IVIS: Highly customizable framework for visualization and processing of IoT data

Bulej, Lubomír; Bureš, Tomáš; Hnětynka, Petr; Camra, Vaclav; Siegl, Petr; Töpfer, Michal

doi:10.1109/seaa51224.2020.00095

Cited by 5 publications

(8 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This agent software has been installed on all the sixteen edge boards. We created a plugin for sending data to IVIS [10], this platform plays the role of the aforementioned storage server and graphical user interface. The plugin is based on a Telegraf Json serializer so it is consistent with the Telegraf architecture and provides the serialization of data into a JSON payload which is compatible with IVIS.…”

Section: Runtime Monitoringmentioning

confidence: 99%

“…The QRML toolset offers language support, visualizations, documentation generation, templatecode generation, and constraint-solving support that helps to design and develop new Cyber-physical complex systems. In addition, a monitoring system has been designed using the open-source data visualization and processing framework called IVIS by L. Bulej et al [10] in order to provide a performance visualization of the previously mentioned device.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Computer Vision on the Edge to Reduce Network Bandwidth Consumption and Computing Resources in Multi-view 3D Industrial Inspection without Hidden Surfaces

Escrivá

Ruiz

Carbó

et al. 2023

J Sign Process Syst

View full text Add to dashboard Cite

Industrial inspection industry requires high precision, fast and reliable systems, where images play a central role. These systems are composed by several hardware and also cyber-physical componentes where complexity increases when multiple heterogeneous sensor inputs are combined. Our 3D industrial inspection scanner is able to reconstruct complete objects without occlusion with use of multiple sensors and actuators using a complex software architecture. Our system allows increasing the throughput by removing the bottleneck network issue, decreasing network data transfer using a new edge systems architecture that segments and optimizes image transferring. Also, this work presents the results of applying technology developed during the FitOptiVis European ECSEL project. FitOptiVis will provide a reference architecture supporting composability built on suitable component abstractions and embedded sensing, actuation and processing devices adhering to those abstractions. The reference architecture will support design portability, on-line multi-objective quality and resource management and run-time adaptation guaranteeing system constraints and requirements based on platform virtualization. The FitOptiVis project will be applied to design the new architecture of the new edge components and develop the runtime system monitoring.

show abstract

Section: Runtime Monitoringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computer Vision on the Edge to Reduce Network Bandwidth Consumption and Computing Resources in Multi-view 3D Industrial Inspection without Hidden Surfaces

Escrivá

Ruiz

Carbó

et al. 2023

J Sign Process Syst

View full text Add to dashboard Cite

show abstract

“…While touch, click, and other interaction methods are widely used on IVIS [3,4], recent advancements in artificial intelligence technology have led to the emergence of new interaction methods, such as voice input and in-air gesture recognition [5]. These methods that use biometric information can greatly improve cybersecurity in interaction.…”

Section: Introductionmentioning

confidence: 99%

“…These methods that use biometric information can greatly improve cybersecurity in interaction. In particular, in-air gesture recognition allows drivers to perform customized gestures within the recognition area of a sensor, such as a camera or a sensor, which can then provide personalized feedback through the IVIS system [4]. As users do not need to look at the screen when making gestures, we believe that in-air gesture recognition has the potential to reduce driver distraction and improve driving safety compared to touch interactions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of In-Air Gestures on In-Car Task’s Diver Distraction

et al. 2023

View full text Add to dashboard Cite

As in-vehicle information systems (IVIS) grow increasingly complex, the demand for innovative artificial intelligence-based interaction methods that enhance cybersecurity becomes more crucial. In-air gestures offer a promising solution due to their intuitiveness and individual uniqueness, potentially improving security in human–computer interactions. However, the impact of in-air gestures on driver distraction during in-vehicle tasks and the scarcity of skeleton-based in-air gesture recognition methods in IVIS remain largely unexplored. To address these challenges, we developed a skeleton-based framework specifically tailored for IVIS that recognizes in-air gestures, classifying them as static or dynamic. Our gesture model, tested on the large-scale AUTSL dataset, demonstrates accuracy comparable to state-of-the-art methods and increased efficiency on mobile devices. In comparative experiments between in-air gestures and touch interactions within a driving simulation environment, we established an evaluation system to assess the driver’s attention level during driving. Our findings indicate that in-air gestures provide a more efficient and less distracting interaction solution for IVIS in multi-goal driving environments, significantly improving driving performance by 65%. The proposed framework can serve as a valuable tool for designing future in-air gesture-based interfaces for IVIS, contributing to enhanced cybersecurity.

show abstract