Paper
5 October 2006 Autonomous vision networking: miniature wireless sensor networks with imaging technology
Gioia Messinger, Giora Goldberg
Author Affiliations +
Proceedings Volume 6394, Unmanned/Unattended Sensors and Sensor Networks III; 63940W (2006) https://doi.org/10.1117/12.706143
Event: Optics/Photonics in Security and Defence, 2006, Stockholm, Sweden
Abstract
The recent emergence of integrated PicoRadio technology, the rise of low power, low cost, System-On-Chip (SOC) CMOS imagers, coupled with the fast evolution of networking protocols and digital signal processing (DSP), created a unique opportunity to achieve the goal of deploying large-scale, low cost, intelligent, ultra-low power distributed wireless sensor networks for the visualization of the environment. Of all sensors, vision is the most desired, but its applications in distributed sensor networks have been elusive so far. Not any more. The practicality and viability of ultra-low power vision networking has been proven and its applications are countless, from security, and chemical analysis to industrial monitoring, asset tracking and visual recognition, vision networking represents a truly disruptive technology applicable to many industries. The presentation discusses some of the critical components and technologies necessary to make these networks and products affordable and ubiquitous - specifically PicoRadios, CMOS imagers, imaging DSP, networking and overall wireless sensor network (WSN) system concepts. The paradigm shift, from large, centralized and expensive sensor platforms, to small, low cost, distributed, sensor networks, is possible due to the emergence and convergence of a few innovative technologies. Avaak has developed a vision network that is aided by other sensors such as motion, acoustic and magnetic, and plans to deploy it for use in military and commercial applications. In comparison to other sensors, imagers produce large data files that require pre-processing and a certain level of compression before these are transmitted to a network server, in order to minimize the load on the network. Some of the most innovative chemical detectors currently in development are based on sensors that change color or pattern in the presence of the desired analytes. These changes are easily recorded and analyzed by a CMOS imager and an on-board DSP processor. Image processing at the sensor node level may also be required for applications in security, asset management and process control. Due to the data bandwidth requirements posed on the network by video sensors, new networking protocols or video extensions to existing standards (e.g. Zigbee) are required. To this end, Avaak has designed and implemented an ultra-low power networking protocol designed to carry large volumes of data through the network. The low power wireless sensor nodes that will be discussed include a chemical sensor integrated with a CMOS digital camera, a controller, a DSP processor and a radio communication transceiver, which enables relaying of an alarm or image message, to a central station. In addition to the communications, identification is very desirable; hence location awareness will be later incorporated to the system in the form of Time-Of-Arrival triangulation, via wide band signaling. While the wireless imaging kernel already exists specific applications for surveillance and chemical detection are under development by Avaak, as part of a co-founded program from ONR and DARPA. Avaak is also designing vision networks for commercial applications - some of which are undergoing initial field tests.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gioia Messinger and Giora Goldberg "Autonomous vision networking: miniature wireless sensor networks with imaging technology", Proc. SPIE 6394, Unmanned/Unattended Sensors and Sensor Networks III, 63940W (5 October 2006); https://doi.org/10.1117/12.706143
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Sensor networks

Imaging systems

Image processing

Digital signal processing

Video

Video surveillance

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