525 research outputs found
Distributed urban traffic applications based on CORBA event services
Intelligent transportation systems (ITS) in urban environments are based today on
modern embedded systems with enhanced digital connectivity and higher processing capabilities,
supporting distributed applications working in a cooperative manner. This paper provides an
overview about modern cooperative ITS equipments and presents a distributed application to
be used in an urban data network. As a case example, an application based on an embedded
CORBA-compliant middleware layer and several computer vision equipments is presented.
Results prove the feasibility of distributed applications for building intelligent urban
environments
Dagstuhl News January - December 2007
"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic
Multi-dimensional data indexing and range query processing via Voronoi diagram for internet of things
In a typical Internet of Things (IoT) deployment such as smart cities and Industry 4.0, the amount of sensory data collected from physical world is significant and wide-ranging. Processing large amount of real-time data from the diverse IoT devices is challenging. For example, in IoT environment, wireless sensor networks (WSN) are typically used for the monitoring and collecting of data in some geographic area. Spatial range queries with location constraints to facilitate data indexing are traditionally employed in such applications, which allows the querying and managing the data based on SQL structure. One particular challenge is to minimize communication cost and storage requirements in multi-dimensional data indexing approaches. In this paper, we present an energy- and time-efficient multidimensional data indexing scheme, which is designed to answer range query. Specifically, we propose data indexing methods which utilize hierarchical indexing structures, using binary space partitioning (BSP), such as kd-tree, quad-tree, k-means clustering, and Voronoi-based methods to provide more efficient routing with less latency. Simulation results demonstrate that the Voronoi Diagram-based algorithm minimizes the average energy consumption and query response time
Identifying and Explaining Safety-critical Scenarios for Autonomous Vehicles via Key Features
Ensuring the safety of autonomous vehicles (AVs) is of utmost importance and
testing them in simulated environments is a safer option than conducting
in-field operational tests. However, generating an exhaustive test suite to
identify critical test scenarios is computationally expensive as the
representation of each test is complex and contains various dynamic and static
features, such as the AV under test, road participants (vehicles, pedestrians,
and static obstacles), environmental factors (weather and light), and the
road's structural features (lanes, turns, road speed, etc.). In this paper, we
present a systematic technique that uses Instance Space Analysis (ISA) to
identify the significant features of test scenarios that affect their ability
to reveal the unsafe behaviour of AVs. ISA identifies the features that best
differentiate safety-critical scenarios from normal driving and visualises the
impact of these features on test scenario outcomes (safe/unsafe) in 2D. This
visualization helps to identify untested regions of the instance space and
provides an indicator of the quality of the test suite in terms of the
percentage of feature space covered by testing. To test the predictive ability
of the identified features, we train five Machine Learning classifiers to
classify test scenarios as safe or unsafe. The high precision, recall, and F1
scores indicate that our proposed approach is effective in predicting the
outcome of a test scenario without executing it and can be used for test
generation, selection, and prioritization.Comment: 28 pages, 6 figure
Evidence-based Development of Trustworthy Mobile Medical Apps
abstract: Widespread adoption of smartphone based Mobile Medical Apps (MMAs) is opening new avenues for innovation, bringing MMAs to the forefront of low cost healthcare delivery. These apps often control human physiology and work on sensitive data. Thus it is necessary to have evidences of their trustworthiness i.e. maintaining privacy of health data, long term operation of wearable sensors and ensuring no harm to the user before actual marketing. Traditionally, clinical studies are used to validate the trustworthiness of medical systems. However, they can take long time and could potentially harm the user. Such evidences can be generated using simulations and mathematical analysis. These methods involve estimating the MMA interactions with human physiology. However, the nonlinear nature of human physiology makes the estimation challenging.
This research analyzes and develops MMA software while considering its interactions with human physiology to assure trustworthiness. A novel app development methodology is used to objectively evaluate trustworthiness of a MMA by generating evidences using automatic techniques. It involves developing the Health-Dev β tool to generate a) evidences of trustworthiness of MMAs and b) requirements assured code generation for vulnerable components of the MMA without hindering the app development process. In this method, all requests from MMAs pass through a trustworthy entity, Trustworthy Data Manager which checks if the app request satisfies the MMA requirements. This method is intended to expedite the design to marketing process of MMAs. The objectives of this research is to develop models, tools and theory for evidence generation and can be divided into the following themes:
• Sustainable design configuration estimation of MMAs: Developing an optimization framework which can generate sustainable and safe sensor configuration while considering interactions of the MMA with the environment.
• Evidence generation using simulation and formal methods: Developing models and tools to verify safety properties of the MMA design to ensure no harm to the human physiology.
• Automatic code generation for MMAs: Investigating methods for automatically
• Performance analysis of trustworthy data manager: Evaluating response time generating trustworthy software for vulnerable components of a MMA and evidences.performance of trustworthy data manager under interactions from non-MMA smartphone apps.Dissertation/ThesisDoctoral Dissertation Computer Science 201
Selected Papers from the First International Symposium on Future ICT (Future-ICT 2019) in Conjunction with 4th International Symposium on Mobile Internet Security (MobiSec 2019)
The International Symposium on Future ICT (Future-ICT 2019) in conjunction with the 4th International Symposium on Mobile Internet Security (MobiSec 2019) was held on 17–19 October 2019 in Taichung, Taiwan. The symposium provided academic and industry professionals an opportunity to discuss the latest issues and progress in advancing smart applications based on future ICT and its relative security. The symposium aimed to publish high-quality papers strictly related to the various theories and practical applications concerning advanced smart applications, future ICT, and related communications and networks. It was expected that the symposium and its publications would be a trigger for further related research and technology improvements in this field
- …