1 / 18

Experiences and Challenges in Campaign Style Deployments using Wireless Sensor Networks

This study discusses the practical challenges faced during campaign-style deployments of wireless sensor networks (WSNs) in a tropical ecosystem in Quito, Ecuador. Conducted over 16 days with high data rates and limited power supply, the deployment focused on understanding soil respiration. Key issues included power cycling, sensor range limitations, and the need for on-the-fly data management. Lessons learned emphasize the maturity of WSN technology and the necessity for adaptable sensor configurations and real-time data access for researchers in the field.

rufin
Télécharger la présentation

Experiences and Challenges in Campaign Style Deployments using Wireless Sensor Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Experiences and Challenges in Campaign Style Deployments using Wireless Sensor Networks Jayant Gupchup†, Scott Pitz*, Douglas Carlson† , Chih-Han Chang*, Michael Bernard*, Andreas Terzis†, Alex Szalay±, Katalin Szlavecz* Department of Computer Science, Johns Hopkins University† Department of Physics and Astronomy, Johns Hopkins University± Department of Earth and Planetary Sciences, Johns Hopkins University*

  2. Campaign Style Deployment Quito Jayant Gupchup

  3. Requirements / Constraints Jayant Gupchup • No access to line power or internet • Collect data at a high rate (e.g. 30s) • Deployment order of days to weeks • Researchers require access to data in field

  4. A Typical Sensor Network Stable Storage Gateway/ Basestation ……. 7 Ah

  5. Differences / Challenges Power ~ 4W Jayant Gupchup • On-site decisions • Ad hoc hardware reconfigurations • Dealing with high data rates in the field (using a netbook) • Use of high power sensors • Vaisala CO2 sensors • Driven by a car battery

  6. Deployment Details - I Jayant Gupchup • Location : Quito, Ecuador • Goal : Understand tropical soil respiration • Duration : 16 days

  7. Deployment Details -II Jayant Gupchup • 30s Sampling Interval • Data retrieved over the air using a netbook • 20 Sampling locations • 12 Soil CO2 • 8 Soil Temperature & Moisture • Each CO2 Location • 3 depths (12 locations, 3 depths = 36 sensors) • Vaisala GMT 220 Series • CO2 Powered by 12 V / 45 Ah Car Battery

  8. A CO2 Set-Up 3 m 3 m 3 m Jayant Gupchup

  9. Under The Hood Antenna TelosB Mote Mote Battery CO2 Sensor Power Connector CO2 Sensors Jayant Gupchup

  10. Power Consumption Jayant Gupchup • Lead acid car batteries 12V / 45Ah • Each battery serviced 9 CO2 sensors • Total current draw :1A • Lasted 36 hours after recharge

  11. Power Cycling Motivation Jayant Gupchup • Batteries needed replacement/recharged every other day • Carried every other day for ~ 3 Km • 12V/40Ah car battery weighs 14Kg • Power Cycling! • Warm up time: 15 min

  12. Some Data Power Loss Sensors lack range Jayant Gupchup

  13. Ad Hoc Replacements Jayant Gupchup • At 11 locations, sensors lacked range to sense the phenomenon • Distribution of CO2 hardware • 10000 ppm : 26 • 20000 ppm : 12 • 30000 ppm : 3 • 100000 ppm : 3 • Researchers placed sensors initially • Reconfigured sensors if range was not good enough • Final data calibration requires accurate metadata: • sensor type and date of reconfiguration • Motivates need for self-Identifying sensors (Dallas 1-wire protocol)

  14. High Data Rates Jayant Gupchup • Decisions in field are driven by the data • Researchers used netbook to download and view data • 10 days of 30s sampling: ~ 576000 rows • Spreadsheet and word processing software unable to handle this volume • Researchers stopped looking • Downsample: Provide low-resolution “view” in the field

  15. System Performance Automated parts from existing system worked well. Jayant Gupchup

  16. Conclusions Jayant Gupchup • WSN technology is mature enough to be driven by scientists • Challenges / Lessons Learned • Power cycling for high power sensors • Self-Identifying sensor design • Researchers require low-resolution data in field

  17. Credit Jayant Gupchup NSF- MIRTHE, NSF- IDBR Microsoft Research Betty and Gordon Moore Foundation

  18. Questions Jayant Gupchup

More Related