scholarly journals LEHER - LOW-COST ENHANCED HYDRO-NAVIGATION SYSTEM ENSURING REAL-TIME MONITORING OF SHIPS WITH THE HELP OF RASPBERRY PI, ROCKBLOCK 9603 SATELLITE COMMUNICATION MODULE AND A COUPLE OF OTHER SENSORS

Author(s):  
Prithwijit Das ◽  
2020 ◽  
Vol 15 ◽  
pp. 155892502097726
Author(s):  
Wei Wang ◽  
Zhiqiang Pang ◽  
Ling Peng ◽  
Fei Hu

Performing real-time monitoring for human vital signs during sleep at home is of vital importance to achieve timely detection and rescue. However, the existing smart equipment for monitoring human vital signs suffers the drawbacks of high complexity, high cost, and intrusiveness, or low accuracy. Thus, it is of great need to develop a simplified, nonintrusive, comfortable and low cost real-time monitoring system during sleep. In this study, a novel intelligent pillow was developed based on a low-cost piezoelectric ceramic sensor. It was manufactured by locating a smart system (consisting of a sensing unit i.e. a piezoelectric ceramic sensor, a data processing unit and a GPRS communication module) in the cavity of the pillow made of shape memory foam. The sampling frequency of the intelligent pillow was set at 1000 Hz to capture the signals more accurately, and vital signs including heart rate, respiratory rate and body movement were derived through series of well established algorithms, which were sent to the user’s app. Validation experimental results demonstrate that high heart-rate detection accuracy (i.e. 99.18%) was achieved in using the intelligent pillow. Besides, human tests were conducted by detecting vital signs of six elder participants at their home, and results showed that the detected vital signs may well predicate their health conditions. In addition, no contact discomfort was reported by the participants. With further studies in terms of validity of the intelligent pillow and large-scale human trials, the proposed intelligent pillow was expected to play an important role in daily sleep monitoring.


2015 ◽  
Vol 47 (3) ◽  
pp. 236-251 ◽  
Author(s):  
Bambang Kuswandi ◽  
Fitria Damayanti ◽  
Jayus Jayus ◽  
Aminah Abdullah ◽  
Lee Yook Heng

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4093
Author(s):  
Alimed Celecia ◽  
Karla Figueiredo ◽  
Marley Vellasco ◽  
René González

The adequate automatic detection of driver fatigue is a very valuable approach for the prevention of traffic accidents. Devices that can determine drowsiness conditions accurately must inherently be portable, adaptable to different vehicles and drivers, and robust to conditions such as illumination changes or visual occlusion. With the advent of a new generation of computationally powerful embedded systems such as the Raspberry Pi, a new category of real-time and low-cost portable drowsiness detection systems could become standard tools. Usually, the proposed solutions using this platform are limited to the definition of thresholds for some defined drowsiness indicator or the application of computationally expensive classification models that limits their use in real-time. In this research, we propose the development of a new portable, low-cost, accurate, and robust drowsiness recognition device. The proposed device combines complementary drowsiness measures derived from a temporal window of eyes (PERCLOS, ECD) and mouth (AOT) states through a fuzzy inference system deployed in a Raspberry Pi with the capability of real-time response. The system provides three degrees of drowsiness (Low-Normal State, Medium-Drowsy State, and High-Severe Drowsiness State), and was assessed in terms of its computational performance and efficiency, resulting in a significant accuracy of 95.5% in state recognition that demonstrates the feasibility of the approach.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4350
Author(s):  
Rui Lu ◽  
Jiwu Lu ◽  
Ping Liu ◽  
Min He ◽  
Jiangwei Liu

The VRLA (valve-regulated lead-acid) battery is an important part of a direct current (DC) power system. In order to resolve issues of large volume, complicated wiring, and single function for a battery monitoring system at present, we propose to build a novel intelligent-health-monitoring system. The system is based on the ZigBee wireless communication module for collecting voltage, temperature, internal resistance, and battery current in real-time. A general packet radio service (GPRS) network is employed for interacting data with the cloud-monitoring platform. The system can predict the remaining capacity of the battery combined with the software algorithm for realizing real-time monitoring of the battery’s health status and fault-warning, providing a basis for ensuring the safe and reliable operation of the battery. In addition, the system effectively integrates most of the circuits of the battery status collector onto one chip, which greatly reduces the size and the power consumption of the collector and also provides a possibility for embedding each VRLA battery with a chip that can monitor the health status during the whole life. The test results indicate that the system has the characteristics of real-time monitoring, high precision, small-volume, and comprehensive functions.


Micromachines ◽  
2017 ◽  
Vol 8 (10) ◽  
pp. 292
Author(s):  
Carlos Polanco ◽  
Ignacio Vazquez ◽  
Adrian Martinez-Rivas ◽  
Miguel Arias-Estrada ◽  
Thomas Buhse ◽  
...  

2013 ◽  
Vol 65 (2) ◽  
pp. 103-108 ◽  
Author(s):  
Yuichi Aoyama ◽  
Koichiro Doi ◽  
Kazuo Shibuya ◽  
Harumi Ohta ◽  
Iuko Tsuwa

2011 ◽  
Vol 127 (2) ◽  
pp. 749-754 ◽  
Author(s):  
S. Piermarini ◽  
G. Volpe ◽  
M. Esti ◽  
M. Simonetti ◽  
G. Palleschi

Sign in / Sign up

Export Citation Format

Share Document