information. The experiment reported in this paper involves the application of a smart Strain Gauge Platform, which automatically measures strain for different applications, using a wireless sensor. In this experiment, an AR headset was used to improve actionable data visualization. The results of the reported experiment indicate that since the AR headset makes it possible to visualize information collected from the sensors in a graphic form in real time, it enables automatic, effective, reliable, and instant communication from a smart low-cost sensor strain gauge to a database. Moreover, it allows inspectors to observe augmented data and compare it across time and space, which then leads to appropriate prioritization of infrastructure management decisions based on accurate observations.

scholarly journals DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Suppawong Tuarob ◽  
Poom Wettayakorn ◽  
Ponpat Phetchai ◽  
Siripong Traivijitkhun ◽  
Sunghoon Lim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Data Collection ◽  
Stock Market ◽  
Real Time ◽  
Stock Prices ◽  
Contextual Information ◽  
Online News ◽  
Stock Prediction ◽  
Stock Market Prediction

AbstractThe explosion of online information with the recent advent of digital technology in information processing, information storing, information sharing, natural language processing, and text mining techniques has enabled stock investors to uncover market movement and volatility from heterogeneous content. For example, a typical stock market investor reads the news, explores market sentiment, and analyzes technical details in order to make a sound decision prior to purchasing or selling a particular company’s stock. However, capturing a dynamic stock market trend is challenging owing to high fluctuation and the non-stationary nature of the stock market. Although existing studies have attempted to enhance stock prediction, few have provided a complete decision-support system for investors to retrieve real-time data from multiple sources and extract insightful information for sound decision-making. To address the above challenge, we propose a unified solution for data collection, analysis, and visualization in real-time stock market prediction to retrieve and process relevant financial data from news articles, social media, and company technical information. We aim to provide not only useful information for stock investors but also meaningful visualization that enables investors to effectively interpret storyline events affecting stock prices. Specifically, we utilize an ensemble stacking of diversified machine-learning-based estimators and innovative contextual feature engineering to predict the next day’s stock prices. Experiment results show that our proposed stock forecasting method outperforms a traditional baseline with an average mean absolute percentage error of 0.93. Our findings confirm that leveraging an ensemble scheme of machine learning methods with contextual information improves stock prediction performance. Finally, our study could be further extended to a wide variety of innovative financial applications that seek to incorporate external insight from contextual information such as large-scale online news articles and social media data.

A LOW-COST MULTIHOP WIRELESS SENSOR NETWORK, ENABLING REAL-TIME MANAGEMENT OF ENVIRONMENTAL DATA FOR THE GREENHOUSE AND NURSERY INDUSTRY

2008 ◽  
pp. 523-530 ◽  
Author(s):  
J.D. Lea-Cox ◽  
A.G. Ristvey ◽  
F. Arguedas Rodriguez ◽  
D.S. Ross ◽  
J. Anhalt ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Time Management ◽  
Low Cost ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Multihop Wireless

Real-Time Physiological Data Collection and Analysis in Animal Inhalation Models: Predictive and Diagnostic Implications

2019 ◽  
pp. 791-802
Author(s):  
Benjamin Wong ◽  
Bryan. J. McCranor ◽  
Lewandowski Lewowski ◽  
Alfred. M. Sciuto
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Physiological Data ◽  
Data Collection And Analysis

scholarly journals SOLUÇÃO DE BAIXO CUSTO PARA O MONITORAMENTO DE SINAIS VITAIS, EM TEMPO REAL, FAZENDO USO DE SENSORES E ARDUINO

2020 ◽  
Vol 12 (2) ◽  
pp. 102-118
Author(s):  
Alexandre dos Santos Gonsalves ◽  
Robson Augusto Siscoutto
Keyword(s):  
Real Time ◽  
Health Monitoring ◽  
Low Cost ◽  
Vital Signs ◽  
Chronic Illnesses ◽  
Wireless Sensor ◽  
Health Monitoring System ◽  
Physical Exercises ◽  
Time Observation ◽  
Real Time Observation

The health monitoring system has become indispensable in the treatment of patients, especially for those who have chronic illnesses and need real-time observation from doctors and specialists. This article presents a low-cost wireless solution for monitoring, in real time, vital signs such as cardiac beats, breathing and blood pressure, collecting and sending data to a remote computer. During development, a wireless sensor box was created, using Arduino Nano and bluetooh sensors, where this box is attached to the patient's body, respecting the patient's flexibility and mobility during physical exercises. During the monitoring, the captured data is transmitted via the bluetooh network. The box uses a battery for its food. After the evaluation, the solution obtained a performance and correctness of the data close to 100%, being considered fit for use. Several experiments were carried out to analyze, quantify and qualify the solution, being discussed and presented in this paper.

scholarly journals Digital Vein Mapping Using Augmented Reality

2020 ◽  
Vol 13 (6) ◽  
pp. 512-521
Author(s):  
Mohamed Taha ◽  
◽  
Mohamed Ibrahim ◽  
Hala Zayed ◽  
◽  
...  
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Infrared Radiation ◽  
Low Cost ◽  
Economic Cost ◽  
Frame Rate ◽  
Infrared Light ◽  
Real Time Processing ◽  
And Gender ◽  
Time Systems

Vein detection is an important issue for the medical field. There are some commercial devices for detecting veins using infrared radiation. However, most of these commercial solutions are cost-prohibitive. Recently, veins detection has attracted much attention from research teams. The main focus is on developing real-time systems with low-cost hardware. Systems developed to reduce costs suffer from low frame rates. This, in turn, makes these systems not suitable for real-world applications. On the other hand, systems that use powerful processors to produce high frame rates suffer from high costs and a lack of mobility. In this paper, a real-time vein mapping prototype using augmented reality is proposed. The proposed prototype provides a compromised solution to produce high frame rates with a low-cost system. It consists of a USB camera attached to an Android smartphone used for real-time detection. Infrared radiation is employed to differentiate the veins using 20 Infrared Light Emitting Diodes (LEDs). The captured frames are processed to enhance vein detection using light computational algorithms to improve real-time processing and increase frame rate. Finally, the enhanced view of veins appears on the smartphone screen. Portability and economic cost are taken into consideration while developing the proposed prototype. The proposed prototype is tested with people of different ages and gender, as well as using mobile devices of different specifications. The results show a high vein detection rate and a high frame rate compared to other existing systems.

scholarly journals Differentiation of Patients with Balance Insufficiency (Vestibular Hypofunction) versus Normal Subjects Using a Low-Cost Small Wireless Wearable Gait Sensor

Biosensors ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 29 ◽  
Author(s):  
Tam Nguyen ◽  
Jonathan Young ◽  
Amanda Rodriguez ◽  
Steven Zupancic ◽  
Donald Lie
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Normal Subjects ◽  
The Elderly ◽  
Measurement Unit ◽  
Balance Disorders ◽  
Remote Sensor ◽  
Data Collection And Analysis ◽  
Dynamic Gait Index ◽  
Dynamic Gait

Balance disorders present a significant healthcare burden due to the potential for hospitalization or complications for the patient, especially among the elderly population when considering intangible losses such as quality of life, morbidities, and mortalities. This work is a continuation of our earlier works where we now examine feature extraction methodology on Dynamic Gait Index (DGI) tests and machine learning classifiers to differentiate patients with balance problems versus normal subjects on an expanded cohort of 60 patients. All data was obtained using our custom designed low-cost wireless gait analysis sensor (WGAS) containing a basic inertial measurement unit (IMU) worn by each subject during the DGI tests. The raw gait data is wirelessly transmitted from the WGAS for real-time gait data collection and analysis. Here we demonstrate predictive classifiers that achieve high accuracy, sensitivity, and specificity in distinguishing abnormal from normal gaits. These results show that gait data collected from our very low-cost wearable wireless gait sensor can effectively differentiate patients with balance disorders from normal subjects in real-time using various classifiers. Our ultimate goal is to be able to use a remote sensor such as the WGAS to accurately stratify an individual’s risk for falls.

Visual Ethnography as a Research Methodology

2022 ◽  
pp. 18-40
Author(s):  
Candace Kaye
Keyword(s):  
Qualitative Research ◽  
Data Collection ◽  
Research Methodology ◽  
Visual Ethnography ◽  
Research Topics ◽  
Data Collection And Analysis ◽  
The Future ◽  
Investigative Process ◽  
The Way

The chapter presents a rationale for using visual ethnography as part of the methodology in qualitative research and illustrates what visual ethnography methodology is capable of accomplishing when imagery is included in the investigative process. Visual ethnography offers a venue for collecting and analyzing data that would otherwise be inaccessible and positions imagery as an important, rather than a minimal or occasional, choice for use in qualitative research. Topics include contemporary definitions of visual ethnography and its value in qualitative research, historical applications of visual ethnographic theory that influence the way researchers view visual ethnography today, and contemporary uses of visual ethnography in data collection and analysis. Finally, the conclusion explores the future of visual ethnography.

scholarly journals Design and implementation of data collection module for WSN application

2015 ◽  
Vol 4 (1) ◽  
pp. 104
Author(s):  
Valentina Markova ◽  
Teodora Trifonova ◽  
Venceslav Draganov
Keyword(s):  
Data Collection ◽  
Power Management ◽  
Low Cost ◽  
Wireless Sensor ◽  
Remote Monitoring System ◽  
Design And Implementation ◽  
System A ◽  
Monitoring Applications ◽  
Reliable Performance ◽  
Proper Operation

This paper presents the design and implementation of universal low cost data collection module (DCM), which is an essential part of remote monitoring system based on wireless sensor network. The proposed module expands the capabilities of a measuring node for collecting data from greater number of sensors. The DCM includes four parts: one group multiplexers for data acquisition, second group multiplexers for power management, voltage to current converters and DC/DC converters. The universal DC/DC converters provide autonomous power supply for the sensors and the multiplexers, which can be turned on or off for a certain period of time. The data collecting, monitoring and logging functions are realized through a LabVIEW project.The proper operation and the reliable performance of the system were proved by practical experiment. The proposed module makes the WSN-based system a versatile solution for a variety of monitoring applications.

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