Abstract

Digital Elevation Models (DEMs) are used to derive information from the morphology of a land. The topographic attributes obtained from the DEM data allow the construction of watershed delineation useful for predicting the behavior of systems and for studying hydrological processes. Imagery acquired from Unmanned Aerial Vehicles (UAVs) and 3D photogrammetry techniques offer cost-effective advantages over other remote sensing methods such as LIDAR or RADAR. In particular, a high spatial resolution for measuring the terrain microtopography. In this work, we propose a Structure from Motion (SfM) pipeline using UAVs for generating high-resolution, high-quality DEMs for developing a rainfall-runoff model to study flood areas. SfM is a computer vision technique that simultaneously estimates the 3D coordinates of a scene and the pose of a camera that moves around it. The result is a 3D point cloud which we process to obtain a georeference model from the GPS information of the camera and ground control points. The pipeline is based on open source software OpenSfM and OpenDroneMap. Encouraging experimental results on a test land show that the produced DEMs meet the metrological requirements for developing a surface-runoff model. © Published under licence by IOP Publishing Ltd. This work has been partly funded by Universidad Tecnológica de Bolívar project (FI2006T2001). The authors thank Direccion de Investigaciones Universidad Tecnologica de Bolivar for their support.

Abstract

TNO has formulated the ambition of founding a basis for the development of flexible multi-data source and multi-application (ad hoc) sensor networks. These networks are envisioned on a scale that is beyond networks for specific and separate sensor networks. These separate networks need in the future to be combined intelligently in order to assist users with real-time assessment during operations in challenging environments. For this, enabling technologies such as network architectures and model-based data-interpretation are being developed. In this context TNO has developed wireless sensor networks that consist of very small and cheap nodes. Each node can be the size of a golf ball and can run for a long time on an A4 battery. They are designed to be deployed on a massive scale (100-10k or larger). In the tactical environment they are typically lying on the ground. Because it is very difficult to test the performance of such deployments under realistic and controllable conditions, simulation is the only way to get insight in this. This paper focuses on how to study the performance of massive deployments of these sensor networks through simulation. It describes the modeling, validation and simulation of such networks. Features such as antenna patterns, radio propagation/path loss, terrain, medium access and transport protocols, routing, and simulation parallelization are discussed. Model validation experiments for the antenna pattern, the path loss propagation and communication performance for nodes lying on the ground will be discussed. It further describes the implementation of a promising energy aware MAC and transport protocol that are proposed in the literature and are suitable for congestion mitigation and cross-layer optimization. Results on timeliness of messages, bandwidth and power consumption are discussed. ©2008 IEEE.

Abstract

For several years, either in the frame of research projects (French, European), or for direct application on aircraft programs, Dassault Aviation has developed multifunctional materials and structures (MMS) with specific benefits in aerodynamics, de-icing, acoustic or electromagnetisms. The main challenge is to get the best compromise between the high functional performances desired and the mechanical and aeronautic environment resistance needed for the application. This presentation will review some examples of development performed in the recent years for aircraft aerodynamics improvement, icing protection, acoustics and new antenna radomes.