This is a repository for data for the publication: Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models. Luis M. Candanedo, Véronique Feldheim. Energy and Buildings. Volume 112, 15 January 2016, Pages 28-39.

Souce code of "Inter-seasons and Inter-households Domain Adaptation Based on DANNs and Pseudo Labeling for Non-Intrusive Occupancy Detection" (JSAI Journal) + "Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains"(https://arxiv.org/abs/2412.04682).

At AI4Casting Hub, we leverage data from Public Health Ontario's Ontario Respiratory Virus Tool, which monitors hospital bed occupancy and other virus detections. This data provides crucial insights that we use to forecast the healthcare system's burden during disease outbreaks, enabling more effective planning and response.

Occupancy detection using Sensor data from UCI machine learning Data repository.

No description available

Code used for unsupervised occupancy detection based on smart water and electricity meter data

Rossman R., Yackulic C., Saunders S.P., Reid J., Davis R., and Zipkin E.F. 2016. Dynamic N-occupancy models: estimating demographic rates and local abundances from detection-nondetection data. Ecology. 97: 3300-3307.

1DConvNet applied to room occupancy detection based on data from several environment sensors. Data courtesy of the UCI Machine Learning Repository.

This repository provides source code and data used for the paper "Overcoming Data Scarcity through Transfer Learning in CO2-based Building Occupancy Detection".

No description available

Occupancy Detection Data Set

The aim of this project is to prepare the dataset in order to solve several tasks including applying basic & advanced classification models, Time Series Analysis and Forecasting/Classification, Sequential Pattern Mining, Outlier Detection and Explainability

No description available

Occupancy detection of an office room based on sensors data.

Evaluation of Machine Learning Models with Yellowbrick

Binary classification upon room occupancy detection based on the environmental conditions (sensor data)

Data and code for "Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models", Sollmann, R., Peer Community Journal (submitted)

CO₂-driven occupancy detection & energy-IAQ optimization in offices. Uses EDA, clustering (K-Means/DBSCAN), and predictive models (SARIMAX MSE=0.72) to cut HVAC peaks (65% at 10AM-4PM, r=0.78) and enable DCV (35% savings). Repo: cleaned data, code, visualizations. Apps: ASHRAE compliance, adaptive controls. Future: IoT/edge-AI integration.

It is a Collection of python notebook from a group project in data mining esplorino Advanced techniques such as classification, neural network, clustering, regressors, forecasting and more.

Praktikum penambangan data chapter 1, temperature, humidity, etc A dataset for predicting room occupancy using environmental factors

The dataset consists of experimental data used for a binary classification task to determine room occupancy based on features such as temperature, humidity, light, and CO₂ levels. Ground-truth occupancy labels were established using time-stamped images captured at one-minute intervals. From UCI Repository, Creators Luis Candanedo.

This is a repository for data for the publication: Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models. Luis M. Candanedo, Véronique Feldheim. Energy and Buildings.

No description available

Find the occupancy of room using random forest classifier.

Occupancy Detection Dataset

No description available

No description available

Advanced Analytics to Detect House Occupancy

Projeto da matéria de Mineração de dados utilizando a base de dados Occupancy_Detection_Data_Set

Python dili ile yazılmıştır.