Early forest fire detection by vision-enabled wireless sensor networks

Wireless sensor networks constitute a powerful technology particularly suitable for environmental monitoring. With regard to wildfires, they enable low-cost fine-grained surveillance of hazardous locations like wildland-urban interfaces. This paper presents work developed during the last 4 years targeting a vision-enabled wireless sensor network node for the reliable, early on-site detection of forest fires. The tasks carried out ranged from devising a robust vision algorithm for smoke detection to the design and physical implementation of a power-efficient smart imager tailored to the characteristics of such an algorithm. By integrating this smart imager with a commercial wireless platform, we endowed the resulting system with vision capabilities and radio communication. Numerous tests were arranged in different natural scenarios in order to progressively tune all the parameters involved in the autonomous operation of this prototype node. The last test carried out, involving the prescribed burning of a 95 x 20-m shrub plot, confirmed the high degree of reliability of our approach in terms of both successful early detection and a very low false-alarm rate. Journal compilationMinisterio de Ciencia e Innovación TEC2009-11812, IPT-2011-1625-430000Office of Naval Research (USA) N000141110312Centro para el Desarrollo Tecnológico e Industrial IPC-2011100

Facial Privacy Protection in Airborne Recreational Videography

PhDCameras mounted on Micro Aerial Vehicles (MAVs) are increasingly used for recreational photography and videography. However, aerial photographs and videographs of public places often contain faces of bystanders thus leading to a perceived or actual violation of privacy. To address this issue, this thesis presents a novel privacy lter that adaptively blurs sensitive image regions and is robust against di erent privacy attacks. In particular, the thesis aims to impede face recognition from airborne cameras and explores the design space to determine when a face in an airborne image is inherently protected, that is when an individual is not recognisable. When individuals are recognisable by facial recognition algorithms, an adaptive ltering mechanism is proposed to lower the face resolution in order to preserve privacy while ensuring a minimum reduction of the delity of the image. Moreover, the lter's parameters are pseudo-randomly changed to make the applied protection robust against di erent privacy attacks. In case of videography, the lter is updated with a motion-dependent temporal smoothing to minimise icker introduced by the pseudo-random switching of the lter's parameters, without compromising on its robustness against di erent privacy attacks. To evaluate the e ciency of the proposed lter, the thesis uses a state-of-the-art face recognition algorithm and synthetically generated face data with 3D geometric image transformations that mimic faces captured from an MAV at di erent heights and pitch angles. For the videography scenario, a small video face data set is rst captured and then the proposed lter is evaluated against di erent privacy attacks and the quality of the resulting video using both objective measures and a subjective test.This work was supported in part by the research initiative Intelligent Vision Austria with funding from the Austrian Federal Ministry of Science, Research and Economy and the Austrian Institute of Technology

Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments

Revisión de algoritmos, métodos y técnicas para la detección de UAVs y UAS en aplicaciones de audio, radiofrecuencia y video

Unmanned Aerial Vehicles (UAVs), also known as drones, have had an exponential evolution in recent times due in large part to the development of technologies that enhance the development of these devices. This has resulted in increasingly affordable and better-equipped artifacts, which implies their application in new fields such as agriculture, transport, monitoring, and aerial photography. However, drones have also been used in terrorist acts, privacy violations, and espionage, in addition to involuntary accidents in high-risk zones such as airports. In response to these events, multiple technologies have been introduced to control and monitor the airspace in order to ensure protection in risk areas. This paper is a review of the state of the art of the techniques, methods, and algorithms used in video, radiofrequency, and audio-based applications to detect UAVs and Unmanned Aircraft Systems (UAS). This study can serve as a starting point to develop future drone detection systems with the most convenient technologies that meet certain requirements of optimal scalability, portability, reliability, and availability.Los vehículos aéreos no tripulados, conocidos también como drones, han tenido una evolución exponencial en los últimos tiempos, debido en gran parte al desarrollo de las tecnologías que potencian su desarrollo, lo cual ha desencadenado en artefactos cada vez más asequibles y con mejores prestaciones, lo que implica el desarrollo de nuevas aplicaciones como agricultura, transporte, monitoreo, fotografía aérea, entre otras. No obstante, los drones se han utilizado también en actos terroristas, violaciones a la privacidad y espionaje, además de haber producido accidentes involuntarios en zonas de alto riesgo de operación como aeropuertos. En respuesta a dichos eventos, aparecen tecnologías que permiten controlar y monitorear el espacio aéreo, con el fin de garantizar la protección en zonas de riesgo. En este artículo se realiza un estudio del estado del arte de la técnicas, métodos y algoritmos basados en video, en análisis de sonido y en radio frecuencia, para tener un punto de partida que permita el desarrollo en el futuro de un sistema de detección de drones, con las tecnologías más propicias, según los requerimientos que puedan ser planteados con las características de escalabilidad, portabilidad, confiabilidad y disponibilidad óptimas

Spatio-Temporal Information for Action Recognition in Thermal Video Using Deep Learning Model

Researchers can evaluate numerous information to ensure automated monitoring due to the widespread use of surveillance cameras in smart cities. For the monitoring of violence or abnormal behaviors in smart cities, schools, hospitals, residences, and other observational domains, an enhanced safety and security system is required to prevent any injuries that might result in ecological, economic and social losses. Automatic detection for prompt actions is vital and may help the respective departments effectively. Based on thermal imaging, several researchers have concentrated on object detection, tracking, and action identification. Few studies have simultaneously extracted spatial-temporal information from a thermal image and utilized it to recognize human actions. This research provides a novelty based on frame-level and spatial and temporal features which combines richer context temporal information to address the issue of poor efficiency and less accuracy in detecting abnormal/violent behavior in thermal monitoring devices. The model can locate (bounded box) video frame areas involving different human activities and recognize (classify) the actions. The dataset on human behavior includes videos captured with infrared cameras in both indoor and outdoor environments. The experimental results using the publicly available benchmark datasets reveal the proposed model\u27s efficiency. Our model achieves 98.5% and 94.85% accuracy on IITR Infrared Action Recognition (IITR-IAR) and Thermal Simulated Fall (TSF) datasets, respectively. In addition, the proposed method may be evaluated in more realistic conditions, such as zooming in and out etc

The Design Fabrication and Flight Testing of an Academic Research Platform for High Resolution Terrain Imaging

This thesis addresses the design, construction, and flight testing of an Unmanned Aircraft System (UAS) created to serve as a testbed for Intelligence, Surveillance, and Reconnaissance (ISR) research topics that require the rapid acquisition and processing of high resolution aerial imagery and are to be performed by academic research institutions. An analysis of the requirements of various ISR research applications and the practical limitations of academic research yields a consolidated set of requirements by which the UAS is designed. An iterative design process is used to transition from these requirements to cycles of component selection, systems integration, flight tests, diagnostics, and subsystem redesign. The resulting UAS is designed as an academic research platform to support a variety of ISR research applications ranging from human machine interaction with UAS technology to orthorectified mosaic imaging. The lessons learned are provided to enable future researchers to create similar systems

Design of a quadcopter to work at high temperatures

The project develops the design of a quadcopter to work within industrial plants which can be found even at 80 degrees Celsius. These plants should be checked as a way of detecting faults or cracks to prevent other serious incidents that may arise. Both the whole building as well as industrial machinery, which are inside the plant, should be inspected without the need to wait until the infrastructure is fully cooled down. Both external mechanical defense to get close to surfaces, adapting to customer specifications, as well as mechanical and electronic components in the multicopter are designed. It shall support all the requested temperature at least 80 degrees.El proyecto desarrolla el diseño de un cuadricóptero para trabajar dentro de plantas industriales que se pueden encontrar hasta una temperatura de 80 grados. Estos edificios deben ser revisados continuamente como una forma de detectar fallas o grietas que puedan evitar otros incidentes más graves que pudieran surgir. Todo el edificio, así como la maquinaria industrial que están dentro de la planta, deben ser inspeccionados sin la necesidad de esperar hasta que la infraestructura está totalmente enfriada ...Ingeniería Industria