Towards Usage of Wireless MEMS Networks in Industrial Context

Minet, Pascale; Bourgeois, Julien

doi:10.1109/dmems.2012.18

Cited by 2 publications

(2 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For that, the average [2] differentiation rate of our models has been computed. Figure 9 shows also the average differentiation rate of group {O, L, I}.…”

Section: Offline Phasementioning

confidence: 99%

Simulation to help calibration of a MEMS sensor network

Dedu

Bourgeois

Boutoustous

2010

International Journal of Pervasive Computing and Communications

Self Cite

View full text Add to dashboard Cite

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to present a calibrator to determine the best grid size of a Smart Surface. The Smart Surface is a micro-electro mechanical systems (MEMS) whose goal is to sort micro-parts. Design/methodology/approach -The possible micro-parts are rotated and translated, and their characteristics are stored in a database. Afterwards, when such a micro-part is laid off the Smart Surface, its characteristics are compared to database values. Simulations show that some grid sizes are better than others in terms of success in part recognition. Findings -The tests performed on all groups of three out of four models show that a sensors grid of (35, 35) is an appropriate parameter for the Smart Surface.Research limitations/implications -The authors plan to work on a more general case, using any kinds of parts. Practical implications -The work allows the automation of the process of sorting micro-parts, in assembly lines for example. Originality/value -Few works exist for part recognition on very small parts and for choosing the best discretization scale.

show abstract

“…For that, the average [2] differentiation rate of our models has been computed. Figure 9 shows also the average differentiation rate of group {O, L, I}.…”

Section: Offline Phasementioning

confidence: 99%

Simulation to help calibration of a MEMS sensor network

Dedu

Bourgeois

Boutoustous

2010

International Journal of Pervasive Computing and Communications

Self Cite

View full text Add to dashboard Cite

show abstract

“…The benefits of integrating wireless communication technology with industrial applications are compelling. Some exploratory work has been done such as drip irrigation control for agriculture using wireless sensor and actuator network (WSAN) [4], environment control system in WSAN [5,6], wireless ventilation systems in mining industrial [7], wireless fire detection and control [8], towards usage of wireless MEMS in industrial context [9], and monitoring system for robots and inventories in assembly line based on wireless sensor networks (WSNs) [10].…”

Section: Introductionmentioning

confidence: 99%

Distributed Estimation Fusion and Control with Packet Losses for Industrial Wireless Sensor and Actuator Networks

Ren

Liu

2014

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

This paper is concerned with a reliable solution to the distributed estimation and control issues over hybrid two-tier industrial wireless sensor and actuator networks (IWSANs). It aims at applying wireless technology to industrial automation control domains in hash industrial environment. A main challenge in these application domains is that wireless communication channels must satisfy strict requirements of real time and reliability. Therefore, first, we propose a new interacting dual model (IDM) adaptive estimation algorithm to identify the unreliable wireless communication channels, and, second, to further enhance the accuracy and fault tolerance of state estimation for controlled plant, a federated multisensor estimation fusion approach is presented. Furthermore, considering that the IWSANs need commonly to be deployed over a vast geographical area, a distributed collaborative control strategy is adopted. Finally, an example of temperature control illustrates the effectiveness of the proposed method.

show abstract

Towards Usage of Wireless MEMS Networks in Industrial Context

Cited by 2 publications

References 46 publications

Simulation to help calibration of a MEMS sensor network

Simulation to help calibration of a MEMS sensor network

Distributed Estimation Fusion and Control with Packet Losses for Industrial Wireless Sensor and Actuator Networks

Contact Info

Product

Resources

About