2007
DOI: 10.1117/12.706147
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SenseTK: a multimodal, multimedia sensor networking toolkit

Abstract: This paper describes the design and implementation of a multi-modal, multimedia capable sensor networking framework called SenseTK. SenseTK allows application writers to easily construct multi-modal, multimedia sensor networks that include both traditional scalar-based sensors as well as sensors capable of recording sound and video. The distinguishing features of such systems include the need to push application processing deep within the sensor network, the need to bridge extremely low power and low computati… Show more

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Cited by 4 publications
(1 citation statement)
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“…To conduct an insightful survey that uncovers the underlying structural shortcomings we relaxed our requirements. We organized the platforms that satisfy our relaxed selection criteria into architectural classes: General Purpose Architectures: MeshEye [12] and WiSN Mote [7], Panoptes [13], XYZ [14], and NIT-Hohai Node [15]; Heavily Coupled Architectures: eCAM and WiSNAP [16], Cyclops [17], Smart Camera Mote [18], and CMUcam3 [19], and Externally Dependent Architectures: DSPCam [20], Stargate [21], Imote2/Stargate 2 [2], [22], CITRIC [23], Scatter-Web [24], FleckTM-3 [25] and Fox node [26].…”
Section: Selection and Organization Of Wireless Video Sensor Node Plamentioning
confidence: 99%
“…To conduct an insightful survey that uncovers the underlying structural shortcomings we relaxed our requirements. We organized the platforms that satisfy our relaxed selection criteria into architectural classes: General Purpose Architectures: MeshEye [12] and WiSN Mote [7], Panoptes [13], XYZ [14], and NIT-Hohai Node [15]; Heavily Coupled Architectures: eCAM and WiSNAP [16], Cyclops [17], Smart Camera Mote [18], and CMUcam3 [19], and Externally Dependent Architectures: DSPCam [20], Stargate [21], Imote2/Stargate 2 [2], [22], CITRIC [23], Scatter-Web [24], FleckTM-3 [25] and Fox node [26].…”
Section: Selection and Organization Of Wireless Video Sensor Node Plamentioning
confidence: 99%