2002 ◽  
Vol 25 (4) ◽  
pp. 569-575 ◽  
Author(s):  
S.V. Garimella ◽  
Y.K. Joshi ◽  
A. Bar-Cohen ◽  
R. Mahajan ◽  
K.C. Toh ◽  
...  

Author(s):  
Yinka-Banjo Chika ◽  
Salau Abiola Adekunle

Smart fabrics, generally regarded as smart Textiles are fabrics that have embedded electronics and interconnections woven into them, resulting in physical flexibility that is not achievable with other known electronic manufacturing techniques. Interconnections and components are intrinsic to the fabric therefore are not visible and less susceptible of getting tangled by surrounding objects. Smart fabrics can also more easily adapt to quick changes in the sensing and computational requirements of any specific application, this feature being useful for power management and context awareness. For electronic systems to be part of our day-to-day outfits such electronic devices need to conform to requirements as regards wear-ability, this is the vision of wearable technology. Wearable systems are characterized by their capability to automatically identify the activity and the behavioral status of their wearer as well as of the situation around them, and to use this information to adjust the systems' configuration and functionality. This write-up focused on recent developments in the field of Smart Fabrics and pays particular attention to the materials and their manufacturing techniques.


Author(s):  
Xiaoliang Chen ◽  
Peng Sun ◽  
Hongmiao Tian ◽  
Xiangming Li ◽  
Chunhui Wang ◽  
...  

Flexible and stretchable conductors are critical elements for constructing soft electronic systems and have recently attracted tremendous attention. Next generation electronic devices call for self-healing conductors that can mimic the...


2005 ◽  
Vol 14 (06) ◽  
pp. 1173-1182
Author(s):  
LAKSHMI PRABHA VISWANATHAN ◽  
ELWIN CHANDRA MONIE

Dynamic power management is a technique to reduce power consumption of electronic systems by selectively shutting down idle components. In this paper, an intelligent approach is presented based on reinforcement learning to predict the best policy amongst the existing DPM policies. Reinforcement learning is a computational approach to understanding and automating goal-directed learning and decision-making. The effectiveness of this approach is demonstrated by an event-driven simulator, which is designed using JAVA for power-manageable embedded devices. The results of the experiments conducted in this regard establish that the proposed DPM scheme enhances power savings by 10 to 28%.


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