Autonomous aircraft initiative study

The results of a consulting effort to aid NASA Ames-Dryden in defining a new initiative in aircraft automation are described. The initiative described is a multi-year, multi-center technology development and flight demonstration program. The initiative features the further development of technologies in aircraft automation already being pursued at multiple NASA centers and Department of Defense (DoD) research and Development (R and D) facilities. The proposed initiative involves the development of technologies in intelligent systems, guidance, control, software development, airborne computing, navigation, communications, sensors, unmanned vehicles, and air traffic control. It involves the integration and implementation of these technologies to the extent necessary to conduct selected and incremental flight demonstrations

Autonomous environmental protection drone

During the summer, forest fires are the main reason for deforestation and the damage caused to homes and property in different communities around the world. The use of Unmanned Aerial Vehicles (UAVs, and also known as drones) applications has increased in recent years, making them an excellent solution for difficult tasks such as wildlife conservation and forest fire prevention. A forest fire detection system can be an answer to these tasks. Using a visual camera and a Convolutional Neural Network (CNN) for image processing with an UAV can result in an efficient fire detection system. However, in order to be able to have a fully autonomous system, without human intervention, for 24-hour fire observation and detection in a given geographical area, it requires a platform and automatic recharging procedures. This dissertation combines the use of technologies such as CNNs, Real Time Kinematics (RTK) and Wireless Power Transfer (WPT) with an on-board computer and software, resulting in a fully automated system to make forest surveillance more efficient and, in doing so, reallocating human resources to other locations where they are most needed.Durante o verão, os incêndios florestais constituem a principal razão do desflorestamento e dos danos causados às casas e aos bens das diferentes comunidades de todo o mundo. A utilização de veículos aéreos não tripulados (VANTs), em inglês denominados por Unmanned Aerial Vehicles (UAVs) ou Drones, aumentou nos últimos anos, tornando-os uma excelente solução para tarefas difíceis como a conservação da vida selvagem e prevenção de incêndios florestais. Um sistema de deteção de incêndio florestal pode ser uma resposta para essas tarefas. Com a utilização de uma câmara visual e uma Rede Neuronal Convolucional (RNC) para processamento de imagem com um UAV pode resultar num eficiente sistema de deteção de incêndio. No entanto, para que seja possível ter um sistema completamente autónomo, sem intervenção humana, para observação e deteção de incêndios durante 24 horas, numa dada área geográfica, requer uma plataforma e procedimentos de recarga automática. Esta dissertação reúne o uso de tecnologias como RNCs, posicionamento cinemático em tempo real (RTK) e transferência de energia sem fios (WPT) com um computador e software de bordo, resultando num sistema totalmente automatizado para tornar a vigilância florestal mais eficiente e, ao fazê-lo, realocando recursos humanos para outros locais, onde estes são mais necessários

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs

Utilization Of A Large-Scale Wireless Sensor Network For Intrusion Detection And Border Surveillance

To control the border more effectively, countries may deploy a detection system that enables real-time surveillance of border integrity. Events such as border crossings need to be monitored in real time so that any border entries can be noted by border security forces and destinations marked for apprehension. Wireless Sensor Networks (WSNs) are promising for border security surveillance because they enable enforcement teams to monitor events in the physical environment. In this work, probabilistic models have been presented to investigate senor development schemes while considering the environmental factors that affect the sensor performance. Simulation studies have been carried out using the OPNET to verify the theoretical analysis and to find an optimal node deployment scheme that is robust and efficient by incorporating geographical coordination in the design. Measures such as adding camera and range-extended antenna to each node have been investigated to improve the system performance. A prototype WSN based surveillance system has been developed to verify the proposed approach

Applications of Internet of Things

This book introduces the Special Issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITSs), (II) location-based services (LBSs), and (III) sensing techniques and applications. Three papers on ITSs are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBSs are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by Gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al