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  6. Case Study: Automation of Water Quality Testing Operations Using AI

Case Study: Automation of Water Quality Testing Operations Using AI

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last updated:Aug 05, 2022

Rist
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Introduction of a case that achieved accurate and stable automatic quality judgment regardless of the environment, weather, or differences between day and night at each site!

This is an introduction to the case of implementing an "AI Automatic Drainage Monitoring System" at the Kyocera Yasu Plant. In the company's wastewater treatment facilities, workers traditionally visited three scattered wastewater treatment facilities within the plant three times a day to visually check the status of wastewater treatment. Due to labor shortages and the need for improved operational efficiency, there was a demand for the development of a system that could automatically determine the status. After the introduction of the "AI Automatic Drainage Monitoring System," the time spent on visual inspection tasks was reduced, and the burden on workers was alleviated. The expected time-saving effect after implementing the system at the three wastewater treatment facilities is estimated to be 504 hours annually. [Case Overview (Excerpt)] ■ Challenges - The visual inspection of the wastewater treatment status at the facilities required a considerable amount of time, and improvements in operations were necessary due to labor shortages and efficiency concerns. - In outdoor wastewater treatment facilities, the appearance of the water surface varies depending on the time of day and weather conditions, making automatic status determination by the system technically challenging. *For more details, please refer to the PDF document or feel free to contact us.

    Drainage and ventilation equipmentSecurity cameras and surveillance systems
2021-09-30_15h34_57.png

Case Study: Automation of Water Quality Testing Operations Using AI

2021-09-30_15h34_57.png
2021-09-30_15h34_57.png
  • Related Link - https://www.rist.co.jp/service/airesearch/

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【Summary of Other Cases (Excerpt)】 ■Results - Achieved reduction in time for visual inspection tasks and alleviation of worker burden. - The expected time reduction effect after the system implementation at three wastewater treatment facilities is estimated to be 504 hours annually. - By installing dedicated lighting for the imaging environment and utilizing AI models optimized for each site, accurate and stable automatic quality judgment is achieved regardless of the environmental conditions, weather, or differences between day and night at each site. ■Development System - Development of an AI model that determines the quality of wastewater treatment based on images of the water surface in wastewater treatment facilities. - Development of an image processing algorithm to remove noise from images prior to quality judgment by the AI model. - Development of a system that issues alerts when the quality judgment results from the AI model indicate abnormalities. *For more details, please refer to the PDF document or feel free to contact us.

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[Case Study] Automation of Water Quality Testing Operations Using AI

[Case Study] Automation of Water Quality Testing Operations Using AI

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Rist

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Rist Inc. is a company that develops and provides solutions and products using AI technology, primarily focused on the manufacturing industry, under the mission of "Bringing brilliance to Japan's future with AI." We possess the technical expertise to address the unique challenges of the manufacturing industry and develop custom solutions tailored to our clients' needs, including appearance inspection systems utilizing Deep Learning, data analysis, and predictive models. By mastering new technologies such as Deep Learning, which are being researched worldwide, we continue to challenge ourselves to solve the issues faced by our clients and society through the systematization of tasks that have traditionally been performed by humans and the accumulation and analysis of know-how.

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