scholarly journals Patient Healthcare Monitoring system for Emergency Situations

2019 ◽  
Vol 8 (12S) ◽  
pp. 287-290
Keyword(s):  
Real Time ◽  
Sensor Node ◽  
Threshold Value ◽  
Raspberry Pi ◽  
Physical Parameters ◽  
Remote Communication ◽  
Emergency Situations ◽  
Remote Transmission ◽  
The Individual ◽  
System Access

System for real time patient monitoring, have attracted noteworthy consideration in the most recent two decades. An enormous number of economical forms of patient checking systems are accessible, which were being used by approved health care experts. Notwithstanding this there is a solid requirement for online patient observing system, when the patient isn't in the emergency clinic. The principle target of this paper is to structure and execute an economical, convenient powerful patient checking observing system that can transmit the essential indications of a patient in crisis /crucial circumstances constantly through a remote communication network. Different sensors, for example, pulse, temperature, blood pressure and fingerprint are inter-faced through the microcontroller for estimating the significant physical parameters of the patient. For remote transmission, these sensors are associated with a sensor node through GSM module. Raspberry-Pi is utilized as a sensor node as it has better highlights contrasted with different controllers. Subsequent to giving system access to the Raspberry Pix board, it goes about as a server. At that point the server routinely sends estimated information to the web-server, which are additionally checked by employing web page which can be recovered from anyplace on the planet using workstations, laptops, android advanced cell and so on. The deliberate constant parameters are refreshed at regular intervals. The information procured is first stored, analyzed and projected on a webserver. The framework is executed so that, when the deliberate physiological information surpasses the threshold value, the overseer is alarmed through SMS and a voice call. Also using the proposed system, real-time remote monitoring is also carried out on the patient. Additionally, positional data of the individual can be obtained from GPS receiver as shown on the digital map and sent to the related units. Thus, the system proposed in this paper makes the individual’s day-to-day life relaxed and more comfortable.

scholarly journals Assessing the Best Gap-Filling Technique for River Stage Data Suitable for Low Capacity Processors and Real-Time Application Using IoT

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6354
Author(s):  
Antonio Madueño Luna ◽  
Miriam López Lineros ◽  
Javier Estévez Gualda ◽  
Juan Vicente Giráldez Cervera ◽  
José Miguel Madueño Luna
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Raspberry Pi ◽  
Data Sets ◽  
Analysis Method ◽  
Gap Filling ◽  
Remote Communication ◽  
Catchment Basin ◽  
River Stage ◽  
Real Time Application

Hydrometeorological data sets are usually incomplete due to different reasons (malfunctioning sensors, collected data storage problems, etc.). Missing data do not only affect the resulting decision-making process, but also the choice of a particular analysis method. Given the increase of extreme events due to climate change, it is necessary to improve the management of water resources. Due to the solution of this problem requires the development of accurate estimations and its application in real time, this work present two contributions. Firstly, different gap-filling techniques have been evaluated in order to select the most adequate one for river stage series: (i) cubic splines (CS), (ii) radial basis function (RBF) and (iii) multilayer perceptron (MLP) suitable for small processors like Arduino or Raspberry Pi. The results obtained confirmed that splines and monolayer perceptrons had the best performances. Secondly, a pre-validating Internet of Things (IoT) device was developed using a dynamic seed non-linear autoregressive neural network (NARNN). This automatic pre-validation in real time was tested satisfactorily, sending the data to the catchment basin process center (CPC) by using remote communication based on 4G technology.

scholarly journals The Routing Algorithm Based on Fuzzy Logic Applied to the Individual Physiological Monitoring Wearable Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Jie Jiang ◽  
Yun Liu ◽  
Fuxing Song ◽  
Ronghao Du ◽  
Mengsen Huang
Keyword(s):  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Sensor Node ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Physiological Monitoring ◽  
Network Resources ◽  
The Individual

In recent years, the research of individual wearable physiological monitoring wireless sensor network is in the primary stage. The monitor of physiology and geographical position used in wearable wireless sensor network requires performances such as real time, reliability, and energy balance. According to these requirements, this paper introduces a design of individual wearable wireless sensor network monitoring system; what is more important, based on this background, this paper improves the classical Collection Tree Protocol and puts forward the improved routing protocol F-CTP based on the fuzzy logic routing algorithm. Simulation results illustrate that, with the F-CTP protocol, the sensor node can transmit data to the sink node in real time with higher reliability and the energy of the nodes consumes balance. The sensor node can make full use of network resources reasonably and prolong the network life.

scholarly journals Internet of Things based Real Time Water Monitoring System

2019 ◽  
Vol 8 (2) ◽  
pp. 1368-1372
Keyword(s):  
Water Pollution ◽  
Real Time ◽  
Monitoring System ◽  
Intelligent Systems ◽  
Ph Value ◽  
Low Cost ◽  
Mechanical Systems ◽  
Raspberry Pi ◽  
Individual Species ◽  
The Individual

In real time computing, the embedded systems are a collection of electrical and mechanical systems with a association of small computers. The advancement of such electro mechanical systems with the environment is crucial in today’s scenario. Nowadays, the environmental pollution creates hazardous effect on the living creatures. The harmful pollutants should be identified and should be evacuated for the survival of mankind and other living organisms. Among the environmental pollutions, water pollution is more contaminated than air and soil. The water pollution damages the individual species and all biological creatures. The qualitative analysis of water is a thrust area of research with intelligent systems. At present, testing equipment are used in the laboratories to perform investigations with various water samples. These laboratory analysis make use of chemicals, reagents and sensors for determining the suitability of water for drinking purposes. Such laboratory methods are time consuming and are relatively expensive. To address this issue, quality of drinking water needs to be measured and monitored in real time for the safety of the people. This paper attempts to develop a low cost real time monitoring system to measure various parameters such as PH value, turbidity level and temperature. The measured values are processed through Raspberry Pi 3 module. The results are validated with real-time samples collected from various places and conveyed to the remote user through cloud server

PROTOTYPE ALAT PEMANTAU SALURAN AIR BAWAH TANAH DENGAN MENGGUNAKAN WEBCAM C170 BERBASIS RASPBERRY PI

2015 ◽  
Vol 1 (1) ◽  
pp. 37-45
Author(s):  
Irwansyah Irwansyah ◽  
Hendra Kusumah ◽  
Muhammad Syarif
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Public Awareness ◽  
Underground Water ◽  
Raspberry Pi ◽  
Laptop Computer ◽  
Web Browser ◽  
Disaster Monitoring ◽  
The Times ◽  
Human Desire

Along with the times, recently there have been found tool to facilitate human’s work. Electronics is one of technology to facilitate human’s work. One of human desire is being safe, so that people think to make a tool which can monitor the surrounding condition without being monitored with people’s own eyes. Public awareness of the underground water channels currently felt still very little so frequent floods. To avoid the flood disaster monitoring needs to be done to underground water channels.This tool is controlled via a web browser. for the components used in this monitoring system is the Raspberry Pi technology where the system can take pictures in real time with the help of Logitech C170 webcam camera. web browser and Raspberry Pi make everyone can control the devices around with using smartphone, laptop, computer and ipad. This research is expected to be able to help the users in knowing the blockage on water flow and monitored around in realtime.

scholarly journals An Improved Multipath Mitigation Method and Its Application in Real-Time Bridge Deformation Monitoring

2021 ◽  
Vol 13 (12) ◽  
pp. 2259
Author(s):  
Ruicheng Zhang ◽  
Chengfa Gao ◽  
Qing Zhao ◽  
Zihan Peng ◽  
Rui Shang
Keyword(s):  
Real Time ◽  
Sampling Rate ◽  
Threshold Value ◽  
Deformation Monitoring ◽  
Success Rates ◽  
Multipath Mitigation ◽  
Mode Decomposition ◽  
Observation Noise ◽  
Original Observation ◽  
Better Than

A multipath is a major error source in bridge deformation monitoring and the key to achieving millimeter-level monitoring. Although the traditional MHM (multipath hemispherical map) algorithm can be applied to multipath mitigation in real-time scenarios, accuracy needs to be further improved due to the influence of observation noise and the multipath differences between different satellites. Aiming at the insufficiency of MHM in dealing with the adverse impact of observation noise, we proposed the MHM_V model, based on Variational Mode Decomposition (VMD) and the MHM algorithm. Utilizing the VMD algorithm to extract the multipath from single-difference (SD) residuals, and according to the principle of the closest elevation and azimuth, the original observation of carrier phase in the few days following the implementation are corrected to mitigate the influence of the multipath. The MHM_V model proposed in this paper is verified and compared with the traditional MHM algorithm by using the observed data of the Forth Road Bridge with a seven day and 10 s sampling rate. The results show that the correlation coefficient of the multipath on two adjacent days was increased by about 10% after residual denoising with the VMD algorithm; the standard deviations of residual error in the L1/L2 frequencies were improved by 37.8% and 40.7%, respectively, which were better than the scores of 26.1% and 31.0% for the MHM algorithm. Taking a ratio equal to three as the threshold value, the fixed success rates of ambiguity were 88.0% without multipath mitigation and 99.4% after mitigating the multipath with MHM_V. The MHM_V algorithm can effectively improve the success rate, reliability, and convergence rate of ambiguity resolution in a bridge multipath environment and perform better than the MHM algorithm.

scholarly journals Measurement of Physical Parameters of Water Quality in Real-Time Based on Arduino

2021 ◽  
Vol 1751 ◽  
pp. 012067
Author(s):  
Junaidi ◽  
T M Putra ◽  
A Surtono ◽  
G A Puazi ◽  
S W Suciyati ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Physical Parameters

scholarly journals Nanometre-Scale Visualization of Chemical Parameter Changes by T1-Weighted ODMR Imaging Using a Fluorescent Nanodiamond

Chemosensors ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 68
Author(s):  
Takahiro Fujisaku ◽  
Ryuji Igarashi ◽  
Masahiro Shirakawa
Keyword(s):  
Magnetic Resonance ◽  
Laser Pulse ◽  
Real Time ◽  
Physical Parameters ◽  
Biological Processes ◽  
Chemical Parameter ◽  
Ph Conditions ◽  
Optically Detected ◽  
Life Phenomena ◽  
Selection Of

The dynamics of physical parameters in cells is strongly related to life phenomena; thus, a method to monitor and visualize them on a single-organelle scale would be useful to reveal unknown biological processes. We demonstrate real-time nanometre-scale T1-weighted imaging using a fluorescent nanodiamond. We explored optically detected magnetic resonance (ODMR) contrast at various values of interval laser pulse (τ), showing that sufficient contrast is obtained by appropriate selection of τ. By this method, we visualized nanometre-scale pH changes using a functionalized nanodiamond whose T1 has a dependence on pH conditions.

scholarly journals Development of a Raspberry Pi-Based Sensor System for Automated In-Field Monitoring to Support Crop Breeding Programs

Inventions ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 42
Author(s):  
Worasit Sangjan ◽  
Arron H. Carter ◽  
Michael O. Pumphrey ◽  
Vadim Jitkov ◽  
Sindhuja Sankaran
Keyword(s):  
Real Time ◽  
Imaging System ◽  
Crop Growth ◽  
Sensor System ◽  
Plant Phenotyping ◽  
Raspberry Pi ◽  
The Internet ◽  
Growth Stages ◽  
Crop Breeding ◽  
Breeding Programs

Sensor applications for plant phenotyping can advance and strengthen crop breeding programs. One of the powerful sensing options is the automated sensor system, which can be customized and applied for plant science research. The system can provide high spatial and temporal resolution data to delineate crop interaction with weather changes in a diverse environment. Such a system can be integrated with the internet to enable the internet of things (IoT)-based sensor system development for real-time crop monitoring and management. In this study, the Raspberry Pi-based sensor (imaging) system was fabricated and integrated with a microclimate sensor to evaluate crop growth in a spring wheat breeding trial for automated phenotyping applications. Such an in-field sensor system will increase the reproducibility of measurements and improve the selection efficiency by investigating dynamic crop responses as well as identifying key growth stages (e.g., heading), assisting in the development of high-performing crop varieties. In the low-cost system developed here-in, a Raspberry Pi computer and multiple cameras (RGB and multispectral) were the main components. The system was programmed to automatically capture and manage the crop image data at user-defined time points throughout the season. The acquired images were suitable for extracting quantifiable plant traits, and the images were automatically processed through a Python script (an open-source programming language) to extract vegetation indices, representing crop growth and overall health. Ongoing efforts are conducted towards integrating the sensor system for real-time data monitoring via the internet that will allow plant breeders to monitor multiple trials for timely crop management and decision making.

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