scholarly journals Wireless Sensor Network Based on a Chemocapacitive Sensor Array for the Real-time Monitoring of Industrial Pollutants

2014 ◽  
Vol 87 ◽  
pp. 564-567 ◽  
Author(s):  
P. Oikonomou ◽  
A. Botsialas ◽  
A. Olziersky ◽  
I. Stratakos ◽  
S. Katsikas ◽  
...  
Sensors ◽  
2018 ◽  
Vol 18 (3) ◽  
pp. 820 ◽  
Author(s):  
Alessandro Pozzebon ◽  
Irene Cappelli ◽  
Alessandro Mecocci ◽  
Duccio Bertoni ◽  
Giovanni Sarti ◽  
...  

2013 ◽  
Vol 475-476 ◽  
pp. 127-131 ◽  
Author(s):  
Jing Jiang Song ◽  
Ying Li Zhu

With the development of agricultural modernization, agricultural environment protection, Wireless Sensor Networks are used in the field of environmental monitoring for modern agriculture, which brings a broad and bright application prospects. The paper presents a real-time monitoring system based ZigBee wireless sensor network and GPRS network. The system gives the hardware design of wireless sensor node and software implementations. The system design provided a guarantee to achieve accurate, remote and real-time monitoring agricultural environmental information.


Author(s):  
Anchana Muankid ◽  
Mahasak Ketcham

The Cardiovascular disease (CVD) is the most of death in the world. Electrocardiogram (ECG) is the graph that shows heart electrical activities. The physician record and detect the abnormal Electrocardiogram (ECG) signal by the Holter monitor that patient need to carry on the device for record ECG signal in 24 hours. Pan-Tomkins algorithm was appropriate for Real-time ECG signal recognition because high accuracy and rapidly analysis. This research propose the Real-time ECG Signal monitoring system for detect the abnormal ECG signal by using Pan-Tomkins algorithm with Wireless Sensor Network. The system separated into 2 part; sender module and receiver module. Experimental the system by using the ECG signal data from MIT-BIH database. Selected 20 samples of abnormal ECG signal then experimental at 10 and 20 meters sender module-receiver module distance, calculate R-R interval and R amplitude threshold The results show that the Real-time ECG signal monitoring system detect 17 abnormal ECG signal, the accuracy is 85%. This systems efficient for detect the abnormal of ECG signal in real-time.


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