Energy efficient sensor network implementations

Conference · Wed Dec 31 23:00:00 EST 2008

OSTI ID:970577

Frigo, Janette R ^[1]; Raby, Eric Y ^[1]; Brennan, Sean M ^[1]; Kulathumani, Vinod ^[2]; Rosten, Ed ^[3]; Wolinski, Christophe ^[4]; Wagner, Charles ^[4]; Charot, Francois ^[4]

---

1. Los Alamos National Laboratory
2. WEST VIRGINIA UNIV.
3. CAMBRIDGE UNIV.
4. IRISA

In this paper, we discuss a low power embedded sensor node architecture we are developing for distributed sensor network systems deployed in a natural environment. In particular, we examine the sensor node for energy efficient processing-at-the-sensor. We analyze the following modes of operation; event detection, sleep(wake-up), data acquisition, data processing modes using low power, high performance embedded technology such as specialized embedded DSP processors and a low power FPGAs at the sensing node. We use compute intensive sensor node applications: an acoustic vehicle classifier (frequency domain analysis) and a video license plate identification application (learning algorithm) as a case study. We report performance and total energy usage for our system implementations and discuss the system architecture design trade offs.

• Research Organization: Los Alamos National Laboratory (LANL)
• Sponsoring Organization: DOE
• DOE Contract Number: AC52-06NA25396
• OSTI ID: 970577
• Report Number(s): LA-UR-09-05907; LA-UR-09-5907
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ACOUSTICS
ARCHITECTURE
CLASSIFICATION
DATA ACQUISITION
DATA PROCESSING
DESIGN
DETECTION
LEARNING
PERFORMANCE
PLATES