Daniel G. Costa

The Coverage Problem in Video-Based Wireless Sensor Networks: A Survey

Wireless sensor networks typically consist of a great number of tiny low-cost electronic devices with limited sensing and computing capabilities which cooperatively communicate to collect some kind of information from an area of interest. When wireless nodes of such networks are equipped with a low-power camera, visual data can be retrieved, facilitating a new set of novel applications. The nature of video-based wireless sensor networks demands new algorithms and solutions, since traditional wireless sensor networks approaches are not feasible or even efficient for that specialized communication scenario. The coverage problem is a crucial issue of wireless sensor networks, requiring specific solutions when video-based sensors are employed. In this paper, it is surveyed the state of the art of this particular issue, regarding strategies, algorithms and general computational solutions. Open research areas are also discussed, envisaging promising investigation considering coverage in video-based wireless sensor networks.

A survey on multimedia-based cross-layer optimization in visual sensor networks.

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks.

Exploiting the sensing relevancies of source nodes for optimizations in visual sensor networks

Wireless ad-hoc networks composed of resource-constrained camera-enabled sensors can provide visual information for a series of monitoring applications, enriching the understanding of the physical world. In many cases, source nodes may have different sensing relevancies for the monitoring functions of the applications, according to the importance of the visual information retrieved from the monitored field. As a direct result, high quality is only required for the most relevant information and, as it is expected that many visual monitoring applications can tolerate some quality loss in the data received from the least relevant source nodes, the network operation can be optimized exploiting this innovative concept. As a novel global QoS parameter, we envisage that the sensing relevancies of source nodes can be considered for a series of optimizations in different aspects of the wireless sensor network operation, achieving energy saving or assuring high quality transmission for the most relevant data. In this paper we discuss some approaches for the establishment of the sensing relevancies of the nodes and propose a protocol to support them. Moreover, we present two practical examples of optimizations based on the sensing relevancies of source nodes that transmit still images of the monitored field, addressing issues as energy-efficient data transmission and packet prioritization in intermediate nodes.

Adaptive Monitoring Relevance in Camera Networks for Critical Surveillance Applications

Camera networks have been considered for a large set of visual monitoring applications. For some of them, cameras may be continuously monitoring scenes or groups of targets, but some events may trigger a critical level of visual monitoring, as in public security, industrial automation, and response to natural disasters. In such way, some critical events as a bomb explosion, a volcanic eruption, forest wildfire, or a car accident must be captured with high relevance, potentially helping when identifying responsibilities and during rescue operations. New relevance levels, which can be reflected in higher quality of transmitted images or video streams or even higher priority during transmission over the network must be quickly assigned to cameras that can view the critical events. In this work we propose a methodology to dynamically assign relevancies to cameras that view the area of critical events, employing scalar sensors and a decentralized decision mechanism. The resulting multimodal camera network can considerably enhance the critical surveillance in different monitoring applications. We propose some optimizations that exploit the monitoring relevance in such scenarios.

A Survey of Image Security in Wireless Sensor Networks

Wireless sensor networks are increasingly gaining attention. In recent years, a great deal of monitoring, control and tracking applications have been designed for different scenarios. For such networks, camera-enabled sensors can retrieve visual data from a monitored field, providing valuable information for many applications. In general, those networks have resource constraints of processing, memory, energy and transmission bandwidth, imposing many design challenges. Nevertheless, a group of applications may also have security requirements, which bring additional complexity to be handled. Most traditional security mechanisms for popular networks, like the Internet, are not suitable for wireless sensor networks, demanding proper investigation in this area. In this paper, we survey recent developments in encryption and privacy in wireless sensor networks deployed for transmissions of image snapshots, reviewing innovative approaches to provide different levels of security. Promising research directions are also discussed.

Effect of frame size on energy consumption in wireless image sensor networks

Wireless sensor networks composed of camera-enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. While few bytes can represent scalar data, even low-resolution still images may require thousand of bytes, turning data fragmentation into a relevant design issue. Different optimization approaches have been proposed in recent years to achieve energy saving in wireless image sensor networks. However, the impact of image fragmentation upon the adopted MAC technology has been neglected in most cases. In this work we investigate the effect of frame size on image transmissions over wireless sensor networks, linking the maximum frame size, the useful payload and the frame error rate effects. Additionally, we discuss different approaches for transmissions of DWT-based encoded images and the impact of inserting application-specific information into the frame header. We believe that our discussions can contribute to the advance of the design of wireless image sensor networks.

Research trends in wireless visual sensor networks when exploiting prioritization.

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, where many critical topics, such as communication efficiency and energy consumption, have been investigated in the past few years. However, when sensors are endowed with low-power cameras for visual monitoring, a new scope of challenges is raised, demanding new research efforts. In this context, the resource-constrained nature of sensor nodes has demanded the use of prioritization approaches as a practical mechanism to lower the transmission burden of visual data over wireless sensor networks. Many works in recent years have considered local-level prioritization parameters to enhance the overall performance of those networks, but global-level policies can potentially achieve better results in terms of visual monitoring efficiency. In this paper, we make a broad review of some recent works on priority-based optimizations in wireless visual sensor networks. Moreover, we envisage some research trends when exploiting prioritization, potentially fostering the development of promising optimizations for wireless sensor networks composed of visual sensors.

Selecting redundant nodes when addressing availability in wireless visual sensor networks

As Wireless Sensor Networks have been employed to support critical monitoring applications, network availability has become a major design concern. In these networks, redundancy can be exploited to enhance the attainable availability level, where redundant sensors can replace faulty nodes. When camera-enabled sensors are deployed to retrieve visual information, the perception of redundancy changes considerably, since the redundancy of visual sensors depends on the monitoring requirements of the applications. In such context, characteristics as deployment density, viewing angle and sensing range are relevant when planning wireless sensor network applications, directly impacting in the number of redundant nodes. We propose an algorithm to select redundant nodes in Wireless Visual Sensor Networks, according to the application requirements. Moreover, we discuss how parameters of the deployed network can influence on the number of redundant nodes.

A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications

The advance of technologies in several areas has allowed the development of smart city applications, which can improve the way of life in modern cities. When employing visual sensors in that scenario, still images and video streams may be retrieved from monitored areas, potentially providing valuable data for many applications. Actually, visual sensor networks may need to be highly dynamic, reflecting the changing of parameters in smart cities. In this context, characteristics of visual sensors and conditions of the monitored environment, as well as the status of other concurrent monitoring systems, may affect how visual sensors collect, encode and transmit information. This paper proposes a fuzzy-based approach to dynamically configure the way visual sensors will operate concerning sensing, coding and transmission patterns, exploiting different types of reference parameters. This innovative approach can be considered as the basis for multi-systems smart city applications based on visual monitoring, potentially bringing significant results for this research field.

Wireless visual sensor networks for smart city applications

Nowadays, the major cities of the world have to solve problems that were unthinkable in past decades. Due to the population growing rate, new issues are still arising, but technology can be used to address such issues and improve life quality in big cities. In that scenario, surveillance is a highly desired service and most governments are already using different types of devices to provide high levels of security. Wireless Visual Sensor Networks (WVSN) can be used to monitor every part of a city without the cost of running cables all over it. However, there must be an efficient way to gather all information collected by the sensors and cameras, with reduced energy consumption and average latency. This work proposes a new algorithm to position multiple mobile sinks in WVSN deployed along roads and streets. A relevance-based approach was designed to position sinks closer to source nodes with higher sensing relevance, since they are expected to transmit more data packets. The proposed algorithm can detect forbidden and disconnected zones, making sure sinks will be positioned in permitted areas, which makes this approach very suitable for realistic smart city applications. A mobile sinks positioning approach for smart cities is proposed.Movement constraints in urban areas are considered for sinks positioning.More relevant nodes in the network are prioritized by the sinks.Energy consumption is reduced compared to static sinks.Packets latency is reduced for more relevant nodes.