scholarly journals Wireless Sensor Network for in situ Soil Moisture Monitoring

Author(s):  
Jianing Fang ◽  
Chuheng Hu ◽  
Nour Smaoui ◽  
Doug Carlson ◽  
Jayant Gupchup ◽  
...  
2012 ◽  
Vol 04 (08) ◽  
pp. 202-209 ◽  
Author(s):  
Aurelio Cano ◽  
José Luís Añón ◽  
Candid Reig ◽  
Cristina Millán-Scheiding ◽  
Ernesto López-Baeza

2017 ◽  
Vol 07 (10) ◽  
pp. 288-300 ◽  
Author(s):  
José O. Payero ◽  
Ali Mirzakhani Nafchi ◽  
Rebecca Davis ◽  
Ahmad Khalilian

2018 ◽  
Vol 1028 ◽  
pp. 012058
Author(s):  
Baihaqi Siregar ◽  
AB Azmi Nasution ◽  
Lukman Adlin ◽  
Ulfi Andayani ◽  
Fahmi Fahmi

Due to the recent advancements in the fields of Micro Electromechanical Sensors (MEMS), communication, and operating systems, wireless remote monitoring methods became easy to build and low cost option compared to the conventional methods such as wired cameras and vehicle patrols. Pipeline Monitoring Systems (PMS) benefit the most of such wireless remote monitoring since each pipeline would span for long distances up to hundreds of kilometers. However, precise monitoring requires moving large amounts of data between sensor nodes and base station for processing which require high bandwidth communication protocol. To overcome this problem, In-Situ processing can be practiced by processing the collected data locally at each node instead of the base station. This Paper presents the design and implementation of In-situ pipeline monitoring system for locating damaging activities based on wireless sensor network. The system built upon a WSN of several nodes. Each node contains high computational 1.2GHz Quad-Core ARM Cortex-A53 (64Bit) processor for In-Situ data processing and equipped in 3-axis accelerometer. The proposed system was tested on pipelines in Al-Mussaib gas turbine power plant. During test knocking events are applied at several distances relative to the nodes locations. Data collected at each node are filtered and processed locally in real time in each two adjacent nodes. The results of the estimation is then sent to the supervisor at base-station for display. The results show the proposed system ability to estimate the location of knocking event.


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