54,340 research outputs found
Information Centric Networking in the IoT: Experiments with NDN in the Wild
This paper explores the feasibility, advantages, and challenges of an
ICN-based approach in the Internet of Things. We report on the first NDN
experiments in a life-size IoT deployment, spread over tens of rooms on several
floors of a building. Based on the insights gained with these experiments, the
paper analyses the shortcomings of CCN applied to IoT. Several interoperable
CCN enhancements are then proposed and evaluated. We significantly decreased
control traffic (i.e., interest messages) and leverage data path and caching to
match IoT requirements in terms of energy and bandwidth constraints. Our
optimizations increase content availability in case of IoT nodes with
intermittent activity. This paper also provides the first experimental
comparison of CCN with the common IoT standards 6LoWPAN/RPL/UDP.Comment: 10 pages, 10 figures and tables, ACM ICN-2014 conferenc
Impact of polarization diversity in massive MIMO for industry 4.0
The massive polarimetric radio channel is evaluated in an indoor industrial scenario at 3.5 GHz using a 10Ă—10 uniform rectangular array (URA). The analysis is based on (1) propagation characteristics like the average received gain and the power to interference ratio from the Gram matrix and (2) system-oriented metrics such as sum-rate capacity with maximum-ratio transmitter (MRT). The results clearly show the impact of polarization diversity in an industrial scenario and how it can considerably improve different aspects of the system design. Results for sum-rate capacity are promising and show that the extra degree of freedom, provided by polarization diversity, can optimize the performance of a very simple precoder, the MRT
An IoT-based solution for monitoring a fleet of educational buildings focusing on energy efficiency
Raising awareness among young people and changing their behaviour and habits concerning energy usage iskey to achieving sustained energy saving. Additionally, young people are very sensitive to environmental protection so raising awareness among children is much easier than with any other group of citizens. This work examinesways to create an innovative Information & Communication Technologies (ICT) ecosystem (including web-based, mobile, social and sensing elements) tailored specifically for school environments, taking into account both theusers (faculty, staff, students, parents) and school buildings, thus motivating and supporting young citizenĹ› behavioural change to achieve greater energy efficiency. A mixture of open-source IoT hardware and proprietary platforms on the infrastructure level, are currently being utilized for monitoring a fleet of 18 educational buildings across 3 countries, comprising over 700 IoT monitoring points. Hereon presented is the system's high-level architecture, as well as several aspects of its implementation, related to the application domain of educational building monitoring and energy efficiency. The system is developed based on open-source technologies andservices in order to make it capable of providing open IT-infrastructure and support from different commercial hardware/sensor vendors as well as open-source solutions. The system presented can be used to develop and offer newapp-based solutions that can be used either for educational purposes or for managing the energy efficiency ofthebuilding. The system is replicable and adaptable to settings that may be different than the scenarios envisionedhere (e.g., targeting different climate zones), different IT infrastructures and can be easily extended to accommodate integration with other systems. The overall performance of the system is evaluated in real-world environment in terms of scalability, responsiveness and simplicity
Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study
Developing robot agnostic software frameworks involves synthesizing the
disparate fields of robotic theory and software engineering while
simultaneously accounting for a large variability in hardware designs and
control paradigms. As the capabilities of robotic software frameworks increase,
the setup difficulty and learning curve for new users also increase. If the
entry barriers for configuring and using the software on robots is too high,
even the most powerful of frameworks are useless. A growing need exists in
robotic software engineering to aid users in getting started with, and
customizing, the software framework as necessary for particular robotic
applications. In this paper a case study is presented for the best practices
found for lowering the barrier of entry in the MoveIt! framework, an
open-source tool for mobile manipulation in ROS, that allows users to 1)
quickly get basic motion planning functionality with minimal initial setup, 2)
automate its configuration and optimization, and 3) easily customize its
components. A graphical interface that assists the user in configuring MoveIt!
is the cornerstone of our approach, coupled with the use of an existing
standardized robot model for input, automatically generated robot-specific
configuration files, and a plugin-based architecture for extensibility. These
best practices are summarized into a set of barrier to entry design principles
applicable to other robotic software. The approaches for lowering the entry
barrier are evaluated by usage statistics, a user survey, and compared against
our design objectives for their effectiveness to users
Deep Drone Racing: From Simulation to Reality with Domain Randomization
Dynamically changing environments, unreliable state estimation, and operation
under severe resource constraints are fundamental challenges that limit the
deployment of small autonomous drones. We address these challenges in the
context of autonomous, vision-based drone racing in dynamic environments. A
racing drone must traverse a track with possibly moving gates at high speed. We
enable this functionality by combining the performance of a state-of-the-art
planning and control system with the perceptual awareness of a convolutional
neural network (CNN). The resulting modular system is both platform- and
domain-independent: it is trained in simulation and deployed on a physical
quadrotor without any fine-tuning. The abundance of simulated data, generated
via domain randomization, makes our system robust to changes of illumination
and gate appearance. To the best of our knowledge, our approach is the first to
demonstrate zero-shot sim-to-real transfer on the task of agile drone flight.
We extensively test the precision and robustness of our system, both in
simulation and on a physical platform, and show significant improvements over
the state of the art.Comment: Accepted as a Regular Paper to the IEEE Transactions on Robotics
Journal. arXiv admin note: substantial text overlap with arXiv:1806.0854
Regulating Highly Automated Robot Ecologies: Insights from Three User Studies
Highly automated robot ecologies (HARE), or societies of independent
autonomous robots or agents, are rapidly becoming an important part of much of
the world's critical infrastructure. As with human societies, regulation,
wherein a governing body designs rules and processes for the society, plays an
important role in ensuring that HARE meet societal objectives. However, to
date, a careful study of interactions between a regulator and HARE is lacking.
In this paper, we report on three user studies which give insights into how to
design systems that allow people, acting as the regulatory authority, to
effectively interact with HARE. As in the study of political systems in which
governments regulate human societies, our studies analyze how interactions
between HARE and regulators are impacted by regulatory power and individual
(robot or agent) autonomy. Our results show that regulator power, decision
support, and adaptive autonomy can each diminish the social welfare of HARE,
and hint at how these seemingly desirable mechanisms can be designed so that
they become part of successful HARE.Comment: 10 pages, 7 figures, to appear in the 5th International Conference on
Human Agent Interaction (HAI-2017), Bielefeld, German
- …