An Adaptive Energy Saving Mechanism for the IEEE 802.15.4 LR-WPAN

2006 ◽  
pp. 38-46 ◽  
Author(s):  
Dong-Hoon Cho ◽  
Jung-Hoon Song ◽  
Ki-Jun Han
Keyword(s):  
Energy Saving ◽  
Ieee 802.15.4

Cellular Automata-Based WSN Energy Saving Technology

2012 ◽  
Vol 546-547 ◽  
pp. 1334-1339 ◽  
Author(s):  
Wei Qiao Li ◽  
Qin Yu ◽  
Li Xiang Ma
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Cellular Automata ◽  
Energy Saving ◽  
Sensor Network ◽  
Ieee 802.15.4 ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Utilization Rate ◽  
Continuous Power

Wireless sensor network is a new type of wireless network. IEEE 802.15.4 / Zigbee standards with low energy consumption, low speed characteristics has been widely used in wireless sensor network. As the wireless sensor nodes are often set in complex geographical environment and had not continuous power supply, thus saving energy has been one of the main directions of research at home and abroad. Cellular automata are a mimic biological cell reproduction form of dynamical system, with a simple rule to reveal the complex global characteristics. This paper presents a kind of cellular automata and Zigbee based wireless sensor network binding mechanism, so that the wireless node according to the communication state during hibernation and job switching between states in order to achieve the purpose of energy saving. Simulations show that the mechanism can reduce the network energy consumption, improve energy utilization rate, and prolong the survival time of the node.

Subjective Time Preference and Willingness to Pay for an Energy-Saving Durable Good

2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink
Keyword(s):  
Willingness To Pay ◽  
Energy Saving ◽  
Subjective Time ◽  
Durable Good ◽  
Discount Function ◽  
Hyperbolic Discount ◽  
The One ◽  
Two Parameter ◽  
Difference Effect ◽  
Better Than

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.

Assessing IECC Energy Saving Potential for Residential Construction in Florida

2012 ◽  
Author(s):  
A. A. Raheem ◽  
R. R. A. Issa ◽  
S. Olbina
Keyword(s):  
Energy Saving ◽  
Residential Construction ◽  
Energy Saving Potential

Energy Saving Model of Three-Section Natural Ventilation for Shaft-Collecting Shed-Chimney of Highway Tunnel and Its Application

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Xuan Zheng ◽  
Dawei Guo ◽  
Xue Li ◽  
Jiaxin Shi
Keyword(s):  
Energy Saving ◽  
Natural Ventilation ◽  
Highway Tunnel

Renewables, energy saving and welfare in Italian fragile rural areas

2016 ◽  
pp. 102-118 ◽  
Author(s):  
Giorgio Osti
Keyword(s):  
Energy Saving ◽  
Rural Areas

Danieli Endless Casting and Rolling: Energy-Saving Technology for the Rebar Market

2020 ◽  
Author(s):  
F. Tortul ◽  
M. Cimolino ◽  
S. Ronco ◽  
A. De Luca
Keyword(s):  
Energy Saving ◽  
Energy Saving Technology

Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG
Keyword(s):  
Control System ◽  
Machine Vision ◽  
Energy Saving ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Lighting Control ◽  
Lighting Energy ◽  
Neural Network Algorithm ◽  
Energy Saving Control ◽  
Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

ENERGY-SAVING ELECTRIC DRIVE OF A DRY DOCK DEWATERING PUMPS BASED DIFFERENTIAL CASCADE

2016 ◽  
Vol 22 (98) ◽  
pp. 200-210
Author(s):  
Paul E. Hristo ◽  
Keyword(s):  
Energy Saving ◽  
Electric Drive ◽  
Dry Dock
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