A WSN approach to unmanned aerial surveillance of traffic anomalies: Some challenges and potential solutions

Stationary CCTV cameras are often used to help monitor car movements and detect any anomalies - e.g., accidents, cars going faster than the allowed speed, driving under the influence of alcohol, etc. The height of the cameras can limit their effectiveness and the types of image processing algorithm which can be used. With advancements in the development of inexpensive aerial flying objects and wireless devices, these two technologies can be coupled to support enhanced surveillance. The flying objects can carry multiple cameras and be sent well above the ground to capture and feed video/image information back to a ground station. In addition, because of the height the objects can achieve, they can capture videos and images which could lend themselves more suitably for the application of a variety of video and image processing algorithms to assist analysts in detecting any anomalies. In this paper, we examine some main challenges of using flying objects for surveillance purposes and propose some potential solutions to these challenges. By doing so, we attempt to provide the basis for developing a framework to build a viable system for improved surveillance based on low-cost equipment. © 2013 IEEE.t.published_or_final_versio

MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a museum

In recent years there has been a growing interest into the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discovering and following the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present MusA (Museum Assistant), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these application

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas

U.S. Unmanned Aerial Vehicles (UAVS) and Network Centric Warfare (NCW) impacts on combat aviation tactics from Gulf War I through 2007 Iraq

Unmanned, aerial vehicles (UAVs) are an increasingly important element of many modern militaries. Their success on battlefields in Afghanistan, Iraq, and around the globe has driven demand for a variety of types of unmanned vehicles. Their proven value consists in low risk and low cost, and their capabilities include persistent surveillance, tactical and combat reconnaissance, resilience, and dynamic re-tasking. This research evaluates past, current, and possible future operating environments for several UAV platforms to survey the changing dynamics of combat-aviation tactics and make recommendations regarding UAV employment scenarios to the Turkish military. While UAVs have already established their importance in military operations, ongoing evaluations of UAV operating environments, capabilities, technologies, concepts, and organizational issues inform the development of future systems. To what extent will UAV capabilities increasingly define tomorrow's missions, requirements, and results in surveillance and combat tactics? Integrating UAVs and concepts of operations (CONOPS) on future battlefields is an emergent science. Managing a transition from manned- to unmanned and remotely piloted aviation platforms involves new technological complexity and new aviation personnel roles, especially for combat pilots. Managing a UAV military transformation involves cultural change, which can be measured in decades.http://archive.org/details/usunmannedaerial109454211Turkish Air Force authors.Approved for public release; distribution is unlimited

Unmanned aerial vehicles (UAVs) for inspection in construction and building industry

Digital data capture is a key component of Industry 4.0 practices. In the past few decades Unmanned Aerial Vehicles (UAVs) have entered the construction industry to capture site data and to cover topographic as well as different types of inspection matters. Photographs, live video, photogrammetric digital elevation models and 3D point clouds can be generated using different photogrammetry facilities, cameras and lasers attached to either a fixed wing or rotorcraft UAVs. UAVs have the ability to deliver information by monitoring, 3Dmaping, measuring, analysing, as well as recording on-site activities. This paper presents the state of art of UAVs usage in construction and building industry and evaluates their applications by experimental case studies. The challenges of using UAVs and their links to BIM will be also discussed. This study found that visual imaging is currently the most popular use of UAVs on construction sites to ensure integrity of structural inspection, however, 3D models derived from LiDAR and photogrammetry techniques are surpassing more traditional methods as they are still significantly cheaper and faster to use. UAVs is also used to monitor workers on site to identify what resources they need in order to carry out their tasks more efficiently and also for the purposes of their health and safety. Despite the approved efficiency of using UAVs on sites to provide better visualization of the working environment, there are still key issues to be tackled such as: the limited flight time of UAVs and its weight. Structural/site investigations have shown that there are some defects on the use of aerial vehicles, with the most important to be the cost along with the precision of the results which may vary depending on the technologies used. There is further study required into the combination of UAVs derived data and its inclusion into BIM, as barriers remain regarding translatable data platforms. There are also some ethical concerns of surveying workers on site and how to protect their privacy

A cost-effectiveness analysis of tactical satellites, high-altitude long-endurance airships, and high and medium altitude unmanned aerial systems for ISR and communication missions

Before 1991, the United States military's demand for additional communications bandwidth and timely intelligence was rising rapidly. Since then, with the advent of the Global War on Terrorism, it has increased substantially. To address this growing need, the Department of Defense has focused its acquisition and procurement efforts on obtaining new communications and intelligence, surveillance, and reconnaissance (ISR) platforms that can help lessen shortfalls and possibly exploit new, untapped resources. Recently, there has been an increasing focus on new technology, such as tactical satellites or high-altitude long-endurance airships, as a way to increase communications and intelligence collection capacities. Likewise, advances in the capabilities of medium-altitude and high-altitude unmanned aerial systems have resulted in a more prominent role for them on today's battlefield. Each of these vehicles has a unique niche in today's military, but the increasing capabilities of each are beginning to create some overlap in their uses. This study will conduct a cost-effectiveness analysis on these systems for use as a persistent communications and ISR platform. In particular, it will measure the effectiveness of each for comparison, and will offer possibilities to increase the overall effective use of the three together to maximize performance and cost.http://archive.org/details/acosteffectivene109453934US Army (USA) author.Approved for public release; distribution is unlimited

Traffic Surveillance and Automated Data Extraction from Aerial Video Using Computer Vision, Artificial Intelligence, and Probabilistic Approaches

In transportation engineering, sufficient, reliable, and diverse traffic data is necessary for effective planning, operations, research, and professional practice. Using aerial imagery to achieve traffic surveillance and collect traffic data is one of the feasible ways that is facilitated by the advances of technologies in many related areas. A great deal of aerial imagery datasets are currently available and more datasets are collected every day for various applications. It will be beneficial to make full and efficient use of the attribute rich imagery as a resource for valid and useful traffic data for many applications in transportation research and practice. In this dissertation, a traffic surveillance system that can collect valid and useful traffic data using quality-limited aerial imagery datasets with diverse characteristics is developed. Two novel approaches, which can achieve robust and accurate performance, are proposed and implemented for this system. The first one is a computer vision-based approach, which uses convolutional neural network (CNN) to detect vehicles in aerial imagery and uses features to track those detections. This approach is capable of detecting and tracking vehicles in the aerial imagery datasets with a very limited quality. Experimental results indicate the performance of this approach is very promising and it can achieve accurate measurements for macroscopic traffic data and is also potential for reliable microscopic traffic data. The second approach is a multiple hypothesis tracking (MHT) approach with innovative kinematics and appearance models (KAM). The implemented MHT module is designed to cooperate with the CNN module in order to extend and improve the vehicle tracking system. Experiments are designed based on a meticulously established synthetic vehicle detection datasets, originally induced scale-agonistic property of MHT, and comprehensively identified metrics for performance evaluation. The experimental results not only indicate that the performance of this approach can be very promising, but also provide solutions for some long-standing problems and reveal the impacts of frame rate, detection noise, and traffic configurations as well as the effects of vehicle appearance information on the performance. The experimental results of both approaches prove the feasibility of traffic surveillance and data collection by detecting and tracking vehicles in aerial video, and indicate the direction of further research as well as solutions to achieve satisfactory performance with existing aerial imagery datasets that have very limited quality and frame rates. This traffic surveillance system has the potential to be transformational in how large area traffic data is collected in the future. Such a system will be capable of achieving wide area traffic surveillance and extracting valid and useful traffic data from wide area aerial video captured with a single platfor