Projects for Software Development Arena（AY2022）

In the Software Development Arena, students take the initiative in solving social problems.

01． Smart Museum

Contact

• YOSHIOKA Rentaro

Mission

• Role : Improve visitor experience at the Fukushima Museum
• Target : Visitor support and exhibition design
• Value : Improve visitor learning and knowledge acquisition

Purpose

• Currently, it is difficult to obtain objective data on visitor's behavior in viewing the exhibits that is necessary for evaluation/improvement
• Also, it is currently difficult to understand the visitor's learning experience so as to provide necessary support
• To improve the situation, it is desired to be able to objectively grasp visitor's behavior within the exhibit hall
• Furthermore, it is required to collect visitor's learning experience without hindering their experiences
• Therefore, a system that objectively measures visitor behavior and supports curators for analysis and interpretation will be developed

Goal

• Visitor's satisfaction in terms of learning improves.

Scenario

• Realize objective thorough measurement of visitor behavior
• Develop devices/applications for visitors that encourages/induces appreciation of exhibits
• Develop advanced computational methods to analyze and visualize visitor behavior
• Develop a system for curators that encourages analyzing and interpreting the measured/computed visitor behavior
• Develop a system to assist curators in designing exhibitions based on the analysis and interpretation

Keywords

• Knowledge experience, activity sensing devices, image recognition, data visualization, data analysis, human-computer-interaction, human-computer-collaboration

Research Database

02． High-speed autonomous driving on low-friction road surfaces

Contact

• OKUYAMA Yuichi

Mission

• Role : Improve availability of autonomous driving on low-friction surfaces
• Target : Modeling methods for automotive driving environments and automated learning mechanisms for driving
• Value : Acquisition of automated driving algorithms on low-friction surfaces

Purpose

• Currently, automated driving on low-friction surfaces is difficult
• Driving on low-friction surfaces is different from normal driving
• Development on real vehicles is difficult due to cost and environmental reproducibility
• Using radio-controlled drifting cars that simulate driving on low-friction surfaces
• Obtaining driving data and development of automated driving in small-size cars or simulator are desired
• Development of a simulator for racetracks that mimic low-friction surfaces and radio-controlled drifting cars

Goal

• Realization of automated driving of drifting radio-controlled cars on real-tracks

Scenario

• Development of a simple 3D modeling method for radio-controlled circuits
• Development of a simulator that simulates the physical behavior of a drift RC car
• Development of a system to automatically learn to drive on the simulator
• Development of a system to absorb differences between simulator and real world observations and driving

Keywords

• 3D modeling, artificial intelligence, reinforcement learning, sim2real, autonomous driving, drifting/sliding

Research Database

03． Smart Learning

Contact

• WATANOBE Yutaka

Mission

• Role : Reduce educational disparities in accordance with SDGs 4 (Quality Education for All)
• Target : Learning support and educational support in the educational field
• Value : Visualization to motivate learning, explanation methods to facilitate understanding, user interfaces and machine learning models for autonomous learning environments

Purpose

• There are educational disparities in education, especially ICT education, due to regional, school, and economic conditions
• Currently, business and educational methods related to enriching content, training systems, and competitive/gaming elements are the mainstream
• However, for skills exercises such as programming, for example, easy-to-understand explanations and feedback are necessary, but a lack of instructors is becoming a problem
• Therefore, we will develop a smart learning environment and its subsystems to support learners' self-directed learning

Goal

• Improving learner motivation or self-directed learning efficiency

Scenario

• Development of visualization methods to view and manage the state of the learner
• Development of representation techniques to explain and execute algorithms and procedures
• Development of user interfaces that can adapt to the learner's situation
• Development of machine learning models to support autonomous learning
• Development of data mining and data analysis methods for learning data

Keywords

• Educational technologies, visualization, educational data mining, adaptive learning, autonomous learning, programming, user interface/experience, artificial intelligence

Research Database

04． Smart Information Visualization

Contact

• TAKAHASHI Shigeo

Mission

• Role : Enhanced readability in abstract data visualization
• Target : Visual metaphor design for interactive visual data analysis
• Value :Egocentric visual data analysis with Human-in-the-Loop

Purpose

• The amount of available data continues to grow regardless of its type
• The demand for extracting important features from such large-scale complicated data also increases
• This leads to the need of developing egocentric visualization of such extracted data for individual analysts
• We tackle this challenge by implementing an interactive system for information visualization
• We also design new visual metaphors to improve the readability of the data

Goal

• Help analysts understand the data according to individual requirements interactively through visualization

Scenario

• Prepare the data structure of networks having vertices with multivariate vectors and edges connecting them
• Find 2D optimal layouts of the networks by referring to inherent relationships and similarities among vertices
• Transform the networks into visual metaphors by successively deleting minor edges according to their importance
• Transform the network into visual metaphors by extracting the major connectivity among vertices
• Visualize the networks from their global structures to local features via visual metaphors by continuously controlling the connectivity among vertices

Keywords

• Network visualization, network drawing, visual metaphor design, interactive visualization

Research Database