Panoptes: scalable low-power video sensor networking technologies
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Cyclops: in situ image sensing and interpretation in wireless sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
A survey on wireless multimedia sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Proceedings of the 6th international conference on Information processing in sensor networks
FireFly Mosaic: A Vision-Enabled Wireless Sensor Networking System
RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
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Dealing with visual data is the key for environmental monitoring tasks in Wireless Multimedia Sensor Networks (WMSNs). Tasks such as object detection, recognition, and/or tracking do require extracting and using the right information from the inherently large amount of visual data. The widely accepted solution of legacy WSNs, transmitting the acquired data to a central base station for further processing, would render a WMSN totally useless because of the unacceptable use of bandwidth and energy. Therefore, we consider the in situ processing as a viable solution for WMSNs. However, processing power and memory capacity restrictions of existing multimedia sensor nodes along with their power consumption are the limiting factors for wide-spread use of in situ processing. Nevertheless, recent technological improvements and introduction of the new ARM cores encourage us to evaluate the image processing capabilities of ARM7/ARM9/ARM11 based micro-controllers for in situ processing in WMSNs. In this work, we first discussed the architectural design differences among the various ARM cores. Then we classified image processing algorithms into three categories. Then, we evaluated the performance of each microcontroller by running a set of basic image processing algorithms necessary for object detection, recognition, and/or tracking. The test results show that ARM11 runs up to 6---30 times faster than ARM9 and ARM7, respectively. Besides, ARM11 consumes up to 5---7 times less energy than ARM9 and ARM7 for the same type of operations.