Experiments With Sensor Motes and Java-DSP

Distributed wireless sensor networks (WSNs) are being proposed for various applications including defense, security, and smart stages. The introduction of hardware wireless sensors in a signal processing education setting can serve as a paradigm for data acquisition, collaborative signal processing, or simply as a platform for obtaining, processing, and analyzing real-life real-time data. In this paper, a software interface that enables the Java-digital signal processing (J-DSP) visual programming environment to communicate in a two-way manner with a wireless sensor network is presented. This interface was developed by writing nesC (an extension to the C programming language for sensors) code that enables J-DSP to issue commands to multiple wireless sensor motes, activate specific transducers, and analyze data using any of the existing J-DSP signal processing functions in real time. A series of exercises were developed and disseminated to provide hardware experiences to signals and systems and signal processing undergraduate students. The hardware with the J-DSP software has been used for two semesters in the senior level digital signal processing (DSP) course at Arizona State University. The interface, the exercises, and their assessment (instruments and results) are described in the paper.

[1]  Andreas Spanias,et al.  Interactive online undergraduate laboratories using J-DSP , 2005, IEEE Transactions on Education.

[2]  Visar Berisha,et al.  Real-time acoustic monitoring using wireless sensor motes , 2006, 2006 IEEE International Symposium on Circuits and Systems.

[3]  David E. Culler,et al.  The nesC language: A holistic approach to networked embedded systems , 2003, PLDI.

[4]  Kathleen E. Wage,et al.  Development of the Signals and Systems Concept Inventory (SSCI) assessment instrument , 2001, 31st Annual Frontiers in Education Conference. Impact on Engineering and Science Education. Conference Proceedings (Cat. No.01CH37193).

[5]  T. Kasparis,et al.  Work in progress - multi-university development and dissemination of online laboratories in probability theory, signals and systems, and multimedia computing , 2005, Proceedings Frontiers in Education 35th Annual Conference.

[6]  Venkatraman Atti,et al.  On-line signal processing using J-DSP , 2004, IEEE Signal Processing Letters.

[7]  Stuart C. Shapiro.  LISP: An interactive approach , 1986 .

[8]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[9]  H. Kwon,et al.  Real-Time Implementation of a Distributed Voice Activity Detector , 2006, Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006..

[10]  I. Akyildiz.  WIRELESS MULTIMEDIA SENSOR NETWORKS : A SURVEY The uthors discusse , .

[11]  Andreas Spanias,et al.  Development of new functions and scripting capabilities in JavaA-DSP for easy creation and seamless integration of animated DSP simulations in Web courses , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  Visar Berisha,et al.  Real-Time Collaborative Monitoring in Wireless Sensor Networks , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[13]  Deborah Estrin,et al.  Guest Editors' Introduction: Overview of Sensor Networks , 2004, Computer.

[14]  Gyula Simon,et al.  Shooter localization in urban terrain , 2004, Computer.

[15]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[16]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[17]  Mani Srivastava,et al.  Overview of sensor networks , 2004 .

[18]  Akbar M. Sayeed,et al.  Detection, Classification and Tracking of Targets in Distributed Sensor Networks , 2002 .