Development of Procedures for Information Interaction of Components of an Automated Environmental Monitoring System

Author(s):  
Elena Volkova ◽  
Alexey Solodkov ◽  
Aleksandr Gorelik ◽  
Elena A. Sevryukova ◽  
Alexandr Baskakov
2021 ◽  
Vol 11 (5) ◽  
pp. 2347 ◽  
Author(s):  
Jorge Solis ◽  
Christoffer Karlsson ◽  
Simon Johansson ◽  
Kristoffer Richardsson

This research aims to develop an automatic unmanned aerial vehicle (UAV)-based indoor environmental monitoring system for the acquisition of data at a very fine scale to detect rapid changes in environmental features of plants growing in greenhouses. Due to the complexity of the proposed research, in this paper we proposed an off-board distributed control system based on visual input for a micro aerial vehicle (MAV) able to hover, navigate, and fly to a desired target location without considerably affecting the effective flight time. Based on the experimental results, the MAV was able to land on the desired location within a radius of about 10 cm from the center point of the landing pad, with a reduction in the effective flight time of about 28%.


2013 ◽  
Vol 791-793 ◽  
pp. 870-873
Author(s):  
Zhong Hui Yin ◽  
Bin Hui Zhang ◽  
An Ning Zhang ◽  
Zi Long Jing ◽  
Yu Ming Gu

In order to protect the components of monitoring, some measures should be taken when refuge chamber uses outside environmental monitoring system. This paper designs a kind of protective device for outside environmental monitoring system based on related theory analysis and coal mine environment. It can protect monitoring components from gas explosion shock wave. Meantime there is good contact between sensitive element and outside environment to guarantee the normal work of the monitoring system. Finally, this paper builds the model of protective device, and analyses its structural strength.


2017 ◽  
Vol 13 (08) ◽  
pp. 4
Author(s):  
Yong Jin ◽  
Zhenjiang Qian ◽  
Xiaoshuang Xing ◽  
Lu Shen

ensor nodes vulnerable becomes a major bottleneck restricting the wide application of wireless sensor networks WSNs (Wireless Sensor Networks). In order to satisfy the needs of industrial production and daily living environment monitoring, it is important to improve the survivability of wireless sensor networks in environmental monitoring application. In order to have a reliable environment monitoring system, this paper analyzed the damage types and causes of WSNs and the measurement methods of WSNs survivability. Then, we studied the fault detection method and finally realized the design can improve the survivability of the scheme. The robust guarantee scheme through hardware design and algorithm model, realized the remote wireless communication services and prolonged the network life cycle, so as to improve the survivability of the environmental monitoring system.


2020 ◽  
Vol 11 (4) ◽  
pp. 57-71
Author(s):  
Qiuxia Liu

Using multi-sensor data fusion technology, ARM technology, ZigBee technology, GPRS, and other technologies, an intelligent environmental monitoring system is studied and developed. The SCM STC12C5A60S2 is used to collect the main environmental parameters in real time intelligently. The collected data is transmitted to the central controller LPC2138 through the ZigBee module ATZGB-780S5, and then the collected data is transmitted to the management computer through the GPRS communication module SIM300; thus, the real-time processing and intelligent monitoring of the environmental parameters are realized. The structure of the system is optimized; the suitable fusion model of environmental monitoring parameters is established; the hardware and the software of the intelligent system are completed. Each sensor is set up synchronously at the end of environmental parameter acquisition. The method of different value detection is used to filter out different values. The authors obtain the reliability of the sensor through the application of the analytic hierarchy process. In the analysis and processing of parameters, they proposed a new data fusion algorithm by using the reliability, probability association algorithm, and evidence synthesis algorithm. Through this algorithm, the accuracy of environmental monitoring data and the accuracy of judging monitoring data are greatly improved.


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