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Networked uavs as aerial sensor network for disaster management applications. Elektrotechnik und Informationstechnik (E&I
"... Advances in control engineering and material science made it possible to develop small-scale unmanned aerial vehicles (UAVs) equipped with cameras and sensors. These UAVs enable us to obtain a bird’s eye view of the environment. Having access to an aerial view over large areas is helpful in disaster ..."
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Advances in control engineering and material science made it possible to develop small-scale unmanned aerial vehicles (UAVs) equipped with cameras and sensors. These UAVs enable us to obtain a bird’s eye view of the environment. Having access to an aerial view over large areas is helpful in disaster situations, where often only incomplete and inconsistent information is available to the rescue team. In such situations, airborne cameras and sensors are valuable sources of information helping us to build an ‘‘overview’ ’ of the environment and to assess the current situation. This paper reports on our ongoing research on deploying small-scale, battery-powered and wirelessly connected UAVs carrying cameras for disaster management applications. In this ‘‘aerial sensor network’ ’ several UAVs fly in formations and cooperate to achieve a certain mission. The ultimate goal is to have an aerial imaging system in which UAVs build a flight formation, fly over a disaster area such as wood fire or a large traffic accident, and deliver high-quality sensor data such as images or videos. These images and videos are communicated to the ground, fused, analyzed in real-time, and finally delivered to the user. In this paper we introduce our aerial sensor network and its application in disaster situations. We discuss challenges of such aerial sensor networks and focus on the optimal placement of sensors. We formulate the coverage problem as integer linear program (ILP) and present first evaluation results.
Pervasive Smart Camera Networks exploiting heterogeneous wireless Channels
- in Proc. of the IEEE International Conference on Pervasive Computing and Communications (PerCom
, 2009
"... Abstract—Smart cameras are embedded systems that perform on-board video content analysis and only report detected events instead of permanently streaming videos. Visual sensor networks aim at integrating smart cameras with wireless sensor networks. Camera sensors have higher requirements regarding c ..."
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Cited by 9 (7 self)
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Abstract—Smart cameras are embedded systems that perform on-board video content analysis and only report detected events instead of permanently streaming videos. Visual sensor networks aim at integrating smart cameras with wireless sensor networks. Camera sensors have higher requirements regarding computing power and communication bandwidth than those typically used in wireless sensor network applications. Consequently, power management is an even more critical issue. This work in progress presents an attempt to address this by combining high and low power radios as well as high and low performance computing systems in one single platform. This allows to control power consumption by selectively enabling only required components. I.
A pervasive smart camera network architecture applied for multi-camera object classification
- in Distributed Smart Cameras, 2009. ICDSC 2009. Third ACM/IEEE International Conference on, 30 2009-sept
"... Abstract—Visual sensor networks are an emerging research area with the goal of using cameras as pervasive and affordable sensing and processing devices. This paper presents a pervasive smart camera platform which is built from off-the-shelf hardware and software components. The hardware platform is ..."
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Abstract—Visual sensor networks are an emerging research area with the goal of using cameras as pervasive and affordable sensing and processing devices. This paper presents a pervasive smart camera platform which is built from off-the-shelf hardware and software components. The hardware platform is comprised of an OMAP 3530 processor, 128 MB RAM and various interfaces for connecting sensors and peripherals. A dual-radio wireless network allows to trade communication performance for power consumption. The software architecture is built upon standard Linux and supports dataflow oriented application development by dynamically instantiating and connecting functions blocks. Data is transferred between blocks via shared memory for high throughput. We present a performance evaluation of our smart camera platform as well as a multi-camera object classification system to demonstrate the capabilities and applicability of our approach. I.
Applications of Trusted Computing in Pervasive Smart Camera Networks
- in Proceedings of the Workshop on Embedded System Security (WESS
, 2009
"... Pervasive Smart Cameras are embedded computer vision systems bringing together the research areas of smart cam-eras and wireless sensor networks. Besides traditional areas like video surveillance or traffic monitoring, small, cheap and powerful camera systems open a wide range of potential new appli ..."
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Cited by 4 (3 self)
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Pervasive Smart Cameras are embedded computer vision systems bringing together the research areas of smart cam-eras and wireless sensor networks. Besides traditional areas like video surveillance or traffic monitoring, small, cheap and powerful camera systems open a wide range of potential new applications including assisted living, home automation or entertainment. At the same time, widespread deployment of cameras introduces several security challenges. Using wireless networking and being mounted at remote locations, smart cameras are an attractive target for attackers. An-other issue of crucial importance when it comes to the ac-ceptance of camera systems is user privacy. In this work we explore the use of Trusted Computing concepts to enhance security of an experimental smart camera system. Addition-ally, we discuss required and achievable performance based on evaluations on our prototype platform. 1.
1 Video Analysis in PTZ Camera Networks From master-slave to cooperative smart cameras
"... Abstract—Pan-Tilt-Zoom (PTZ) cameras are able to dynamically modify their field of view. This functionality introduces new capabilities to camera networks such as increasing the resolution of moving targets and adapting the sensor coverage. On the other hand, PTZ functionality requires solutions to ..."
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Abstract—Pan-Tilt-Zoom (PTZ) cameras are able to dynamically modify their field of view. This functionality introduces new capabilities to camera networks such as increasing the resolution of moving targets and adapting the sensor coverage. On the other hand, PTZ functionality requires solutions to new challenges such as controlling the PTZ parameters, estimating the ego-motion of the cameras and calibrating the moving cameras. This tutorial provides an overview of the main video processing techniques and the currents trends in this active field of research. Autonomous PTZ cameras mainly aim to detect and track targets with the largest possible resolution. Autonomous PTZ operation is activated once the network detects and identifies an object as sensible target and requires accurate control of the PTZ parameters and coordination among the cameras in the network. We, therefore, present cooperative localisation and tracking methods, i.e., multi-agent and consensus-based approaches to jointly compute the target’s properties such as ground-plane position and velocity. Stereo vision exploiting wide baselines can be used to derive 3D target localisation. This tutorial further presents different techniques for controlling PTZ camera hand-off, configuring the network to dynamically track targets and optimizing the network configuration to increase coverage probability. It also discusses implementation aspects for these video processing techniques on embedded smart cameras—with a special focus on data access properties. I.
A Low-Bandwidth Camera Sensor Platform with Applications in Smart Camera Networks
"... Smart camera networks have recently emerged as a new class of sensor network infrastructure that is capable of supporting high-power in-network signal processing and enabling a wide range of applications. In this article, we provide an exposition of our efforts to build a low-bandwidth wireless came ..."
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Smart camera networks have recently emerged as a new class of sensor network infrastructure that is capable of supporting high-power in-network signal processing and enabling a wide range of applications. In this article, we provide an exposition of our efforts to build a low-bandwidth wireless camera network platform, called CITRIC, and its applications in smart camera networks. The platform integrates a camera, a microphone, a frequency-scalable (up to 624 MHz) CPU, 16 MB FLASH, and 64 MB RAM onto a single device. The device then connects with a standard sensor network mote to form a wireless camera mote. With reasonably low power consumption and extensive algorithmic libraries running on a decent operating system that is easy to program, CITRIC is ideal for research and applications in distributed image and video processing. Its capabilities of in-network image processing also reduce communication requirements, which has been high in other existing camera networks with centralized processing. Furthermore, the mote easily integrates with other low-bandwidth sensor networks via the IEEE 802.15.4 protocol. To justify the utility of CITRIC, we present several representative applications. In particular, concrete research results will be demonstrated in two areas, namely, distributed coverage hole identification and distributed object
Decentralised Control of Wireless Sensor Networks
, 2009
"... Wireless sensor networks are receiving a considerable degree of research interest due to their deployment in an increasing number and variety of applications. However, the efficient management of the limited energy resources of such networks in a way that maximises the information value of the data ..."
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Wireless sensor networks are receiving a considerable degree of research interest due to their deployment in an increasing number and variety of applications. However, the efficient management of the limited energy resources of such networks in a way that maximises the information value of the data collected is a significant research challenge. To date, most of these systems have adopted a centralised control mechanism, but from a system’s perspective this raises concerns associated with scalability, robustness, and the ability to cope with dynamism. Given this, decentralised approaches are appealing. But, the design of efficient decentralised regimes is challenging as it introduces an additional control issue related to the dynamic interactions between the network’s interconnected nodes in the absence of a central coordinator. Within this context, this thesis first concentrates on decentralised approaches to adaptive sampling as a means of focusing a node’s energy consumption on obtaining the most important data. Specifically, we develop a principled information metric based upon Fisher information and Gaussian process regression that allows the information content of a node’s observations to be expressed. We then use this metric to derive
Distributed Adaptive Sampling, Forwarding, and Routing Algorithms for Wireless Visual Sensor Networks
"... The efficient management of the limited energy resources of a wire-less visual sensor network is central to its successful operation. Within this context, this paper focuses on the adaptive sampling, forwarding, and routing actions of each node in order to maximise the information value of the data ..."
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The efficient management of the limited energy resources of a wire-less visual sensor network is central to its successful operation. Within this context, this paper focuses on the adaptive sampling, forwarding, and routing actions of each node in order to maximise the information value of the data collected. These actions are inter-related in this setting because each node’s energy consumption must be optimally allocated between sampling and transmitting its own data, receiving and forwarding the data of other nodes, and routing any data. Thus, we develop two optimal decentralised algorithms to solve this distributed constraint optimization problem. The first as-sumes that the route by which data is forwarded to the base station is fixed, and then calculates the optimal sampling, transmitting, and forwarding actions that each node should perform. The second as-sumes flexible routing, and makes optimal decisions regarding both
Analysis of Vision systems and Taxonomy Formulation
"... This report is part of the research work which is conducted in order to develop a benchmark or an abstract model for the vision systems. This work leads to system taxonomy for vision systems which can be used as a reference model for classification and comparison of vision systems. Moreover, it will ..."
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This report is part of the research work which is conducted in order to develop a benchmark or an abstract model for the vision systems. This work leads to system taxonomy for vision systems which can be used as a reference model for classification and comparison of vision systems. Moreover, it will facilitate in development of generic solutions in vision systems.
doi:10.1155/2011/530354 Research Article Securing Embedded Smart Cameras with Trusted Computing
, 2010
"... License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Camera systems are used in many applications including video surveillance for crime prevention and investigation, trac monitoring on highways or building monitoring an ..."
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License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Camera systems are used in many applications including video surveillance for crime prevention and investigation, trac monitoring on highways or building monitoring and automation. With the shift from analog towards digital systems, the capabilities of cameras are constantly increasing. Today’s smart camera systems come with considerable computing power, large memory, and wired or wireless communication interfaces. With onboard image processing and analysis capabilities, cameras not only open new possibilities but also raise new challenges. Often overlooked are potential security issues of the camera system. The increasing amount of software running on the cameras turns them into attractive targets for attackers. Therefore, the protection of camera devices and delivered data is of critical importance. In this work we present an embedded camera prototype that uses Trusted Computing to provide security guarantees for streamed videos. With a hardware-based security solution, we ensure integrity, authenticity, and confidentiality of videos. Furthermore, we incorporate image timestamping, detection of platform reboots, and reporting of the system status. This work is not limited to theoretical considerations but also describes the implementation of a prototype system. Extensive evaluation results illustrate the practical feasibility of the approach. 1.
