M3S - Current projects (partial list)
6G Visible
In this project, our aim is to find out how to combine the various sources of expanded traffic situation information and the most efficient data transfer methods as well as information processing to enable autonomous driving. Software, communication, and computing solutions are critical issues. We also want to find out how the solutions and software architecture can be tested in both virtual and real traffic situations.
Researchers focus on enhancing autonomous driving by traffic-related data outside the scope of a vehicle’s own sensors. Extended traffic situation information refers to information that is obtained from elsewhere and combined with the information produced by the car's own sensors. This refined information is used to assist the driver, remotely control public transport, and finally enable fully autonomous driving.
The research topic is the development of autonomous driving using our own wireless 5G/6G networks and distributed computing solutions as a basis for the collection of extensive situational information, data analysis and decision-making. The research and its results can be used especially in companies developing software in the automotive and transport equipment industry in the development of know-how and new business opportunities. As part of other 6G research made at the University of Oulu, this project offers a concrete, intelligent traffic use case for developing and testing software solutions and architectures.
MuFano (Multimodal Fusion based Anomaly Detection for Improving Microservice-based System)
Academy of Finland Consortium Project [Univ. of Oulu- Univ. of Helsinki] (01.09.2022 - 31.08.2026) 1.42M Budget
This project will advance anomaly detection of Microservices using Artificial Intelligence. The project is aimed at preventing the degradation of microservices anomalies both at runtime and design time.
First, we produce a novel and replicable benchmark data set from an open-source project comprising multiple modalities (execution logs, service calls, and performance metrics) with software testing techniques. Second, we advance architectural reconstruction techniques, both statically and dynamically, with the goal of reconstructing the actual architecture of the systems.
Then, at the University of Oulu, we will investigate architectural degradation techniques, investigating possible anti-patterns and metric degradation using temporal graph analysis techniques. The University of Helsinki will concentrate on performance anomaly detection. We will connect both our techniques back to software architecture, development (Dev), and operations (Ops) and provide countermeasures.
The scientific impact is in two areas. First, we develop AI models for software behavior analysis that aim to go beyond the current state of the art. Second, we link our AI models to software development and operations work and develop a novel tool LogViz that shows interactive visualizations and helps anomaly resolution.
6GSoft (6G software for extremely distributed and heterogeneous massive networks of connected devices )
Business Finland (03/2023-02-2026) 2.1M
Developing and managing 5G and especially 6G software will demand totally new software development methods, tools, processes, and architectures. We need novel industry-scale software engineering to support the integrated development of heterogeneous systems, including software platforms, cloud, big data, AI, edge, IoT, and quantum computing. The number of connected devices will explode, and they all have software. They range from micro-level devices with very limited processing capability to larger connected devices with strong processing power and large applications in the cloud.
Current architectures, orchestration, and scalability methods and tools cannot support such complex, heterogeneous, and highly distributed 6G software systems. In addition, the application of current technologies will create a very high energy overhead due to the lack of optimization for such a large number of connected devices.
The 6GSoft project aims to achieve four main goals:
1) Development of 6G-era sustainable software development methods, processes, and tools.
2) Development of Energy-Aware 6G orchestration and scalability models and tools.
3) architectural support for 6G software.
4) Business-driven 6G software development models
The consortium is composed of four Finnish Universities (University of Oulu, LUT University, University of Jyväskylä, and Tampere University) and four Finnish Companies (Ericsson Oy, Bittium Wireless Oy, Aidon Oy, and Wirepas Oy), covering a wide set of topics regarding software research.
Full Bachelor's programme in Software Engineering in Nanjing, China
M3S unit has prepared a Bachelor's Programme in Software Engineering in China in collaboration with Nanjing Institute of Technology (NJIT). It will be a double degree programme in the Degree Programme of Information Processing Science. Annually NJIT will recruit 100 students to study in Nanjing, China.
This education export project is the biggest such project in the university so far. It is also one of the biggest among all externally funded projects in the university.
Nordic Health Data Spaces
Nordic Health Data Spaces project examines how upcoming European Health Data Space can facilitate cross-border healthcare, and how the Aurora region (northern regions of Finland, Sweden, and Norway) can be prepared. The project is funded by Interreg Aurora and is a collaboration coordinated by University of Oulu together with NTNU Norway, University of Umeå, and Norwegian Centre for E-health Research.
More information from project manager Prabhat Ram, prabhat.ram(at)oulu.fi
Reboot Skills
Reboot Skills creates an European training program on advanced digital skills targeted for the manufacturing industry. The project provides a set of courses increasing the capacity of European countries to advance digitalization of the manufacturing industry and especially SME companies. The courses range from AI to Robotics, and IoT to Cybersecurity.
The project is a collaboration coordinated by University of Oulu with University of Limerick, Skillnet Ireland, MADE Competence Center in Italy, KU Leuven, Flanders Make, University of Luleå, and DIMECC.
More information from project manager Anna Sachinopoulou, anna.sachinopoulou(at)oulu.fi
NLP-TD – Detecting Technical Debt with Natural Language Processing – Academy of Finland
We think that by analyzing millions of source code files, we can capture the collective mind of software developers. Software developers’ thoughts can be analyzed from the natural language comments that provide opinions about source code. This project focuses on thoughts about technical debt in the source code.
Technical debt utilizes the concept of financial debt to illustrate the technical problems that result in unnecessary increases in software development costs. Gartner has evaluated that the cost of technical debt can be several hundred millions of dollars to the software industry. Currently, thousands of open source projects enable large-scale probabilistic reasoning on human thoughts about source code.
We’re building a Natural Language Processing (NLP) based technical debt detector. Our work is a part of a greater path that is on making computers understand source code as humans understand it.
CRITICAL – Technological and Societal Innovations to Cultivate Critical Reading in the Internet Era – Academy of Finland
One of the main challenges of our times is the spread of misinformation and disinformation on the Internet. The exposure to false information, in conjunction with poor critical reading skills, may endanger citizen’s decision-making on important issues.
The CRITICAL project aims to develop technological and societal innovations to support adolescents (aged 10–17) critical reading skills required in the Internet era. The project increases understanding of development of critical reading skills and factors affecting development of these skills. We are developing a Critical Reading Lab service that includes critical reading assessments and games, teacher training materials, and a system for crowdsourcing game content. We’ll apply adaptive teachable agent games to enhance critical reading skills and examine cognitive, motivational, and emotional aspects of learning.
This project aspires to have a wide impact on preparing adolescents to deal with misinformation and disinformation.
Oxilate – Operational eXcellence by Integrating Learned information into AcTionable Expertise
Most societal and industrial innovations have become reliant on the deployment of software-intensive high-tech system technologies in one form or another. The challenge for the European high-tech systems industry is to accommodate these technologies to pursue a position as world-leader in their respective markets.
In that process, industry is increasingly confronted with a need to reposition itself in its value chain. Whereas the traditional product manufacturing model is steadily becoming obsolete, the emphasis rapidly shifts to providing total end-user solutions. This requires high-tech systems companies to address an emerging role as both system integrator and service provider of smart systems and solutions that flawlessly can be integrated and serviced in the ever-changing customers’ operating environment.
This challenge is taken up by the Oxilate project, which focuses on providing support for systems fully integrated in the customer’s operational workflow. This is done by development and integration of actionable data analytics with expert knowledge into widely available support and (independent) tools for professionals, creating direct business value in the product life-cycle they serve.
Visdom
Visualisation is a powerful method for communication, especially in cross-disciplinary communication with various stakeholders, as in operations. Many software development tools already provide some visualisations, but integrated views that combine data from several sources are still at research prototype level.
The Visdom ITEA3 project will develop new types of visualisations that utilise and merge data from several data sources in modern DevOps development. The aim is to provide simple ‘health check’ visualisations about the state of the development process, software, and use. Visdom is an ITEA3 project funded by Business Finland.
SMAD
SMAD was a research project which studies different aspects of autonomous driving. As its official Finnish name states, it aimed to create ‘an intelligent, moving autonomous test environment’. The test environment consisted of two identical Toyota Rav4 SUVs and a trailer, complemented with a broad palette of different sensors and research equipment of the members of the research consortium.
SMAD covered the automotive and vehicle research done in the university of Oulu in a broad manner – six research teams from ITEE and two teams from the Faculty of Technology built the project consortium. The project is ranked under the 6G Flagship program umbrella and co-operation and information sharing is done with other activities of 6G Flagship.
SMAD had a duration from late 2018 to the end of March 2021. It was funded mainly by the European Regional Development Fund.
More Stamina
More Stamina is a Business Finland funded Research to Business project, which explores the potential of an eHealth app for people with Multiple Sclerosis. The project is a collaboration with the Faculty of Medicine. The project will develop and study a digital health solution for persons with Multiple Sclerosis to help them better manage their fatigue and other MS-related symptoms.
WWData
The aim of WWData project is to help wastewater network management, by developing tools and methods for handling data in a safe way in e.g. cloud services. The most critical parameters are identified and the frequency of the measurements is evaluated against the needs for measurements in the networks.
Project scope includes the parameters outside of the networks that could be utilized in the management process. The project also aims to develop new tools and methods for analysis and handling data for observing the slow, long term changes in the processes. Using these methods predictability will increase, making it easier to identify deviations in the networks.
The project is funded by the European Regional Development Fund.
Reboot IoT Factory
Reboot IoT Factory brings together service and solution providers, industrial leaders and top research organizations to improve the competitiveness of the Finnish manufacturing industry through digitalization.
The Reboot operative model is based on agile co-creation and experience sharing within real-world production environments. Each forerunner factory commits as a research and development platform for proof-of-concept experiments, which combine technology research and factory digitalization needs.
The project is funded by Business Finland.
Smart Mask
Smart Mask project defines a groundbreaking new digitized reusable mask to protect against the coronavirus with interchangeable filters, wireless upgradeable sensing service with health cloud analytics. Project utilizes new and smart materials to provide improved protection as well as comfortable use. Mask’s integrated and replaceable sensors measure biosignals of the user and environmental variables. One of the most important measurements are related to safe use of the mask, such as the air tightness of the mask and air filter quality. Sensor model can be changed in the mask according to the needs of the user.
Collected data is stored in a distributed IoT platform, where analysis is performed in real-time with the help of advanced AI algorithms (e.g. data mining, machine learning). Based on the analysis results, real-time alerts, recommendations and long-term personal health data can be offered to users. The data can be visualized in an easily understandable manner with a mobile application.
The first phase of the project aims at proof-of-concept that will be further developed in the following project. The results of the project will help to mitigate the Covid-19 epidemic as well as other infections that spread through respiratory droplets. In addition, the results advance the utilization of health data and development of new applications and services.
In the first phase of the project participating organizations are University of Oulu and Oulu University of Applied Science. Project is funded by Business Finland.
CHAMELEONS
CHAMELEONS is a H2020 funded project to develop new and innovative educational interventions to improve the learning experience offered by higher education with the intention of shaping more adaptable, entrepreneurial, and employable graduates, ready to meet the challenges of the future. The consortium is led by University College Dublin.
M3S leads a work package focusing on designing the educational modules with stakeholders.