From the course: Leveraging AI and Data Engineering for Sustainable Solutions
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Using IoT for sustainability data collection in Google Colab
From the course: Leveraging AI and Data Engineering for Sustainable Solutions
Using IoT for sustainability data collection in Google Colab
- [Instructor] Now let's examine the IoT temperature data collected from various sensors. IoT temperature sensors train data from multiple rooms, capturing fluctuations over time. This steady flow of data enables us to detect environmental patterns and potential changes. Using Google Colab will load in the data set and review its structure, identifying the key data columns including timestamps, temperature, humidity, and CO2 levels. We are stimulating the IoT data to allow us to create a realistic data set representing various environmental conditions. This dataset will be used to understand patterns and anomalies in the local environment. With sensors collecting data across different locations, we can examine how temperature and air quality can vary. This helps us track and understand environmental changes. Visualizations such as line plots allow us to observe trends in temperature, humidity, and CO2 levels over time, highlighting any patterns or shifts.
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