Collaborative signal and information processing for target detection with heterogeneous sensor networks

In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce high performance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behaviour and capacity, target behaviour and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield

Indoor And Outdoor Real Time Information Collection in Disaster Scenario

A disaster usually severely harms human health and property. After a disaster, great amount of information of a disaster area is needed urgently. The information not only indicates the severity of the disaster, but also is crucial for an efficient search and rescue process. In order to quickly and accurately collect real time information in a disaster scenario, a mobile platform is developed for an outdoor scenario and a localization and navigation system for responders is introduced for an indoor scenario. The mobile platform has been integrated to the DIORAMA system. It is built with a 6-wheel robot chassis along with an Arduino microcontroller. Controlled by a mounted Android smartphone, the mobile platform can receive commands from incident commanders and quickly respond to the commands. While patrolling in a disaster area, a constant RFID signal is collected to improve the localization accuracy of victims. Pictures and videos are also captured in order to enhance the situational awareness of rescuers. The design of the indoor information collection is focused on the responder side. During a disaster scenario, it is hard to track responders’ locations in an indoor environment. In this thesis, an indoor localization and navigation system based on Bluetooth low energy and Android is developed for helping responders report current location and quickly find the right path in the environment. Different localization algorithms are investigated and implemented. A navigation system based on A­* is also proposed

Towards generation of as-damaged BIM models using laser-scanning and as-built BIM: First estimate of as-damaged locations of reinforced concrete frame members in masonry infill structures

After an earthquake, Terrestrial Laser Scanning (TLS) can capture point clouds of the damaged state of building facades rapidly, remotely and accurately. A long-term research effort aims to develop applications that can reconstruct ‘as-damaged’ BIM models of reinforced concrete (RC) framed buildings based on their ‘as-built’ BIM models and scans of their ‘as-damaged’ states. This paper focuses on a crucial step: generating an initial ‘best-guess’ for the new locations of the façade structural members. The output serves as the seed for a recursive process in which the location and damage to each object is refined in turn. Locating the ‘as-built’ structural members in the ‘as-damaged’ scan is challenging because each member may have different displacement and damage. An algorithm was developed and tested for the case of reinforced concrete frames with masonry infill walls. It exploits the topology of the frames to map the original structural grid onto the damaged façade. The tests used synthetic datasets prepared from records of two earthquake-damaged buildings. In both cases, the results were sufficiently accurate to allow progress to the following step, assessment of the individual structural members

Reconfigurable Intelligent Surfaces in Challenging Environments: Underwater, Underground, Industrial and Disaster

Reconfigurable intelligent surfaces (RISs) have been introduced to improve the signal propagation characteristics by focusing the signal power in the preferred direction, thus making the communication environment "smart". The typical use cases and applications for the "smart" environment include beyond 5G communication networks, smart cities, etc. The main advantage of employing RISs in such networks is a more efficient exploitation of spatial degrees of freedom. This advantage manifests in better interference mitigation as well as increased spectral and energy efficiency due to passive beam steering. Challenging environments comprise a range of scenarios, which share the fact that it is extremely difficult to establish a communication link using conventional technology due to many impairments typically associated with the propagation medium and increased signal scattering. Although the challenges for the design of communication networks, and specifically the Internet of Things (IoT), in such environments are known, there is no common enabler or solution for all these applications. Interestingly, the use of RISs in such scenarios can become such an enabler and a game changer technology. Surprisingly, the benefits of RIS for wireless networking in underwater and underground medium as well as in industrial and disaster environments have not been addressed yet. In this paper, we aim at filling this gap by discussing potential use cases, deployment strategies and design aspects for RIS devices in underwater IoT, underground IoT as well as Industry 4.0 and emergency networks. In addition, novel research challenges to be addressed in this context are described.Comment: 16 pages, 13 figures, submitted for publication in IEEE journa

Tag Recognition for Quadcopter Drone Movement

Unmanned Aerial Vehicle (UAV) drone such as Parrot AR.Drone 2.0 is a flying mobile robot which has been popularly researched for the application of search and rescue mission. In this project, Robot Operating System (ROS), a free open source platform for developing robot control software is used to develop a tag recognition program for drone movement. ROS is popular with mobile robotics application development because sensors data transmission for robot control system analysis will be very handy with the use of ROS nodes and packages once the installation and compilation is done correctly. It is expected that the drone can communicate with a laptop via ROS nodes for sensors data transmission which will be further analyzed and processed for the close-loop control system. The developed program consisting of several packages is aimed to demonstrate the recognition of different tags by the drone which will be transformed into a movement command with respect to the tag recognized; in other words, a visual-based navigation program is developed

Wireless sensors networks

After studying in depth look at wireless sensor networks are quite clear improvement compared to traditional wireless networks due to several factors as are the durability of the lifetime of the batteries, allowing greater portability of sensor nodes and that can record more events to power stay longer in some places, the routing protocols networks sensors allow gain than in durability also gain in efficiency the avoidance of collisions between packets, which also ensures a lower number of unnecessary network traffic. Because of the great features of such networks are currently using sensor networks in many projects related to different fields such as: environment, health, military, construction and structures, automotive, home automation, agriculture, etc. This type of network currently is leading a technological revolution similar to that had appearance of internet, because the applications appear to be infinite, also speaks global surveillance network on the planet capable of recording and tracking people specific goods and research projects have generated great interest for application in practice

Urban palimpsest: re-placing memory in war torn city Dresden

Urban landscapes can be envisaged as a palimpsest of historical layers, some of which have disappeared while others remain active in constituting contemporary identities. Yet memory is tricky and one’s memory can be false, distorted or erased consciously or unconsciously from brain. Like history, some memories can be lost, while others others might be retained and continue to influence the present. This thesis explores memory as active construction. Construction and reconstruction are ongoing and as layered and nuanced as the history itself. Moreover, memory is both personal and collective. It is shared, appropriated, and reassigned depending on whose personal filter is determining value or elimination. The thesis uses the idea of palimpsest, a term suggesting the wearing away of a surface to expose previous realities and presences in a collage of focus, diffusion, collision and superimposition. By engaging the new media Augmented Reality (AR), the shield of the present and the individual can be dropped long enough to allow history and memory to accumulate, interact and shared beyond, the single viewer and moment of physical encounter

Annual report 2017 Deering, New Hampshire.

This is an annual report containing vital statistics for a town/city in the state of New Hampshire