Philip Kuryloski, Annarita Giani, Roberta Giannantonio, Katherine S. Gilani, Ville-Pekka Seppa , Edmund Seto , Raffaele Gravina , Victor Shia, Curtis Wang, Posu Yan, Allen Yang, Jari Hyttinen, Shankar Sastry, Stephen Wicker, Ruzena Bajcsy
Citation
Philip Kuryloski, Annarita Giani, Roberta Giannantonio, Katherine S. Gilani, Ville-Pekka Seppa , Edmund Seto , Raffaele Gravina , Victor Shia, Curtis Wang, Posu Yan, Allen Yang, Jari Hyttinen, Shankar Sastry, Stephen Wicker, Ruzena Bajcsy. "DexterNet: An Open Platform for Heterogeneous Body Sensor Networks and Its Applications". Talk or presentation, 11, November, 2008.
Abstract
We design and implement a novel platform, called DexterNet, for heterogeneous body sensor networks. The system is motivated by shifting research paradigms in body sensor networks to support real-time, persistent human monitoring in both indoor and outdoor environments. The platform adopts a three-layer, hierarchical architecture to control heterogeneous body sensors. The first layer, called the body sensor layer (BSL), deals with design of different wireless body sensors and their instrumentation on the body. We detail two custom-built body sensors, one measuring body motions and the other measuring the ECG and respiratory patterns. At the second layer, called the personal network layer (PNL), the wireless body sensors on a single subject communicate with a mobile computer station. The mobile station can be either a computer or a smart phone that supports Linux OS and the IEEE 802.15.4 protocol. It issues control commands to the body sensors and receives and processes sensor data measured from the body sensors. These functions are abstracted and implemented as an open-source software library, called Signal Processing In Node Environment (SPINE). A DexterNet network is scalable, and can be reconfigured on-the-fly via SPINE. At the third layer, called the global network layer (GNL), multiple PNLs communicate with a remote Internet server to permanently log the sensor data and support higher-level applications in both indoor and outdoor environments. We demonstrate the versatility of the DexterNet platform via three applications: avatar visualization, human activity recognition, and integration of DexterNet with global positioning sensors and air pollution sensors for asthma studies.
Electronic downloads
- 8%20-%20Kuryloski-Gilani-Yan.ppt · application/vnd.ms-powerpoint · 1709 kbytes
| Citation formats |
- HTML
Philip Kuryloski, Annarita Giani, Roberta Giannantonio, Katherine S. Gilani, Ville-Pekka Seppa , Edmund Seto , Raffaele Gravina , Victor Shia, Curtis Wang, Posu Yan, Allen Yang, Jari Hyttinen, Shankar Sastry, Stephen Wicker, Ruzena Bajcsy. <a href="http://www.truststc.org/pubs/479.html" ><i>DexterNet: An Open Platform for Heterogeneous Body Sensor Networks and Its Applications</i></a>, Talk or presentation, 11, November, 2008.
- Plain text
Philip Kuryloski, Annarita Giani, Roberta Giannantonio, Katherine S. Gilani, Ville-Pekka Seppa , Edmund Seto , Raffaele Gravina , Victor Shia, Curtis Wang, Posu Yan, Allen Yang, Jari Hyttinen, Shankar Sastry, Stephen Wicker, Ruzena Bajcsy. "DexterNet: An Open Platform for Heterogeneous Body Sensor Networks and Its Applications". Talk or presentation, 11, November, 2008.
- BibTeX
@presentation{KuryloskiGianiGiannantonioGilaniSeppaSetoGravina08_DexterNetOpenPlatformForHeterogeneousBodySensorNetworks, author = {Philip Kuryloski and Annarita Giani and Roberta Giannantonio and Katherine S. Gilani and Ville-Pekka Seppa and Edmund Seto and Raffaele Gravina and Victor Shia and Curtis Wang and Posu Yan and Allen Yang and Jari Hyttinen and Shankar Sastry and Stephen Wicker and Ruzena Bajcsy}, title = {DexterNet: An Open Platform for Heterogeneous Body Sensor Networks and Its Applications}, day = {11}, month = {November}, year = {2008}, abstract = {We design and implement a novel platform, called DexterNet, for heterogeneous body sensor networks. The system is motivated by shifting research paradigms in body sensor networks to support real-time, persistent human monitoring in both indoor and outdoor environments. The platform adopts a three-layer, hierarchical architecture to control heterogeneous body sensors. The first layer, called the body sensor layer (BSL), deals with design of different wireless body sensors and their instrumentation on the body. We detail two custom-built body sensors, one measuring body motions and the other measuring the ECG and respiratory patterns. At the second layer, called the personal network layer (PNL), the wireless body sensors on a single subject communicate with a mobile computer station. The mobile station can be either a computer or a smart phone that supports Linux OS and the IEEE 802.15.4 protocol. It issues control commands to the body sensors and receives and processes sensor data measured from the body sensors. These functions are abstracted and implemented as an open-source software library, called Signal Processing In Node Environment (SPINE). A DexterNet network is scalable, and can be reconfigured on-the-fly via SPINE. At the third layer, called the global network layer (GNL), multiple PNLs communicate with a remote Internet server to permanently log the sensor data and support higher-level applications in both indoor and outdoor environments. We demonstrate the versatility of the DexterNet platform via three applications: avatar visualization, human activity recognition, and integration of DexterNet with global positioning sensors and air pollution sensors for asthma studies. }, URL = {http://www.truststc.org/pubs/479.html} }
Posted by Jessica Gamble on 23 Jan 2009.
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