Suing's AI Technology Newly Added to MLIT's "Water and Sewerage DX Technology Catalog"
Suing Corporation announced that three of its DX-related technologies, including image recognition AI, have been newly added to the Ministry of Land, Infrastructure, Transport and Tourism's 'Water and Sewerage DX Technology Catalog'.
📋 Article Processing Timeline
- 📰 Published: April 10, 2026 at 02:29
- 🔍 Collected: April 10, 2026 at 09:01 (6h 31m after Published)
- 🤖 AI Analyzed: April 20, 2026 at 07:19 (238h 17m after Collected)
Suing Corporation (President: Masaki Yasuda, Headquarters: Minato-ku, Tokyo) announces that its self-developed DX-related technologies have been newly added to the 'Water and Sewerage DX Technology Catalog' published by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) on March 27, 2026.
This time, three technologies were selected for inclusion: Image Recognition AI, Cloud-based Remote Monitoring, and Anomaly/Predictive Detection of Operating Status.
Photo: Remote monitoring using 'Sustainable Water Cloud® (SWaC®)'
## Background
In the domestic water and sewerage industry, there is an increasing need to improve operational efficiency and sophistication utilizing digital technologies, driven by challenges such as aging facilities, a shortage of human resources for operation and maintenance, and the need to ensure stable business continuity even during disasters.
The 'Water and Sewerage DX Technology Catalog' formulated by the MLIT aims to organize and visualize advanced technologies that address these issues, serving as reference information for water and sewerage operators nationwide when considering technology implementation.
By combining our cultivated water treatment technologies with digital technologies, we are working to enhance the operation and management of water and sewerage facilities and improve business efficiency. This inclusion organizes and introduces our efforts as technologies that contribute to the promotion of DX. A total of five of our DX technologies are now listed in the 'Water and Sewerage DX Technology Catalog'.
## Introduction of Listed Technologies
Overview
1
[Practical Stage] Image Recognition AI Condition Monitoring System SaiIK®
This is a condition monitoring technology that quantifies visual judgments—such as water transparency, the state of cohesive flocs, dehydrated filtrate, and dehydration status—that have previously relied on human experience and intuition, utilizing deep learning to substitute and elevate them through AI. By installing devices equipped with cameras and image recognition AI in the facilities, the equipment status can be monitored 24 hours a day, 365 days a year.
This time, three technologies were selected for inclusion: Image Recognition AI, Cloud-based Remote Monitoring, and Anomaly/Predictive Detection of Operating Status.
Photo: Remote monitoring using 'Sustainable Water Cloud® (SWaC®)'
## Background
In the domestic water and sewerage industry, there is an increasing need to improve operational efficiency and sophistication utilizing digital technologies, driven by challenges such as aging facilities, a shortage of human resources for operation and maintenance, and the need to ensure stable business continuity even during disasters.
The 'Water and Sewerage DX Technology Catalog' formulated by the MLIT aims to organize and visualize advanced technologies that address these issues, serving as reference information for water and sewerage operators nationwide when considering technology implementation.
By combining our cultivated water treatment technologies with digital technologies, we are working to enhance the operation and management of water and sewerage facilities and improve business efficiency. This inclusion organizes and introduces our efforts as technologies that contribute to the promotion of DX. A total of five of our DX technologies are now listed in the 'Water and Sewerage DX Technology Catalog'.
## Introduction of Listed Technologies
Overview
1
[Practical Stage] Image Recognition AI Condition Monitoring System SaiIK®
This is a condition monitoring technology that quantifies visual judgments—such as water transparency, the state of cohesive flocs, dehydrated filtrate, and dehydration status—that have previously relied on human experience and intuition, utilizing deep learning to substitute and elevate them through AI. By installing devices equipped with cameras and image recognition AI in the facilities, the equipment status can be monitored 24 hours a day, 365 days a year.