394 research outputs found
Impact of Random Deployment on Operation and Data Quality of Sensor Networks
Several applications have been proposed for wireless sensor networks, including habitat monitoring, structural health monitoring, pipeline monitoring, and precision agriculture. Among the desirable features of wireless sensor networks, one is the ease of deployment. Since the nodes are capable of self-organization, they can be placed easily in areas that are otherwise inaccessible to or impractical for other types of sensing systems. In fact, some have proposed the deployment of wireless sensor networks by dropping nodes from a plane, delivering them in an artillery shell, or launching them via a catapult from onboard a ship.
There are also reports of actual aerial deployments, for example the one carried out using an unmanned aerial vehicle (UAV) at a Marine Corps combat centre in California -- the nodes were able to establish a time-synchronized, multi-hop communication network for tracking vehicles that passed along a dirt road. While this has a practical relevance for some civil applications (such as rescue operations), a more realistic deployment involves the careful planning and placement of sensors. Even then, nodes may not be placed optimally to ensure that the network is fully connected and high-quality data pertaining to the phenomena being monitored can be extracted from the network. This work aims to address the problem of random deployment through two complementary approaches:
The first approach aims to address the problem of random deployment from a communication perspective. It begins by establishing a comprehensive mathematical model to quantify the energy cost of various concerns of a fully operational wireless sensor network. Based on the analytic model, an energy-efficient topology control protocol is developed. The protocol sets eligibility metric to establish and maintain a multi-hop communication path and to ensure that all nodes exhaust their energy in a uniform manner. The second approach focuses on addressing the problem of imperfect sensing from a signal processing perspective. It investigates the impact of deployment errors (calibration, placement, and orientation errors) on the quality of the sensed data and attempts to identify robust and error-agnostic features. If random placement is unavoidable and dense deployment cannot be supported, robust and error-agnostic features enable one to recognize interesting events from erroneous or imperfect data
To Drive or to Be Driven? The Impact of Autopilot, Navigation System, and Printed Maps on Driverâs Cognitive Workload and Spatial Knowledge
The technical advances in navigation systems should enhance the driving experience,
supporting driversâ spatial decision making and learning in less familiar or unfamiliar environments.
Furthermore, autonomous driving systems are expected to take over navigation and driving in the
near future. Yet, previous studies pointed at a still unresolved gap between environmental exploration
using topographical maps and technical navigation means. Less is known about the impact of the
autonomous system on the driverâs spatial learning. The present study investigates the development
of spatial knowledge and cognitive workload by comparing printed maps, navigation systems, and
autopilot in an unfamiliar virtual environment. Learning of a new route with printed maps was
associated with a higher cognitive demand compared to the navigation system and autopilot. In
contrast, driving a route by memory resulted in an increased level of cognitive workload if the route
had been previously learned with the navigation system or autopilot. Way-finding performance
was found to be less prone to errors when learning a route from a printed map. The exploration
of the environment with the autopilot was not found to provide any compelling advantages for
landmark knowledge. Our findings suggest long-term disadvantages of self-driving vehicles for
spatial memory representations
On Evaluating Commercial Cloud Services: A Systematic Review
Background: Cloud Computing is increasingly booming in industry with many
competing providers and services. Accordingly, evaluation of commercial Cloud
services is necessary. However, the existing evaluation studies are relatively
chaotic. There exists tremendous confusion and gap between practices and theory
about Cloud services evaluation. Aim: To facilitate relieving the
aforementioned chaos, this work aims to synthesize the existing evaluation
implementations to outline the state-of-the-practice and also identify research
opportunities in Cloud services evaluation. Method: Based on a conceptual
evaluation model comprising six steps, the Systematic Literature Review (SLR)
method was employed to collect relevant evidence to investigate the Cloud
services evaluation step by step. Results: This SLR identified 82 relevant
evaluation studies. The overall data collected from these studies essentially
represent the current practical landscape of implementing Cloud services
evaluation, and in turn can be reused to facilitate future evaluation work.
Conclusions: Evaluation of commercial Cloud services has become a world-wide
research topic. Some of the findings of this SLR identify several research gaps
in the area of Cloud services evaluation (e.g., the Elasticity and Security
evaluation of commercial Cloud services could be a long-term challenge), while
some other findings suggest the trend of applying commercial Cloud services
(e.g., compared with PaaS, IaaS seems more suitable for customers and is
particularly important in industry). This SLR study itself also confirms some
previous experiences and reveals new Evidence-Based Software Engineering (EBSE)
lessons
Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions
Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEEâRobotics and Automation Society Technical CoâSponsorship. Previous editions were held since 2001 in GuimaraÌes, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal.
ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%.
After the conference, eighth papers will be published in the Portuguese journal RoboÌtica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine.
Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society â Student Activities Committee.
We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAASâCNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers.
Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true.
We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal
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