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Discover how to harness the capabilities of the Meta (Facebook) Prophet model to accurately predict temperature fluctuations using data collected from IoT sensors.

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Temperature Forecasting using IoT Data


Brief Description

This dataset contains the temperature readings from IOT devices installed outside and inside of an anonymous Room (say - admin room). The device was in the alpha testing phase. So, It was uninstalled or shut off several times during the entire reading period ( 28-07-2018 to 08-12-2018) which resulted in random interval recordings and few mis-readings (outliers)

Dataset Link: https://www.kaggle.com/datasets/atulanandjha/temperature-readings-iot-devices?resource=download


Variable Information

id : unique IDs for each reading

room_id/id : room id in which device was installed (inside and/or outside) -> currently 'admin room' only for example purpose.

noted_date : date and time of reading

temp : temperature readings

out/in : whether reading was taken from device installed inside or outside of room?


Some interesting questions to answer

  1. What was the max and min temperature?

  2. How outside temperature was related to inside temperature?

  3. What was the variance of temperature for inside and outside room temperature?

  4. Which was the hottest/coolest month?

  5. Can we use Time Series Forecast algo to predict the next scenario?

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Discover how to harness the capabilities of the Meta (Facebook) Prophet model to accurately predict temperature fluctuations using data collected from IoT sensors.

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