scholarly journals Development of Arduino-based Data Acquisition System for Environmental Monitoring using Zigbee Communication Protocol

2020 ◽  
Vol 1 (3) ◽  
pp. 109-119
Author(s):  
Busari Sherif A ◽  
Dunmoye Abibat F ◽  
Akingbade Kayode F.
Keyword(s):  
Environmental Monitoring ◽  
Data Acquisition ◽  
Data Storage ◽  
Health Management ◽  
Medical Diagnostics ◽  
Indoor Climate ◽  
Data Logging ◽  
Climate Control ◽  
Time Data ◽  
Receiver System

Data Acquisition Systems (DAS) are used for a variety of applications such as environmental monitoring,indoor climate control, health management and medical diagnostics, traffic surveillance and emergency response,disaster management among others. This paper presents the design of a DAS for monitoring environmentaltemperature, pressure and relative humidity. The system employs Arduino Uno microcontroller for signal processingand Zigbee transceivers operating on the 2.4 GHz license-free Industrial, Scientific and Medical (ISM) band ascommunication modules at both the transmitter and receiver ends. While the transmitter board houses the sensors, aGPS module and an LCD, the receiver system is interfaced with a PC which runs a developed MATLAB GUI for datadisplay and analysis and it incorporates an SD card for data storage. The battery-powered system is a low cost, lowpower consumption system which serves as a mini-weather station with real-time data logging, wirelesscommunication and tracking capabilities.

scholarly journals Development of Arduino-based Data Acquisition System for Environmental Monitoring using Zigbee Communication Protocol

2016 ◽  
Vol 1 (3) ◽  
pp. 109-118
Author(s):  
Busari Sherif A. ◽  
Dunmoye Abibat F. ◽  
Akingbade Kayode F.
Keyword(s):  
Environmental Monitoring ◽  
Data Acquisition ◽  
Data Storage ◽  
Health Management ◽  
Medical Diagnostics ◽  
Indoor Climate ◽  
Data Logging ◽  
Climate Control ◽  
Time Data ◽  
Receiver System

Data Acquisition Systems (DAS) are used for a variety of applications such as environmental monitoring, indoor climate control, health management and medical diagnostics, traffic surveillance and emergency response, disaster management among others. This paper presents the design of a DAS for monitoring environmental temperature, pressure and relative humidity. The system employs Arduino Uno microcontroller for signal processing and Zigbee transceivers operating on the 2.4 GHz license-free Industrial, Scientific and Medical (ISM) band as communication modules at both the transmitter and receiver ends. While the transmitter board houses the sensors, a GPS module and an LCD, the receiver system is interfaced with a PC which runs a developed MATLAB GUI for data display and analysis and it incorporates an SD card for data storage. The battery-powered system is a low cost, low-power consumption system which serves as a mini-weather station with real-time data logging, wireless communication and tracking capabilities.

A High Speed and Compact Data Acquisition and Storage System

2013 ◽  
Vol 753-755 ◽  
pp. 3125-3128
Author(s):  
Kai Bu ◽  
Hui Xu ◽  
Zhao Lin Sun ◽  
Jian Bin Liu
Keyword(s):  
Data Acquisition ◽  
Data Storage ◽  
Software Defined Radio ◽  
High Speed ◽  
Storage System ◽  
Base Stations ◽  
Time Data ◽  
Processing Application ◽  
Wideband Signal ◽  
And Storage

Data acquisition and record system plays an important role in signal processing. For the wideband signal acquisition and processing application, such as 3G/4G Base Stations, Wideband Microwave Backhaul, Military Communications, and RADAR, the need for high speed and smart software-defined radio (SDR) test platform is growing. In this paper, we implement a high compact form factor data acquisition and storage system used for the wideband signal application development. In order to implement high compact, low power and high speed real-time data storage, we use a PCIe-based switch architecture and leverage the Flash array as the storage part. The system supports RF sampling directly and offers a 16TB solid state storage module which could be read and write at the sustained speed of 12.8GB/s.

The Implement of B-Ultrasonic Image Acquisition Based on Camera Interface

2014 ◽  
Vol 513-517 ◽  
pp. 3801-3804
Author(s):  
Xiao Ming Gao
Keyword(s):  
Data Acquisition ◽  
Data Storage ◽  
Imaging System ◽  
Image Data ◽  
Medical Diagnostics ◽  
Ultrasonic Image ◽  
Ultrasonic Fields ◽  
Non Invasive ◽  
Software Development System ◽  
System Data

B-ultrasonic is widely used in medical diagnostics and other fields, because of its non-invasive, no radiation, etc. Early B-ultrasonic with analog imaging system cant achieve B-ultrasonic image processing, data storage and other operations. With the development of computer technology and electronic technology, Digital B-ultrasonic systems are increasingly used in actual diagnosis, the paper through the use of digital imaging system to achieve B-ultrasonic front ultrasound imaging, reuse embedded microcontrollers Camera interface for B-ultrasonic acquisition of image data, and on this platform to achieve a B-ultrasonic application software development. System testing show that the system data acquisition is stability, and easy to operate, reliable, also can be widely used in medical and industrial ultrasonic fields. Key words: B-ultrasonic; Data Acquisition; Camera; Digitizing

Wireless Sensors with Advanced Detection and Prognostic Capabilities for Corrosion Health Management

2008 ◽  
Vol 38 ◽  
pp. 123-131
Author(s):  
Kevin Kwan ◽  
Benjamin Caldwell ◽  
Jeffrey Morse ◽  
John O'Day ◽  
Bernard C. Laskowski ◽  
...  
Keyword(s):  
Data Analysis ◽  
Data Acquisition ◽  
Sensor Network ◽  
Data Storage ◽  
Ieee 802.15.4 ◽  
Health Management ◽  
Liquid Crystal Display ◽  
Support Tool ◽  
Handheld Device ◽  
Structural Health

Analatom, Inc. is developing the Structural Health Monitoring (SHM) system using its Linear Polarization Resistance (LPR) corrosion sensors combined with a Texas Instruments MSP430 microprocessor for lower weight, lower power, higher sensitivity, and lower cost than conventional sensor systems. The system provides both strain and corrosion measurements in a package a few mils thick. This combination of data provides critical assessment of structural health, leading to prediction of failure. The MEMS sensors are permanently installed in a highvalued structure, such as a building, bridge or aircraft, and are connected to a data acquisition node. Data transmission and downloading uses a MaxStream ZigBee/IEEE 802.15.4 compliant chip for a wireless, self-organizing network that has low power requirements. The sensor network provides a low-cost, non-intrusive way to detect failures, or to signal ahead of time that preventative maintenance needs to be undertaken to prevent future more expensive replacement. Analatom, Inc. has developed the basic technology for a Portable Maintenance Support Tool (PMST). The device is unique and novel in that it uses a Micro Controller Unit in a handheld device to perform data analysis whilst maintaining a link with a Personal Computer based database for further support. The handheld prototype with a Liquid Crystal Display (LED) touch screen GUI takes readings from a variety of sensors and transfers the data wirelessly to a central PC hub. The handheld unit using the downloaded data from the sensor network can then provide a graphic display and additionally transfer those data to a workstation for further data analysis. Analatom, Inc. builds on its corrosion system platform (sensors, data acquisition unit, data storage) to develop a multiplexed system to obtain data from a variety of sensors, while further developing real time intelligent algorithms to monitor corrosion rates.

The Building of Data Acquisition System Based on Embedded Technology

2012 ◽  
Vol 546-547 ◽  
pp. 481-485
Author(s):  
Ye Hui Liu
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Data Storage ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Time Data ◽  
Local Data ◽  
Software Environment ◽  
Data Acquisition Board ◽  
The Common

The common data acquisition system which is proposed in this paper has achieved features of monitoring layer and data collection layer (Complete the construction of ARM9 system board hardware and software environment; implement the design of STM8L acquisition board; design such application modules as host MODBUS, slave MODBUS, parameter setting, real-time data communications, real-time graphical display, local data storage, ADC, digital filtering and so on). Judging from the system test, it can achieve the desired effect, and especially, STM8L ADC data acquisition board has highly precise and consumes low power.

Design and Implementation of a Data Acquisition Platform for Automated Mechanical Transmission (AMT)

2013 ◽  
Author(s):  
Lirong Wang ◽  
Kai Liu
Keyword(s):  
Data Acquisition ◽  
Data Storage ◽  
Engine Speed ◽  
Mechanical Transmission ◽  
Virtual Instrumentation ◽  
Time Data ◽  
Test Vehicle ◽  
Function Block ◽  
Vehicle Velocity ◽  
Test Platform

A kind of data acquisition platform to test vehicle shifting performance is presented based on virtual instrumentation technology. The platform helps to perform test efficiently by synchronously accessing various kinds of data transferred by electronic transducers and CAN bus, for example the signals of clutch travel, throttle angular, engine speed, gearbox input speed, vehicle velocity and acceleration and so on. A friendly GUI (Graphical user interface) is developed to manage experimental layout based on graphical function block in software of LabVIEW. QSM (Queued Stated Machine) to construct producer consumer architecture with functions of multi-channel and real-time data acquisition, data analysis and data storage is adopted. Vehicle experiment to acquisit data during shifting process of AMT (Automated Mechanical Transmission) are carried out, which takes advantages of high integration, great scalability and excellent reliability. The presented test platform is valuable to design and evaluation of electrical control system in vehicle.

scholarly journals Optimized cryo-EM data-acquisition workflow by sample-thickness determination

2021 ◽  
Vol 77 (5) ◽  
pp. 565-571
Author(s):  
Jan Rheinberger ◽  
Gert Oostergetel ◽  
Guenter P. Resch ◽  
Cristina Paulino
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Data Collection ◽  
Data Acquisition ◽  
Data Storage ◽  
Collection Efficiency ◽  
Sample Thickness ◽  
Access Time ◽  
Time Data ◽  
Data Set

Sample thickness is a known key parameter in cryo-electron microscopy (cryo-EM) and can affect the amount of high-resolution information retained in the image. Yet, common data-acquisition approaches in single-particle cryo-EM do not take it into account. Here, it is demonstrated how the sample thickness can be determined before data acquisition, allowing the identification of optimal regions and the restriction of automated data collection to images with preserved high-resolution details. This quality-over-quantity approach almost entirely eliminates the time- and storage-consuming collection of suboptimal images, which are discarded after a recorded session or during early image processing due to a lack of high-resolution information. It maximizes the data-collection efficiency and lowers the electron-microscopy time required per data set. This strategy is especially useful if the speed of data collection is restricted by the microscope hardware and software, or if microscope access time, data transfer, data storage and computational power are a bottleneck.

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

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