---
title: "Room Occupancy Detection"
url: https://daily.dev/posts/room-occupancy-detection-jhojoim7c
source_url: https://heartbeat.comet.ml/room-occupancy-detection-ddb7a7025243
type: article
source: "HEARTBEAT"
published: 2024-02-07T11:54:44.690Z
updated: 2024-05-09T09:28:18.744Z
tags: ["data-science", "data-analysis", "classification", "data-visualization", "random-forest", "exploratory-data-analysis"]
reading_time: 7
upvotes: 5
comments: 0
language: en
---

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# Room Occupancy Detection

**[HEARTBEAT](https://daily.dev/sources/hrb)** · 7 min read · 5 upvotes · 0 comments

## Summary

This project aims to predict room occupancy based on sensor data. The dataset contains attributes such as date, temperature, humidity, light, CO2, humidity ratio, and occupancy. The exploratory data analysis shows correlations between temperature, light, CO2, and occupancy. The Random Forest Classifier is used as the final model with an accuracy score of 98%.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://heartbeat.comet.ml/room-occupancy-detection-ddb7a7025243>

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---

Tags: [#data-science](https://daily.dev/tags/data-science), [#data-analysis](https://daily.dev/tags/data-analysis), [#classification](https://daily.dev/tags/classification), [#data-visualization](https://daily.dev/tags/data-visualization), [#random-forest](https://daily.dev/tags/random-forest), [#exploratory-data-analysis](https://daily.dev/tags/exploratory-data-analysis)

[View this post on daily.dev](https://daily.dev/posts/room-occupancy-detection-jhojoim7c)