Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network
This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sens...
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MDPI AG
2014-08-01
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Online Access: | http://www.mdpi.com/1424-8220/14/9/15981 |
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doaj-a42423c270a04b32910c625879dd84812020-11-25T01:41:59ZengMDPI AGSensors1424-82202014-08-01149159811600210.3390/s140915981s140915981Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor NetworkJeongyeup Paek0John Hicks1Sharon Coe2Ramesh Govindan3Department of Computer Information Communication Engineering, Hongik University, Sejong 339-701, KoreaComputer Science Department, University of California, Los Angeles, CA 90095, USABiology Department, University of California, Riverside, CA 92521, USADepartment of Computer Science, University of Southern California, Los Angeles, CA 90089, USAThis article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet’s built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Jacinto Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions.http://www.mdpi.com/1424-8220/14/9/15981wireless sensor networksimage sensorssensor applicationstenet, rcrt,cyclops, environmental monitoring |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jeongyeup Paek John Hicks Sharon Coe Ramesh Govindan |
spellingShingle |
Jeongyeup Paek John Hicks Sharon Coe Ramesh Govindan Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network Sensors wireless sensor networks image sensors sensor applications tenet, rcrt,cyclops, environmental monitoring |
author_facet |
Jeongyeup Paek John Hicks Sharon Coe Ramesh Govindan |
author_sort |
Jeongyeup Paek |
title |
Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network |
title_short |
Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network |
title_full |
Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network |
title_fullStr |
Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network |
title_full_unstemmed |
Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network |
title_sort |
image-based environmental monitoring sensor application using an embedded wireless sensor network |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2014-08-01 |
description |
This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet’s built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Jacinto Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions. |
topic |
wireless sensor networks image sensors sensor applications tenet, rcrt,cyclops, environmental monitoring |
url |
http://www.mdpi.com/1424-8220/14/9/15981 |
work_keys_str_mv |
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