Main Article Content

Jose-Luis Jiménez-García
Universitat Politècnica de València
Spain
Biography
David Baselga-Masia
School of Engineering in Computer Science, Universitat Politècnica de València
Spain
Biography
Jose-Luis Poza-Luján
Universitat Politècnica de València
Spain
Biography
Eduardo Munera
Universitat Politècnica de València
Spain
Biography
Juan-Luis Posadas-Yagüe
Universitat Politècnica de València
Spain
Biography
José-Enrique Simó-Ten
Universitat Politècnica de València
Spain
Biography
Vol. 3 No. 1 (2014), Articles, pages 46-55
DOI: https://doi.org/10.14201/ADCAIJ2014384655
Accepted: Oct 15, 2014
Copyright

Abstract

Embedded control systems usually are characterized by its limitations in terms of computational power and memory. Although this systems must deal with perpection and actuation signal adaptation and calculate control actions ensuring its reliability and providing a certain degree of fault tolerance. The allocation of these tasks between some different embedded nodes conforming a distributed control system allows to solve many of these issues. For that reason is proposed the application of smart devices aims to perform the data processing tasks related with the perception and actuation and offer a simple interface to be configured by other nodes in order to share processed information and raise QoS based alarms. In this work is introduced the procedure of implementing a smart device as a sensor as an embedded node in a distributed control system. In order to analyze its benefits an application based on a RGBD sensor implemented as an smart device is proposed.

Downloads

Download data is not yet available.

Article Details

References

Bradski, Gary; Kaehler, Adrian. Learning OpenCV: Computer vision with the OpenCV library. " O'Reilly Media, Inc.", 2008.

Brignell, J. E. The future of intelligent sensors: a problem of technology or ethics?. Sensors and Actuators A: Physical, 1996, vol. 56, no 1, p. 11-15.

Cuesta, Federico; Ollero, Aníbal. Intelligent mobile robot navigation. Springer, 2005.

Dan, Asit, et al. Buffering and caching in large-scale video servers. IEEE, 1995.

Edwards, Chris. Not-so-humble raspberry pi gets big ideas. Engineering & Technology, 2013, vol. 8, no 3, p. 30-33.

Falahati, Soroush. OpenNI Cookbook. Packt Publishing Ltd, 2013.

Fernandes, João, et al. A context aware architecture to support people with partial visual impairments. In Distributed Computing and Artificial Intelligence. Springer International Publishing, 2013. p. 333-340.

Ferrari, Paolo; Flammini, Alessandra; Sisinni, Emiliano. New architecture for a wireless smart sensor based on a software-defined radio. Instrumentation and Measurement, IEEE Transactions on, 2011, vol. 60, no 6, p. 2133-2141.

Freese, Marc, et al. Virtual robot experimentation platform v-rep: a versatile 3d robot simulator. In Simulation, Modeling, and Programming for Autonomous Robots. Springer Berlin Heidelberg, 2010. p. 51-62.

Gamma, Erich, et al. Design patterns: elements of reusable object-oriented software. Pearson Education, 1994.

Gonzalez-Jorge, H., et al. Metrological evaluation of microsoft kinect and asus xtion sensors. Measurement, 2013, vol. 46, no 6, p. 1800-1806.

Grzejszczak, Tomasz, et al. Gesture based robot control. In Computer Vision and Graphics. Springer Berlin Heidelberg, 2012. p. 407-413.

Hintjens, Pieter. ZeroMQ: Messaging for Many Applications. " O'Reilly Media, Inc.", 2013.

Jimenez-Garcia, Jose-Luis, et al. Performance and Results of the Triple Buffering Built-In in a Raspberry PI to Optimize the Distribution of Information from a Smart Sensor. In Distributed Computing and Artificial Intelligence, 11th International Conference. Springer International Publishing, 2014. p. 279-286.

Khan, Shujjat; BAILEY, Donald; Gupta, G. Simulation of Triple Buffer Scheme. In Second International Conference on Computer and Electrical Engineering. 2009.

Lee, Chae Sub; LEE, Gyu Myoung; Rhee, Woo-Seop. Standardization and challenges of smart ubiquitous networks in ITU-T. IEEE Communications Magazine, 2013, vol. 51, no 10, p. 102-110.

Lian, Feng-Li; MOYNE, William; Tilbury, Dawn. Network design consideration for distributed control systems. Control Systems Technology, IEEE Transactions on, 2002, vol. 10, no 2, p. 297-307.

Liao, Chien-Hui Christina, et al. Fall Detection by a SVM-Based Cloud System with Motion Sensors. In Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Springer Netherlands, 2014. p. 37-45.5

Peterson, Larry L.; Davie, Bruce S. Computer networks: a systems approach. Elsevier, 2007.

Poza-Luján, José-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique. Quality of Control and Quality of Service in Mobile Robot Navigation.International Journal of Imaging and Robotics, 2014, vol. 8, no 1.

Tagami, Yuya; Watanabe, Makoto; Yamaguchi, Yuko. Development Environment of 3D Graphics Systems. Fujitsu Scientific & Technical Journal, 2013, vol. 49, no 1, p. 64-70.

Upton, Eben; Halfacree, Gareth. Raspberry Pi user guide. John Wiley & Sons, 2013.

Van Oosterhout, Tim; Kröse, B.; Englebienne, Gwenn. People counting with stereo cameras: two template-based solutions. In International Conference on Computer Vision Theory and Applications (2) 2012, pp. 404-408.

Villaroman, Norman; Rowe, Dale; Swan, Bret. Teaching natural user interaction using OpenNI and the Microsoft Kinect sensor. In Proceedings of the 2011 conference on Information technology education. ACM, 2011. p. 227-232.