https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/WSNSurvey2.pdf

Wireless sensor network survey

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.

/pdf/energy-conservation-in-wireless-sensor-networks-a-survey-1bl7d2obnm.pdf

Energy conservation in wireless sensor networks: A survey

https://www.cs.montana.edu/courses/csci566/Ref/WMSN-Survey.pdf

A survey on wireless multimedia sensor networks

In recent years, the growing interest in the wireless sensor network (WSN) has resulted in thousands of peer-reviewed publications. Most of this research is concerned with scalar sensor networks that measure physical phenomena, such as temperature, pressure, humidity, or location of objects that can be conveyed through low-bandwidth and delay-tolerant data streams. Recently, the focus is shifting toward research aimed at revisiting the sensor network paradigm to enable delivery of multimedia content, such as audio and video streams and still images, as well as scalar data. This effort will result in distributed, networked systems, referred to in this paper as wireless multimedia sensor networks (WMSNs). This article discusses the state of the art and the major research challenges in architectures, algorithms, and protocols for wireless multimedia sensor networks. Existing solutions at the physical, link, network, transport, and application layers of the communication protocol stack are investigated. Finally, fundamental open research issues are discussed, and future research trends in this area are outlined.

Wireless multimedia sensor networks: A survey

Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena. To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.

Cyclops: In Situ Image Sensing and Interpretation in Wireless Sensor Networks

Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena.To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.

http://www.kilopixel.net/publications/sensys2005.pdf

Cyclops: in situ image sensing and interpretation in wireless sensor networks

Recent technological advances in low power CMOS imaging has lead to a new class of imaging devices such as Cyclops. Cyclops is a low power and complexity imaging sensor that mates with conventional sensor network nodes such as Motes.In this demo we present deep vision. An attribute based system that enables orchestrating visual observation through an attribute based system. In our work, visual computations reside on Cyclops sensors and can be addressed as attributes through declarative queries. We present our network architecture and showcase the potential applications and opportunities as well as outstanding challenges. We call our approach deep vision due to the integration of vision with the finest granularity of the sensor network.

Juan Garcia

Papers

Cyclops: In Situ Image Sensing and Interpretation in Wireless Sensor Networks

Cyclops: in situ image sensing and interpretation in wireless sensor networks

Deep Vision: Experiments in Exploiting Vision in Wireless Sensor Networks