Air Properties Time Series Dataset

1) Data Introduction

• The Air Properties Time Series Dataset is a tabular time series dataset collected for air conditioning (HVAC) environment monitoring. It includes key air quality indicators such as dew point temperature, temperature, humidity, air flow, and power consumption of supply and return air at each time interval.

2) Data Utilization

(1) Characteristics of the Air Properties Time Series Dataset: • By integrating real-time air quality, temperature and humidity, dew point, and other environmental indicators, this dataset is well-suited for practical applications such as industrial cleanroom environment control and facility management. (2) Applications of theAir Properties Time Series Dataset: • Development of AHU Operating Status Prediction Models: The dataset can be used to develop machine learning models that predict the operating status (ON/OFF) of air handling units (AHU) using various environmental variables and time information. • Air Conditioning Environment Monitoring and Anomaly Detection: By analyzing the time series patterns of key indicators such as temperature, humidity, and dew point, the dataset can be utilized for real-time environment monitoring and anomaly detection in air conditioning systems.