A python 3 package to retrieve ambient air monitoring data from the United States Environmental Protection Agency’s (US EPA) Air Quality System (AQS) Data Mart API v2 interface - USEPA/pyaqsapi
The M5Stack ATOM collects the air-quality using two sensors. The BME680 is connected via I2C and the PMSA003A uses the serial interface (UART1). Therefore, you need to connect the sensors to the M5Stack as described in the following tables. If you want to change the pin settings,...
Automation of the dashboard to display live air quality data using the auto-refresh feature in Streamlit, as well as GitHub Actions to run main.py python file every hour and commit new copy of db to repository Accessing a live API using control flow knowledge (i.e. loops, list comprehensio...
Load the air quality dataThe Flask app needs to call the API to load the data for the visible portion of a map.Open the app.py file. Add the following code to the bottom of the file: Python Copy def get_color(aqi): # Convert the AQI value to a color. if aqi <= 50: ret...
Goal: Unlimited debugger for an air quality monitoring platform and dynamic encryption and decryption of request data and return data Home:aHR0cHM6Ly93d3cuYXFpc3R1ZHkuY24v Interface:aHR0cHM6Ly93d3cuYXFpc3R1ZHkuY24vYXBpbmV3L2FxaXN0dWR5YXBpLnBocA== ...
AQI-CN data.current.pollution.aqicn integer Air Quality Index (CN) Main Pollutant - CN data.current.pollution.maincn string Main pollutant (CN), for example PM10 Timestamp data.current.weather.ts string Timestamp of the results. Temperature data.current.weather.tp integer Temperature, ...
DatabricksRunNowOperator 需要现有的 Azure Databricks 作业,并使用 POST /api/2.1/jobs/run-now API 请求来触发运行。 Databricks 建议使用 DatabricksRunNowOperator,因为它可以减少作业定义的重复,而且使用此运算符触发的作业运行可以在作业UI 中找到。 DatabricksSubmitRunOperator 不需要 Azure Databricks 中存在某个作...
2). We used the “patatmo” (https://nobodyinperson.gitlab.io/python3-patatmo/index.html, accessed in January 2023) Python module to access the Netatmo Weather API. Data are available at the 10-min temporal resolution, and we retrieved hourly averages. Given that citizens operate the ...
Addressing the constraints inherent in traditional primary Air Quality Index (AQI) forecasting models and the shortcomings in the exploitation of meteorological data, this research introduces a novel air quality prediction methodology leveraging machine learning and the enhanced modeling of secondary data. ...
In our simulation, we ran the proposed model on TensorFlow 2.2.0 [25] API under python 3.5 [26]. With Keras library [27], we evaluated our proposed DQN performance in terms of two perspectives: (1) navigation mapping of proposed DUPT, and (2) mobility (i.e., UAV coverage, traveling...