Eliminating Time Loss in 'Searching for Empty Seats': Senshu University and Shobunsha Holdings Begin Campus DX Demonstration Using 'Imakomi' Congestion Analysis AI

Shobunsha Holdings Co., Ltd. and Organon Inc., in collaboration with Senshu University, announced the commencement of a demonstration experiment on May 4, 2026, to verify the effectiveness of image recognition AI technology as a measure to alleviate congestion in university libraries resulting from recent changes in learning styles.

This experiment will run until March 2027, focusing on visualizing congestion status through camera installation and verifying the impact on student behavior based on quantitative data.

■ Background and Purpose

In recent years, as learning styles have diversified and library functions have advanced, student needs regarding library usage have become more varied. At the Senshu University Kanda Campus, facility constraints, such as the location of the Yasukuni-dori Branch (Knowledge Base) and elevator congestion when moving to upper floors, necessitate the effective and efficient utilization of library seats.

To address these issues, Senshu University and Shobunsha Holdings will conduct a joint demonstration experiment using the 'Imakomi' congestion analysis service provided by Shobunsha Holdings. Images captured by library cameras will be analyzed by AI to visualize congestion levels. The analysis will be handled by Organon, a co-developer of 'Imakomi'.

By installing small cameras and AI analysis devices in study areas, the project aims to provide real-time congestion information on the Senshu University library portal site. This will be used to verify whether it reduces unnecessary student movement and leads to distributed usage (behavioral change) during less crowded times and areas.

■ Overview of the Demonstration

1. Period: May 4, 2026 – March 31, 2027

2. Target Area: Senshu University Library Yasukuni-dori Branch (Knowledge Base), 14th Floor

3. Details:

・New camera installation and rental operation: Small cameras will be installed in the target area, connected to the 'Imakomi Edge' AI analysis device.

・Information disclosure: AI-analyzed real-time congestion data will be displayed on the 'Senshu University Library Portal'.

Leveraging knowledge in making space easy to understand through maps and guidebooks, the goal is to provide a UI that allows students to intuitively grasp availability from smartphones at a glance.

・Privacy Protection: Captured footage will be processed immediately within the device to mask individuals, ensuring operational privacy.

■ Verification Items and Data Usage

Using 'real-time congestion levels' and 'time-series logs' from AI analysis, the experiment will quantitatively evaluate the reduction in unsuccessful seat searches and the occurrence of utilization distribution (peak shifting).

Quantitative results from this experiment are planned for publication in a report from April 2027 onwards.

■ About 'Imakomi'

'Imakomi' is a congestion visualization tool that combines Shobunsha Holdings' expertise in map information with Organon's AI/image analysis technology. It is characterized by its ability to be introduced without large-scale construction by utilizing existing security cameras.