scholarly journals Indoor Localisation of Wireless Sensor Nodes Towards Internet of Things

2017 ◽  
Vol 109 ◽  
pp. 92-99 ◽  
Author(s):  
P.Z. Sotenga ◽  
K. Djouani ◽  
A.M. Kurien ◽  
M.M. Mwila
Keyword(s):  
Internet Of Things ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Indoor Localisation

Design and Implementation of the CNC Monitoring System Based on Internet of Things

2014 ◽  
Vol 945-949 ◽  
pp. 1552-1557 ◽  
Author(s):  
Yi Lin Zheng ◽  
Hu Lin ◽  
Xian Li Su
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Long Distance ◽  
Wireless Sensor Nodes ◽  
Communication Signal ◽  
Cable Laying ◽  
Distance Communication ◽  
Internet Of Things Technology

Aiming at the shortcomings of the traditional CNC sensor network such as the difficult cable laying and long-distance communication signal attenuation, this paper designed the CNC monitoring system based on Internet of Things technology. The design reduced the power consumption of the wireless sensor nodes and the packet loss rate of the sink nodes through the hardware-software co-design. The Internet of Things protocol presented in this paper achieved the real-time communication between the CNC operating platform and the wireless sensor nodes. The experiment result shows that the CNC monitoring system based on Internet of Things technology can provide the temperature and vibration information for the CNC operating platform in time with the advantages of simple layout and reliable communication.

scholarly journals A Node Density Control Learning Method for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3428 ◽  
Author(s):  
Shumei Lou ◽  
Gautam Srivastava ◽  
Shuai Liu
Keyword(s):  
Internet Of Things ◽  
Power Consumption ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Learning Method ◽  
Mobile Nodes ◽  
Node Density ◽  
Wireless Sensor Nodes ◽  
Density Control ◽  
Control Learning

When examining density control learning methods for wireless sensor nodes, control time is often long and power consumption is usually very high. This paper proposes a node density control learning method for wireless sensor nodes and applies it to an environment based on Internet of Things architectures. Firstly, the characteristics of wireless sensors networks and the structure of mobile nodes are analyzed. Combined with the flexibility of wireless sensor networks and the degree of freedom of real-time processing and configuration of field programmable gate array (FPGA) data, a one-step transition probability matrix is introduced. In addition, the probability of arrival of signals between any pair of mobile nodes is also studied and calculated. Finally, the probability of signal connection between mobile nodes is close to 1, approximating the minimum node density at T. We simulate using a fully connected network identifying a worst-case test environment. Detailed experimental results show that our novel proposed method has shorter completion time and lower power consumption than previous attempts. We achieve high node density control as well at close to 90%.

scholarly journals Dynamic Monitoring Of Agricultural Cultivation using IoT and Cloud Mechanism

2019 ◽  
Vol 8 (9) ◽  
pp. 556-560
Keyword(s):  
Data Analysis ◽  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Sensor Network ◽  
Monitoring System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Monitoring ◽  
Wireless Sensor Nodes ◽  
Acquisition Strategies

The objective of this work is a dynamic monitoring of agricultural cultivation using WSN technology. The Wireless Sensor nodes are designed in controlling and supervising the factors of variegated of such as level of water, humidity, and temperature. ZigBee mechanism is used as a medium of transmission in WSN (Wireless Sensor Network) devices using sensors, routers which propagate the data to longer distance over a network, with the help of coordinator sensor and will transmit the data to the cloud computer, which in turn will illustrate the control and data in the monitoring system. The node sensor will extract the factors of agriculture from various sources on realtime and will transmit the data using IoT (Internet of Things), which is integrated with one another on various platforms for performing various types of actions and will reduce the need of labor. Apart from monitoring, enhancement of details can be proposed based on WSN for the deployment of various nodes and by applying digital acquisition strategies for acquisition of data and performing various types of data analysis on cloud using the collected information of agriculture

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