scholarly journals A database system for querying of river networks: facilitating monitoring and prediction applications

2021 ◽  
Author(s):  
Erik Bollen ◽  
Brianna R. Pagán ◽  
Bart Kuijpers ◽  
Stijn Van Hoey ◽  
Nele Desmet ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
Real Time ◽  
River System ◽  
Sensor Data ◽  
Data Management System ◽  
Data Sets ◽  
River Systems ◽  
Real Time Processing ◽  
Data Driven Approach

Abstract The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, … are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.

scholarly journals Measuring the Morphology and Dynamics of the Snake River by Remote Sensing

2011 ◽  
Vol 33 ◽  
pp. 3-15
Author(s):  
Carl Legleiter
Keyword(s):  
Remote Sensing ◽  
Image Data ◽  
River System ◽  
Field Work ◽  
Hyperspectral Data ◽  
Snake River ◽  
Central Component ◽  
Data Sets ◽  
Channel Form ◽  
And Behavior

The Snake River is a central component of Grand Teton National Park, and this dynamic fluvial system plays a key role in shaping the landscape and creating diverse aquatic and terrestrial habitat. The river’s complexity and propensity for change make effective characterization of this resource difficult, however, and conventional, ground-based methods are simply inadequate. Remote sensing provides an appealing alternative approach that could facilitate resource management while providing novel insight on the factors controlling channel form and behavior. In this study, we evaluate the potential to measure the morphology and dynamics of a large, complex river system such as the Snake using optical image data. Initially, we made use of existing, publicly available images and basic digital aerial photography acquired in August 2010. Analysis to date has focused on estimating flow depths from these data, and preliminary results indicate that remote bathymetric mapping is feasible but not highly accurate, with important constraints related to the limited radiometric resolution of these data sets. Additional, more sophisticated hyperspectral data are scheduled for collection in 2011, along with further field work.

scholarly journals A Framework for Real Time Processing of Sensor Data in the Cloud

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Supun Kamburugamuve ◽  
Leif Christiansen ◽  
Geoffrey Fox
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Cloud Services ◽  
Sensor Data ◽  
Smart Devices ◽  
Time Data ◽  
Real Time Processing ◽  
Real Time Data ◽  
Autonomous Robot Navigation ◽  
Real Time Data Processing

We describe IoTCloud, a platform to connect smart devices to cloud services for real time data processing and control. A device connected to IoTCloud can communicate with real time data analysis frameworks deployed in the cloud via messaging. The platform design is scalable in connecting devices as well as transferring and processing data. With IoTCloud, a user can develop real time data processing algorithms in an abstract framework without concern for the underlying details of how the data is distributed and transferred. For this platform, we primarily consider real time robotics applications such as autonomous robot navigation, where there are strict requirements on processing latency and demand for scalable processing. To demonstrate the effectiveness of the system, a robotic application is developed on top of the framework. The system and the robotics application characteristics are measured to show that data processing in central servers is feasible for real time sensor applications.

scholarly journals Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 440
Author(s):  
Anup Vanarse ◽  
Adam Osseiran ◽  
Alexander Rassau ◽  
Peter van der Made
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Olfactory Pathway ◽  
Ultra Low Power ◽  
Real Time Processing ◽  
Power Efficient ◽  
Neuromorphic Hardware ◽  
Neurophysiological Studies

Current developments in artificial olfactory systems, also known as electronic nose (e-nose) systems, have benefited from advanced machine learning techniques that have significantly improved the conditioning and processing of multivariate feature-rich sensor data. These advancements are complemented by the application of bioinspired algorithms and architectures based on findings from neurophysiological studies focusing on the biological olfactory pathway. The application of spiking neural networks (SNNs), and concepts from neuromorphic engineering in general, are one of the key factors that has led to the design and development of efficient bioinspired e-nose systems. However, only a limited number of studies have focused on deploying these models on a natively event-driven hardware platform that exploits the benefits of neuromorphic implementation, such as ultra-low-power consumption and real-time processing, for simplified integration in a portable e-nose system. In this paper, we extend our previously reported neuromorphic encoding and classification approach to a real-world dataset that consists of sensor responses from a commercial e-nose system when exposed to eight different types of malts. We show that the proposed SNN-based classifier was able to deliver 97% accurate classification results at a maximum latency of 0.4 ms per inference with a power consumption of less than 1 mW when deployed on neuromorphic hardware. One of the key advantages of the proposed neuromorphic architecture is that the entire functionality, including pre-processing, event encoding, and classification, can be mapped on the neuromorphic system-on-a-chip (NSoC) to develop power-efficient and highly-accurate real-time e-nose systems.

scholarly journals Architecture and Architectural Patterns for Mobile Augmented Reality

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Donald Munro ◽  
Andre Calitz ◽  
Dieter Vogts
Keyword(s):  
Augmented Reality ◽  
Software Architecture ◽  
Real Time ◽  
Sensor Data ◽  
Mobile Augmented Reality ◽  
Software Developers ◽  
Real Time Processing ◽  
Main Requirement ◽  
Architectural Patterns ◽  
Architecture And Design

A software architecture codifies the design choices of software developers, which defines a modularorganizational spine for the design of a software artefact. Different architectures may bespecified for different types of artefacts, a real-time interactive artefact, for example, wouldhave markedly different requirements to those of a batch based transactional system. The use ofsoftware architecture becomes increasingly important as the complexity ofartefacts increases. Augmented Reality blends the real world observed through a computerinterface, with a computer generated virtual world. With the advent ofpowerful mobile devices, Mobile Augmented Reality (MAR)applications have become increasingly feasible, however the increased power hasled to increased complexity. Most MAR research has been directed towardstechnologies and not design resulting in a dearth of architecture and design literature for MAR. This research is targeted at addressing this void. The main requirement that a MAR architecture must meet isidentified as being the efficient real-time processing of data streams such asvideo frames and sensor data. A set of highly parallelised architecturalpatterns are documented within the context of MAR that meet thisrequirement. The contribution of this research is a software architecture, codifiedas architectural patterns, for MAR.

Implementation of VRML/Java Web-Based Animation and Communications for the Next Generation Inspection System (NGIS) Real-Time Controller

2000 ◽  
Author(s):  
William Shackleford ◽  
Keith Stouffer
Keyword(s):  
Real Time ◽  
Web Site ◽  
Remote Access ◽  
Sensor Data ◽  
Open Architecture ◽  
Inspection System ◽  
Next Generation ◽  
Real Time Processing ◽  
Open Architecture Controller ◽  
Measuring Machine

Abstract The Next Generation Inspection System (NGIS) project is a testbed that consists of a Cordax Coordinate Measuring Machine (CMM), advanced sensors, and the National Institute of Standards and Technology (NIST) Real-Time Control System (RCS) open architecture controller. The RCS controller permits real-time processing of sensor data for feedback control of the inspection probe. The open architecture controller permits external access to internal data, such as the current position of the probe. A remote access web site was developed to access this data to drive a Virtual Reality Modeling Language (VRML) * model of the Cordax CMM. The remote access web site contains a client-controlled pan/tilt/zoom camera which sends video to the client as well as the VRML 3D model of the CMM that is controlled by the NGIS controller located at NIST. This remote access web site allows a client to monitor a remote inspection with a PC and an internet connection.

scholarly journals Integration and Exploitation of Sensor Data in Smart Cities through Event-Driven Applications

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1372 ◽  
Author(s):  
Manuel Garcia Alvarez ◽  
Javier Morales ◽  
Menno-Jan Kraak
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Spatial Information ◽  
Smart Cities ◽  
Spatial Data Analysis ◽  
Sensor Data ◽  
Reference Architecture ◽  
Real Time Processing ◽  
Time Processing ◽  
Event Driven

Smart cities are urban environments where Internet of Things (IoT) devices provide a continuous source of data about urban phenomena such as traffic and air pollution. The exploitation of the spatial properties of data enables situation and context awareness. However, the integration and analysis of data from IoT sensing devices remain a crucial challenge for the development of IoT applications in smart cities. Existing approaches provide no or limited ability to perform spatial data analysis, even when spatial information plays a significant role in decision making across many disciplines. This work proposes a generic approach to enabling spatiotemporal capabilities in information services for smart cities. We adopted a multidisciplinary approach to achieving data integration and real-time processing, and developed a reference architecture for the development of event-driven applications. This type of applications seamlessly integrates IoT sensing devices, complex event processing, and spatiotemporal analytics through a processing workflow for the detection of geographic events. Through the implementation and testing of a system prototype, built upon an existing sensor network, we demonstrated the feasibility, performance, and scalability of event-driven applications to achieve real-time processing capabilities and detect geographic events.

scholarly journals AN INSTANTANEOUS POINT SOURCE DETECTION AND EXTRACTION SYSTEM FOR GEO REMOTE SENSING SATELLITE

2018 ◽  
Vol XLII-3 ◽  
pp. 451-454
Author(s):  
Y. Guo ◽  
Q. Li ◽  
W. Wu
Keyword(s):  
Remote Sensing ◽  
Point Source ◽  
Real Time ◽  
Processing System ◽  
Image Data ◽  
Source Detection ◽  
Source Information ◽  
Real Time Processing ◽  
Time Processing ◽  
Instantaneous Point

To accomplish the task of detecting the instantaneous point source, an on-board information real-time processing system is designed which can process the point-source detection with reconfigurable function. The system has the algorithm reconfigurable function, which can detect and extract the instantaneous point source from the remote sensing image. By using FPGA programming, the satellite target detection and processing algorithm can be update easily. At the same time, the software can be reconfigured to improve the system's information processing capabilities. The system has been verified by simulating real instantaneous source point target image data to meet the real-time processing requirements of instantaneous point source information detection.

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