scholarly journals Realization of Zigbee Wireless Sensor Networks for Temperature and Humidity Monitoring

Author(s):  
Helmy Fitriawan ◽  
Danny Mausa ◽  
Ahmad Surya Arifin ◽  
Agus Trisanto
2013 ◽  
Vol 40 ◽  
pp. 1156-1166 ◽  
Author(s):  
Norberto Barroca ◽  
Luís M. Borges ◽  
Fernando J. Velez ◽  
Filipe Monteiro ◽  
Marcin Górski ◽  
...  

Author(s):  
Дмитро Дмитрович Соколов ◽  
Вікторія Юріївна Мерлак ◽  
Олександр Олександрович Орєхов ◽  
Анатолій Павлович Плахтеев

The article is devoted to the development of a monitoring system based on wireless sensor networks. The purpose of the article is to implement a system for environmental monitoring using wireless sensor networks, as well as its application in an apiary. Wireless sensor networks and their participation in environmental monitoring were investigated, and the interaction of a wireless network and data transfer protocols were described. The monitoring system was reviewed and analyzed, as well as systems in which monitoring is already applied. An experiment was conducted in which it was checked at what maximum distance the temperature and humidity parameters can be transmitted, the experiment was conducted with obstacles and without obstruction. Routing algorithms were examined how they work and how parameters (temperature and humidity) are transferred from sensors to the server. A prototype of a ground-based monitoring system for environmental monitoring was developed based on the wireless technology of building Zigbee sensor networks, taking into account the fact that new nodes can be added to this network or completely replaced. It was also found a solution to how to apply a wireless network in such an area as beekeeping. A mesh topology was selected and the physical devices that are the nodes of the network are separated. Nodes were also designed using as the base station for Arduino sensors and as ZigBee database modules from Digi called XBee. A study of these nodes on the noise immunity and stability of data transmission using sensors of flame, smoke, and temperature with humidity. The study revealed that XBee nodes are very unstable working next to Wi-Fi routers and in case of interference in the form of a forest. A statement of the problem was formed, which showed the relevance of the given system, why it is needed, who will be able to apply it, and also what the system contains and how it works. The functions that the program performs are listed. The conclusion is formulated on the result of the experiment, as well as how the system can be further upgraded, what can be added and what parameters can still be observed.


Author(s):  
R.M. Ilyin ◽  
◽  
S.V. Vtory

The results of a study of changes in temperature and humidity conditions and concentration of carbon dioxide depending on weather conditions in cowsheds for 200 heads of tethered and 320 heads of loose housing are presented. The graphical models of the distribution of temperature, humidity and carbon dioxide concentration inside the cowsheds under similar weather conditions are provided.


2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Mengying Xu ◽  
Jie Zhou

The research of agricultural wireless sensor networks (AWSNs) plays an important role in the field of facility agricultural technology. The temperature and humidity nodes in AWSNs are so tiny that they are limited on computation, network management, information collection, and storage size. Under this condition, task allocation plays a key role in improving the performance of AWSNs to reduce energy consumption and computational constraints. However, the optimization of task allocation is a nonlinearly constrained optimization problem whose complexity increases when constraints such as limited computing capabilities and power are undertaken. In this paper, an elite immune ant colony optimization (EIACO) is proposed to deal with the problem of task allocation optimization, which is motivated by immune theory and elite optimization theory. The EIACO uses ant colony optimization (ACO) to combine the clone operator and elite operator together for the optimization of task allocation. The performances of EIACO with different numbers of temperature and humidity sensor nodes and tasks have been compared by both genetic algorithm (GA) and simulated annealing (SA) algorithm. Simulation results show that the proposed EIACO has a better task execution efficiency and higher convergence speed than GA and SA. Furthermore, the convergence speed of EIACO is faster than GA and SA. Therefore, the whole system efficiency can be improved by the proposed algorithm.


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