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Category "Big Data"

Unlock your data’s full potential

Aviation, Big Data, Graph Visualisation, Machine Learning, Visual Analytics, Visualisation

Do you think data analysis is extraordinarily complex? Is significant training and experience the only way to understand vast amounts of data? Whilst it was once the case, now with the right software, that is just not true. gluoNNet develops data analysis and data-visualisation solutions that unlock your data’s hidden value. Our sophisticated algorithms do the heavy lifting for you, and then our visualisations provide the clarity to make informed decisions. 

Our solutions provide you with a concise summary of all your data, laying bare all the intricacies and nuances by highlighting all the important relationships, bottlenecks, and other strategic insights. With this ‘x-ray vision’ for data, you can enhance your decision-making process, making your organisation more efficient and effective. 

Our modular UI (user interface), is simple to tailor to your needs, allowing an intuitive and clear overview of your organisation with the flexibility to put any aspect of the data under the microscope. The UI displays this data in the most user-friendly way, whether that is with a diagram, map, cluster/galaxy, gauge, bespoke method, or even a simple table — ensuring you can always see your data clearly. With a few clicks, the user can easily filter from large amounts of data to just show anomalies. Workforce optimisation is easy, with flexible views allowing for individual or role-based customisation focusing on relevant data and also restricting access to sensitive data to only those who require it. Each user can easily drag and rearrange the visualisations in a view, to produce a layout that suits them, saving it for later use and sharing with other users.

 

All gluoNNet UI solutions can be customised in a simple and dynamic way.

Our algorithms allow real-time or near real-time processing, no matter if the data is coming from scientific, industrial, financial, infrastructure, or other contexts. Our software can combine many input sources, and is compatible with the cloud, on-premise and disconnected networks. It also tracks and highlights any changes of interest, subject to your criteria, by providing custom alerts. This allows you to stop labour-intensive monitoring and relax, knowing the software will highlight important information. If our algorithms identify urgent alerts, you can receive an immediate notification, allowing you to tackle critical issues without delay. Our product allows for automated or user-controlled dossier and report creation to allow specific alerts or custom analysis to be circulated to a wider audience.

We have applied this innovative approach on aviation data, resulting in a first-of-its-kind digital regulation system for the aviation industry. The aim of this innovative system is to allow better management of aviation-related issues that require regulatory oversight, quickly verifying information, speeding up approval procedures, and stopping actions that are illegal or deceptive.  

 

Click on the images in the gallery to see them in full size.

Another use case we are working on is to better identify and maximise materiality when applied to ESG (Environmental, Social, and Governance) metrics. The user can run diagnostics on current internal processes, and identify gaps or missing areas, articulated and measured within a live dynamic decision-making environment. Regularly ingesting data and processing real-time financial information to continuously update a materiality framework. This allows the user to look at trends over time, discerning what is driving the market, and eventually positioning the company as a global citizen within the ESG future state.

For more information on our data analysis and data visualisation solutions, please contact Michael Denyer or info@gluonnet.com.


Date: Sep 17, 2021
AUTHOR: Hans Baechle

Lunara Nurgaliyeva from Kazakhstan joins CERN openlab’s Summer Student Programme, investigating particle-tracking algorithms applied to aviation logistics

Aviation, Big Data, Machine Learning, Quantum Computing

This summer, gluoNNet’s collaborative research project with CERN openlab in the field of quantum computing is reinforced by Kazakh student Lunara Nurgaliyeva. The 22-year-old computer science and mathematics student from Nazarbayev University in Nur-Sultan participates in the CERN openlab Summer Student Programme 2021.

CERN openlab is a public-private partnership run by the European Organization for Nuclear Research (CERN) that accelerates the development of cutting-edge ICT solutions for the worldwide LHC community and wider scientific research. Through CERN openlab, CERN collaborates with research institutes and ICT companies, gluoNNet being one of them.

Due to the pandemic, the upcoming CERN openlab Summer Student Programme takes place online, with the selected students participating remotely from their homes across the globe. Over nine weeks (June-August 2021), Nurgaliyeva and her fellow students work via remote connection with some of the latest hardware and software technologies and learn how advanced ICT solutions are used in high-energy physics and beyond. Furthermore, Nurgaliyeva and her fellow students attend a series of online lectures and training sessions prepared by ICT experts at CERN. Special virtual lab visits are also part of the internship. Furthermore, the summer students can participate in a hackathon — the CERN Webfest on 21-22 August 2021 with gluoNNet as a co-organiser — and other exciting events.

Through the joint project on quantum graph neural networks, involving CERN openlab, the Middle East Technical University (METU), and gluoNNet, Nurgaliyeva investigates the application of particle-tracking algorithms for logistical challenges in aviation. Previously, researchers in the collaboration have identified several algorithms that might be interesting for aviation logistics. Using methods in machine learning and artificial intelligence, Nurgaliyeva examines these algorithms, aiming to create sustainable solutions for the aviation industry. Optimising environmental impact is one of the key goals of this exercise.  

“I am interested in the evaluation of the suitability of different machine learning and artificial intelligence methods, finding new ways of application in order to solve problems in industry or academia,” says Nurgaliyeva. “I am so excited to work on my project with my supervisors.”

The “Sunflower” project is one potential use case for the research project’s findings. This novel software solution designed for the civil aviation industry is co-developed by gluoNNet, BussinessOptix, and the Civil Aviation Administration of Kazakhstan (CAAKZ). It allows better management of aviation-related issues that require regulatory oversight, such as quickly verifying information, speeding up approval procedures, and stopping actions that are illegal or deceptive. 


Date: Jul 21, 2021
AUTHOR: Hans Baechle

Aviation-regulation project ‘Sunflower’ finishes phase 2, achieving major milestones

Aviation, Big Data, Machine Learning, Visualisation

The Sunflower project finished its second phase successfully, reaching major milestones in the course of the project’s overall development. Project Sunflower is an international collaboration of the Aviation Administration of Kazakhstan (CAAKZ), BusinessOptix, and gluoNNet. Together they are developing a first-of-its-kind digital regulation system for the aviation industry. The aim of this innovative system is to allow better management of aviation-related issues that require regulatory oversight, such as quickly verifying information, speeding up approval procedures, and stopping actions that are illegal or deceptive.

In the course of the now-finished second phase, the developers were able to successfully test new features. The new features will increase the software’s user-friendliness and information output. Among other things, the ability to create a flight dossier was added to the programme. Furthermore,  improvements to the UI (user interface) were made and successfully demonstrated. As a next step, these improvements will be fully integrated. Other features such as 3D views, an integrated weather pane were designed and tested. Additionally, database and data-visualisation mechanisms were improved.

Furthermore, gluoNNet transferred the Sunflower contract from its UK branch to its Swiss business entity. “Transcribing the Sunflower project from our UK subsidiary to our Swiss entity gives us more flexibility in terms of international cooperation regarding the Sunflower project,” says Daniel Dobos, gluoNNet CEO.

A detailed video presentation of the ‘Sunflower’ project can be found here.


Date: Jun 17, 2021
AUTHOR: Hans Baechle

Let’s play!

Big Data, Machine Learning, Quantum Computing,

Quantum computing offers solutions to deal with very large data sets by applying nature’s
laws to programming. Games are a playful way to enthuse especially young students to tackle
tomorrow’s problems as results can be seen quickly. The game “Battleships with partial NOT
gates” teaches principles of quantum mechanics and “Nine Quantum’s Morris” – the quantum
computing version of the board game “Nine Men’s Morris” – introduces the programmer to
tensor and graph neural networks, which are used in particle physics, for example particle track
reconstruction.READ MORE


Date: Feb 13, 2021
AUTHOR: Kristiane Novotny

PRESS RELEASE: The Aviation Administration of Kazakhstan (CAAKZ), BusinessOptix, and gluoNNet launch seminal aviation-tracking application called ‘Sunflower’

Aviation, Big Data, Press release, Visualisation

In collaboration with the Aviation Administration of Kazakhstan (CAAKZ) and BusinessOptix, gluoNNet is developing a first-of-its-kind digital regulation system for the aviation industry. The aim of this innovative system called ‘Sunflower’ is to allow better management of aviation-related issues that require regulatory oversight, such as quickly verifying information, speeding up approval procedures, and stopping actions that are illegal or deceptive. An international and multidisciplinary team of experts conceptualised the system, taking best practices, risk management, and operational data into account. Using cutting-edge data-analysis methods, ‘Sunflower’ delivers the CAAKZ information about an aircraft’s position, flight task, and charterer. Altogether, the ‘Sunflower’ regulation system will help the Kazakh aviation authorities in monitoring aircraft and national airspace, investigating incidents, and preventing illegal activities, eventually making aviation safer and more transparent. 

At gluoNNet, data scientists and software engineers develop the aviation-tracking application up from scratch, including user interface, algorithms, satellite data decoding, and data visualisation. The integrated data-analysis technology, which is based on the latest insights from large-scale particle-physics research, constitutes the backbone of the new regulation system; it allows the processing, contextual analysis, and visualisation of vast amounts of aviation data. As proof of concept, the software processed 4 billion sets of civil aircraft location-data per month that were recorded via satellites in April 2019. Working closely with CAAKZ analysts, gluoNNet tailored the software to their needs in terms of interactivity, customizability, and standalone usage.

In addition, BusinessOptix is creating a digital twin of the in Kazakhstan registered aircraft on their risk and performance management-platform, which will be implemented into the ‘Sunflower’ application in the following months.

 

 

gluoNNet is looking forward to continuing the fruitful collaboration and its efforts to develop and enhance the project even further.

 

Please find the Aviation Administration of Kazakhstan’s press release here.

For a PDF version of this text, click here.

 


Date: Feb 8, 2021
AUTHOR: Hans Baechle