Industrial Problem Solution
Intelligent Underground Station Air-Conditioning System
2020-06-151. Company introduction
DAP Co., Ltd., a company specializing in artificial intelligence solutions based in Uiwang-si, Gyeonggi-do, founded in 2017. The goal is to solve public problems by reducing fine dust. There are smart air quality management system for underground stations, development of artificial intelligence measurement technology for fine dust/dissipation dust, and development of air purification system in the business area
2. Problem Background and Summary
In order to improve the deterioration of air quality in subway stations and inconvenience to subway users, DAP Co., Ltd. installed fine dust measuring devices in station to analyze the observed fine dust concentration data and to create an artificial intelligence model that automatically controls air conditioning facilities and fine dust reduction devices. To predict the concentration of fine dust in subway stations in an hour. Numericalize the actual effect of fine dust reduction devices installed in station
3. Solving Process
Present two methods of prediction using ARIMA model, a traditional method of analyzing time series data, to predict fine dust concentration, and by converting time series data into two-dimensional image data, using synthetic triple neural network (CNN)
To identify the effects of the reduction device, a comparative analysis with the concentration of fine dust in the atmosphere suggests a method to statistically quantify the actual effects of the reduction device.
4. Ripple effects and future plans
As a future task, we suggest ways to increase the accuracy of fine dust concentration levels by directly using the data inside the fine dust meter and introducing a new machine learning method that uses both the fine dust concentration data and the external atmospheric fine dust concentration data observed by the measuring instrument.
1. Company introduction
DAP Co., Ltd., a company specializing in artificial intelligence solutions based in Uiwang-si, Gyeonggi-do, founded in 2017. The goal is to solve public problems by reducing fine dust. There are smart air quality management system for underground stations, development of artificial intelligence measurement technology for fine dust/dissipation dust, and development of air purification system in the business area
2. Problem Background and Summary
In order to improve the deterioration of air quality in subway stations and inconvenience to subway users, DAP Co., Ltd. installed fine dust measuring devices in station to analyze the observed fine dust concentration data and to create an artificial intelligence model that automatically controls air conditioning facilities and fine dust reduction devices. To predict the concentration of fine dust in subway stations in an hour. Numericalize the actual effect of fine dust reduction devices installed in station
3. Solving Process
Present two methods of prediction using ARIMA model, a traditional method of analyzing time series data, to predict fine dust concentration, and by converting time series data into two-dimensional image data, using synthetic triple neural network (CNN)
To identify the effects of the reduction device, a comparative analysis with the concentration of fine dust in the atmosphere suggests a method to statistically quantify the actual effects of the reduction device.
4. Ripple effects and future plans
As a future task, we suggest ways to increase the accuracy of fine dust concentration levels by directly using the data inside the fine dust meter and introducing a new machine learning method that uses both the fine dust concentration data and the external atmospheric fine dust concentration data observed by the measuring instrument.