A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> Video-based sensor networks can provide important visual information in a number of applications including: environmental monitoring, health care, emergency response, and video security. This paper describes the Panoptes video-based sensor networking architecture, including its design, implementation, and performance. We describe a video sensor platform that can deliver high-quality video over 802.11 networks with a power requirement of approximately 5 watts. In addition, we describe the streaming and prioritization mechanisms that we have designed to allow it to survive long-periods of disconnected operation. Finally, we describe a sample application and bitmapping algorithm that we have implemented to show the usefulness of our platform. Our experiments include an in-depth analysis of the bottlenecks within the system as well as power measurements for the various components of the system. <s> BIB001 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> 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. <s> BIB002 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> We introduce Meerkats, a wireless network of batteryoperated camera nodes that can be used for monitoring and surveillance of wide areas. One distinguishing feature of Meerkats (when compared, for example, with systems like Cyclops [10]) is that our nodes are equipped with sufficient processing and storage capabilities to be able to run relatively sophisticated vision algorithms (e.g., motion estimation) locally and/or collaboratively. In previous work [9, 8, 7] we analyzed the energy consumption characteristics of the Meerkats nodes under different duty cycles, involving different power states of the system’s components. In this paper we present an analysis of the performance of the surveillance system as a function of the image acquisition rate and of the synchronization between cameras nodes. Our ultimate goal is to optimally balance the trade-off between application-specific performance requirements (e.g., event miss rate) and network lifetime (as a function of the energy consumption characteristics of each node). <s> BIB003 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> Although imaging is an information-rich sensing modality, the use of cameras in sensor networks is very often prohibited by factors such as power, computation cost, storage, communication bandwidth and privacy. In this paper we consider information selective and privacy-preserving address-event imagers for sensor networks. Instead of providing full images with a high degree of redundancy, our efforts in the design of these imagers specialize on selecting a handful of features from a scene and outputting these features in address-event representation. In this paper we present our initial results in modeling and evaluating address-event sensors in the context of sensor networks. Using three different platforms that we have developed, we illustrate how to model address-event cameras and how to build an emulator using these models. We also present a lightweight classification scheme to illustrate the computational advantages of address-event sensors. The paper concludes with an evaluation of the classification algorithm and a feasibility study of using COTS components to emulate address-event inside a sensor network. <s> BIB004 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> With the advent of CMOS cameras, it is now possible to make compact, cheap and low-power image sensors capable of on-board image processing. These embedded vision sensors provide a rich new sensing modality enabling new classes of wireless sensor networking applications. In order to build these applications, system designers need to overcome challenges associated with limited bandwidth, limited power, group coordination and fusing of multiple camera views with various other sensory inputs. Real-time properties must be upheld if multiple vision sensors are to process data, communicate with each other and make a group decision before the measured environmental feature changes. In this paper, we present FireFly Mosaic, a wireless sensor network image processing framework with operating system, networking and image processing primitives that assist in the development of distributed vision-sensing tasks. Each FireFly Mosaic wireless camera consists of a FireFly (Rowe et al., 2006) node coupled with a CMUcam3 (Rowe et al., 2007) embedded vision processor. The FireFly nodes run the nano-RK (Eswaran et al., 2005) real-time operating system and communicate using the RT-link (Rowe et al., 2006) collision-free TDMA link protocol. Using FireFly Mosaic, we demonstrate an assisted living application capable of fusing multiple cameras with overlapping views to discover and monitor daily activities in a home. Using this application, we show how an integrated platform with support for time synchronization, a collision-free TDMA link layer, an underlying RTOS and an interface to an embedded vision sensor provides a stable framework for distributed real-time vision processing. To the best of our knowledge, this is the first wireless sensor networking system to integrate multiple coordinating cameras performing local processing. <s> BIB005 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> In this paper we present CMUcam3, a low-cost, open source, embedded computer vision platform. The CMUcam3 is the third generation of the CMUcam system and is designed to provide a flexible and easy to use open source development environment along with a more powerful hardware platform. The goal of the system is to provide simple vision capabilities to small embedded systems in the form of an intelligent sensor that is supported by an open source community. The hardware platform consists of a color CMOS camera, a frame buffer, a low cost 32bit ARM7TDMI microcontroller, and an MMC memory card slot. The CMUcam3 also includes 4 servo ports, enabling one to create entire, working robots using the CMUcam3 board as the only requisite robot processor. Custom C code can be developed using an optimized GNU toolchain and executables can be flashed onto the board using a serial port without external downloading hardware. The development platform includes a virtual camera target allowing for rapid application development exclusively on a PC. The software environment comes with numerous open source example applications and libraries including JPEG compression, frame differencing, color tracking, convolutions, histogramming, edge detection, servo control, connected component analysis, FAT file system support, and a face detector. <s> BIB006 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> In this paper, we propose and demonstrate a novel wireless camera network system, called CITRIC. The core component of this system is a new hardware platform that integrates a camera, a frequency-scalable (up to 624 MHz) CPU, 16MB FLASH, and 64MB RAM onto a single device. The device then connects with a standard sensor network mote to form a camera mote. The design enables in-network processing of images to reduce communication requirements, which has traditionally been high in existing camera networks with centralized processing. We also propose a back-end client/server architecture to provide a user interface to the system and support further centralized processing for higher-level applications. Our camera mote enables a wider variety of distributed pattern recognition applications than traditional platforms because it provides more computing power and tighter integration of physical components while still consuming relatively little power. Furthermore, the mote easily integrates with existing low-bandwidth sensor networks because it can communicate over the IEEE 802.15.4 protocol with other sensor network platforms. We demonstrate our system on three applications: image compression, target tracking, and camera localization. <s> BIB007 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> We study the problem of constructing a data gathering tree over a wireless sensor network in order to minimize the total energy for compressing and transporting information from a set of source nodes to the sink. This problem is crucial for advanced computationally intensive applications, where traditional "maximum" in-network compression may result in significant computation energy. We investigate a tunable data compression technique that enables effective trade-offs between the computation and communication costs. We derive the optimal compression strategy for a given data gathering tree and then investigate the performance of different tree structures for networks deployed on a grid topology, as well as general graphs. Our analytical results pertaining to the grid topology and simulation results pertaining to the general graphs indicate that the performance of a simple greedy approximation to the Minimal Steiner Tree (MST) provides a constant-factor approximation for the grid topology and good average performance on the general graphs. Although, theoretically, a more complicated randomized algorithm offers a polylogarithmic performance bound, the simple greedy approximation of MST is attractive for practical implementation. <s> BIB008 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> Abstract In this paper we introduced a novel Linear Programming framework to model sensor network lifetime when data reduction through compression is utilized. Comparative analysis of three data compression and forwarding strategies show that neither data compression nor flow balancing can achieve the maximal possible sensor network lifetime when optimized independently. The comparisons reveal that jointly optimizing data compression and load balancing results in up to an order of magnitude longer network lifetimes than non-optimized data compression and load balancing. <s> BIB009 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> In this letter, we present a Linear Programming framework for modeling dynamic data compression and decompression in conjunction with flow balancing in wireless sensor networks. Using the developed framework, we investigated the sensor network lifetimes for different network sizes with various data compression and flow balancing strategies. Our results show that neither compressing all data nor avoiding data compression completely can achieve the longest possible network lifetime. Dynamic data transformation is shown to achieve significantly longer network lifetimes than the lifetimes obtained with the two pure strategies above. <s> BIB010 </s> A survey of visual sensor network platforms <s> Critical evaluation and open problems <s> Wireless sensor networks (WSNs) are attracting great interest in a number of application domains concerned with monitoring and control of physical phenomena, as they enable dense and untethered deployments at low cost and with unprecedented flexibility. However, application development is still one of the main hurdles to a wide adoption of WSN technology. In current real-world WSN deployments, programming is typically carried out very close to the operating system, therefore requiring the programmer to focus on low-level system issues. This not only distracts the programmer from the application logic, but also requires a technical background rarely found among application domain experts. The need for appropriate high-level programming abstractions, capable of simplifying the programming chore without sacrificing efficiency, has long been recognized, and several solutions have hitherto been proposed, which differ along many dimensions. In this article, we survey the state of the art in programming approaches for WSNs. We begin by presenting a taxonomy of WSN applications, to identify the fundamental requirements programming platforms must deal with. Then, we introduce a taxonomy of WSN programming approaches that captures the fundamental differences among existing solutions, and constitutes the core contribution of this article. Our presentation style relies on concrete examples and code snippets taken from programming platforms representative of the taxonomy dimensions being discussed. We use the taxonomy to provide an exhaustive classification of existing approaches. Moreover, we also map existing approaches back to the application requirements, therefore providing not only a complete view of the state of the art, but also useful insights for selecting the programming abstraction most appropriate to the application at hand. <s> BIB011
Direct comparison of the nine VSN platforms presented is not meaningful. Because as it is stated in BIB003 and BIB002 different platforms are designed with functionalities complementing each other. However, we can compare platforms in the same functional class. Energy dissipation of tier3 platforms is roughly at least an order of magnitude higher than the rest of the platforms. Meerkats dissipates approximately 30% less power than Panoptes when both devices are in their highest energy dissipation mode. Meerkats' energy dissipation at the lowest energy dissipation state is approximately 14% less than that of Panoptes in its lowest energy dissipation state. The difference is due to Meerkats' use of more recent components (e.g., Panoptes uses Applied Data Bitsy board and later StrongARM, whereas Meerkats uses XScale). Both Panoptes and Meerkats use Linux OS and they are designed with a device-level integration approach. Among all the tier2 platforms, CITRIC has the highest computational resources and its energy dissipation is also the highest. Since there is no OS running on MeshEye, it requires special effort to reprogram this platform for different applications. MicrelEye is also a platform without an OS governing the operation of the platform. MeshEye and MicrelEye are single board designs, thus, they are designed with a cross-layer methodology. FireFly Mosaic energy dissipation is higher than MicrelEye and lower than CITRIC. FireFly Mosaic's OS (Nano-RK) and link protocol (RT-link) are custom-designed. Both CITRIC and FireFly Mosaic platforms are designed with multiple-board-level integration approach. Vision Mote, CITRIC, MeshEye, and FireFly Mosaic are equipped with 250 Kbps CC2420 or CC2430 radios. Although MicrelEye is equipped with a Bluetooth radio, it is used with 230 Kbps data rate. Cyclops has the lowest energy dissipation characteristics among all the platforms. It also has the lowest data rate radio (CC1000-38.4 Kbps). Yet, it has sufficient amount of computational power for tasks envisioned for tier1. XYZ-ALOHA energy dissipation is more than double the energy dissipation of Cyclops; however, most of the energy dissipation is due to the networking board. AER concept demonstrated on XYZ-ALOHA platform has potential to reduce the energy dissipation below the Cyclops energy dissipation level for tier1 operations if integrated with a more energy efficient networking board. Each VSN platform introduced in Section 4 is designed with a consideration of specific functionalities and application(s) (see Tables 3 and 4 ). Since these platforms are mainly implemented as proof-of-concept and not commercialized, many details that could be useful for application developers such as cost information are not available. While many commercial versions of WSN platforms are available [52] , none of the VSN platforms presented in this paper can be purchased from vendors. If application developers aim to decrease design effort by purchasing off-the-shelf components, they can choose among three alternatives: & Buying a general-purpose sensor platform and attaching imagers to it. This is the most appropriate choice if the focus is more on system aspects but not on hardware design BIB003 . The designers of Panoptes BIB001 and Meerkats BIB003 have preferred this approach. The platforms they use utilize a webcam attached to the Stargate board from Crossbow Technology [10] . & Purchasing a vision sensor platform and integrating it with a networking board. FireFly Mosaic BIB005 team has designed a sensor board named FireFly having a CC2420 radio and integrated it with CMUcam3 BIB006 . CMUcam3 is a vision sensor platform without networking functions available from multiple international commercial vendors for a cost of approximately US$239 BIB006 . & Buying a general-purpose sensor platform and integrating it with a custom-designed image acquisition and processing board (e.g., Cyclops BIB002 uses Mica2 [10] and CITRIC BIB007 uses Tmote Sky [30] ). There are various interesting open problems to be studied ahead. We present some of these in the rest of this section. The main motivation for implementing in-network processing techniques and compression/coding in VSN platforms is that the complexity involved with acquiring raw images and transmitting large volumes of data impose limitations on cost, scalability, network lifetime and robustness of the sensor networks. On the other hand, in the context of VSN applications it would not be correct to assume that computation is always cheaper than communication and thus preferred. Hence, it is important to balance the tradeoff between amount of reduction achieved with computation on VSN platforms and amount of data transmitted to the base station(s) BIB009 BIB008 . In a recent study BIB010 , using a linear programming framework, it was shown that neither compressing all data nor completely avoiding data compression achieve the longest possible network lifetime. Dynamic data transformation is shown to achieve significantly longer network lifetimes than the lifetimes obtained with pure strategies. Modeling communication/computation tradeoffs as optimization problems could provide insights for the energy-optimal operation of VSNs. But these models become more useful if they are fed by elaborate and realistic performance data obtained experimentally for VSN platforms. Therefore we think that more energy-efficient VSNs could be attained by a close cooperation between practitioners and system optimizers. A promising future work on this area could be investigating whether general cost models covering both computation and communication aspects could be developed or these models should be customized for each platform separately. Performance results of video transfer (as opposed to still images) were reported only for FireFly Mosaic and Panoptes. In the experiment of assisted living application with FireFly Mosaic, the nodes run just five days from AA batteries BIB005 . The reported value of the power required for Panoptes BIB001 is even higher; an order of magnitude greater than FireFly Mosaic due to its use of higher-bandwidth and more energy-hungry 802.11 based networking card. These results indicate that extending the lifetime of battery-powered real-time video applications continues to be one of the greatest challenges that lie ahead of VSN researchers. In our view, maintaining privacy may be critical to the success of future VSN applications in real-life settings considering that camera violates privacy more than other sensors BIB004 and privacy-enhancing techniques like video-masking may introduce extra overhead  . An efficient and promising strategy is to take privacy issues into consideration not as an afterthought but from the start. For instance XYZ-ALOHA could satisfy both privacy and efficiency requirements by the use of address-event imagers BIB004 . For ease of deployment and increased flexibility of VSN platforms, programming should be simple enough to be used by application developers who are experts in their domains but not in technology BIB011 . For achieving the ultimate goal of plug-and-play functionality, more effort is definitely required. With the next-generation of programming solutions, we expect to see more VSNs deployed in real-life.