Self-Positioning Smart Buoys, The \u27Un-Buoy\u27 Solution: Logistic Considerations Using Autonomous Surface Craft Technology and Improved Communications Infrastructure

Moored buoys have long served national interests, but incur high development, construction, installation, and maintenance costs. Buoys which drift off-location can pose hazards to mariners, and in coastal waters may cause environmental damage. Moreover, retrieval, repair and replacement of drifting buoys may be delayed when data would be most useful. Such gaps in coastal buoy data can pose a threat to national security by reducing maritime domain awareness. The concept of self-positioning buoys has been advanced to reduce installation cost by eliminating mooring hardware. We here describe technology for operation of reduced cost self-positioning buoys which can be used in coastal or oceanic waters. The ASC SCOUT model is based on a self-propelled, GPS-positioned, autonomous surface craft that can be pre-programmed, autonomous, or directed in real time. Each vessel can communicate wirelessly with deployment vessels and other similar buoys directly or via satellite. Engineering options for short or longer term power requirements are considered, in addition to future options for improved energy delivery systems. Methods of reducing buoy drift and position-maintaining energy requirements for self-locating buoys are also discussed, based on the potential of incorporating traditional maritime solutions to these problems. We here include discussion of the advanced Delay Tolerant Networking (DTN) communications draft protocol which offers improved wireless communication capabilities underwater, to adjacent vessels, and to satellites. DTN is particularly adapted for noisy or loss-prone environments, thus it improves reliability. In addition to existing buoy communication via commercial satellites, a growing network of small satellites known as PICOSATs can be readily adapted to provide low-cost communications nodes for buoys. Coordination with planned vessel Automated Identification Systems (AIS) and International Maritime Organization standards for buoy and vessel notificat- - ion systems are reviewed and the legal framework for deployment of autonomous surface vessels is considered

Sensor-assisted Video Mapping of the Seafloor

In recent years video surveys have become an increasingly important ground-truthing of acousticseafloor characterization and benthic habitat mapping studies. However, the ground-truthing and detailed characterization provided by video are still typically done using sparse sample imagery supplemented by physical samples. Combining single video frames in a seamless mosaic can provide a tool by which imagery has significant areal coverage, while at the same time showing small fauna and biological features at mm resolution. The generation of such a mosaic is a challenging task due to height variations of the imaged terrain and decimeter scale knowledge of camera position. This paper discusses the current role of underwater video survey, and the potential for generating consistent, quantitative image maps using video data, accompanied by data that can be measured by auxiliary sensors with sufficient accuracy, such as camera tilt and heading, and their use in automated mosaicking techniques. The camera attitude data also provide the necessary information to support the development of a video collage. The collage provides a quick look at the large spatial scale features in a scene and can be used to pinpoint regions that are likely to yield useful information when rendered into high-resolution mosaics. It is proposed that high quality mosaics can be produced using consumer-grade cameras and low-cost sensors, thereby allowing for the economical scientific video surveys. A case study is presented with the results from benthic habitat mapping and the ground-truthing ofseafloor acoustic data using both real underwater imagery and simulations. A computer modeling of the process of video data acquisition (in particular on a non-flat terrain) allows for a better understanding of the main sources of error in mosaic generation and for the choice of near-optimal processing strategies. Various spatial patterns of video survey coverage are compared and it is shown that some patterns have certain advantages in the sense of accumulated error and overall mosaic accuracy

Tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi MARA terhadap mata pelajaran Bahasa Inggeris

Kajian ini dilakukan untuk mengenal pasti tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi Mara Sri Gading terhadap Bahasa Inggeris. Kajian yang dijalankan ini berbentuk deskriptif atau lebih dikenali sebagai kaedah tinjauan. Seramai 325 orang pelajar Diploma in Construction Technology dari Kolej Kemahiran Tinggi Mara di daerah Batu Pahat telah dipilih sebagai sampel dalam kajian ini. Data yang diperoleh melalui instrument soal selidik telah dianalisis untuk mendapatkan pengukuran min, sisihan piawai, dan Pekali Korelasi Pearson untuk melihat hubungan hasil dapatan data. Manakala, frekuensi dan peratusan digunakan bagi mengukur penguasaan pelajar. Hasil dapatan kajian menunjukkan bahawa tahap penguasaan Bahasa Inggeris pelajar adalah berada pada tahap sederhana manakala faktor utama yang mempengaruhi penguasaan Bahasa Inggeris tersebut adalah minat diikuti oleh sikap. Hasil dapatan menggunakan pekali Korelasi Pearson juga menunjukkan bahawa terdapat hubungan yang signifikan antara sikap dengan penguasaan Bahasa Inggeris dan antara minat dengan penguasaan Bahasa Inggeris. Kajian menunjukkan bahawa semakin positif sikap dan minat pelajar terhadap pengajaran dan pembelajaran Bahasa Inggeris semakin tinggi pencapaian mereka. Hasil daripada kajian ini diharapkan dapat membantu pelajar dalam meningkatkan penguasaan Bahasa Inggeris dengan memupuk sikap positif dalam diri serta meningkatkan minat mereka terhadap Bahasa Inggeris dengan lebih baik. Oleh itu, diharap kajian ini dapat memberi panduan kepada pihak-pihak yang terlibat dalam membuat kajian yang akan datang

AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades

Design of a multiple bloom filter for distributed navigation routing

Unmanned navigation of vehicles and mobile robots can be greatly simplified by providing environmental intelligence with dispersed wireless sensors. The wireless sensors can work as active landmarks for vehicle localization and routing. However, wireless sensors are often resource scarce and require a resource-saving design. In this paper, a multiple Bloom-filter scheme is proposed to compress a global routing table for a wireless sensor. It is used as a lookup table for routing a vehicle to any destination but requires significantly less memory space and search effort. An error-expectation-based design for a multiple Bloom filter is proposed as an improvement to the conventional false-positive-rate-based design. The new design is shown to provide an equal relative error expectation for all branched paths, which ensures a better network load balance and uses less memory space. The scheme is implemented in a project for wheelchair navigation using wireless camera motes. © 2013 IEEE

A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving