Smart home environment data across 4 European countries

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-05-09 DOI:10.1016/j.dib.2025.111636

Stefan Winterberger, Dmitriy An, Martin Biallas, Andrew Paice

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引用次数: 0

Abstract

This paper describes a dataset of anonymised smart home environment data that was collected during a project over 359 days (16.05.2023-08.05.2024). The dataset contains information about temperature (°C), humidity (%), ambient light (lux), CO₂ (ppm), VOC (ppm), sound pressure level (dB) in a time interval of 2–5 min in addition to event based data from PIR-Sensors and door contact sensors. Additionally, time and location information for each data point is available in the form of a time stamp, the user ID, the room and the country. The dataset was collected in 4 different European countries from a total of 62 users at their residential settings. Different installations had different sets of sensors, meaning not all parameters were measured at every location. The target group for the field trials was elderly people 65+.

During the project it could be shown that the data can be used to estimate presence in a room, based on the environmental data only, where the output of the PIR-Sensors were used as proxy labels. The weakness of the dataset is the lack of validated ground truth, which makes supervised learning approaches difficult. The strength of the dataset lies in the variety of sensors including sound pressure and the long period (nearly 1 year) of high frequency measurements in different countries.

Collecting data in real-world residential settings is challenging, but by making this dataset publicly available, we provide researchers with a valuable resource to explore smart home applications, presence detection, and environmental monitoring in everyday life.

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横跨4个欧洲国家的智能家居环境数据

本文描述了一个在359天（16.05.2023-08.05.2024）的项目中收集的匿名智能家居环境数据集。该数据集包含温度（°C）、湿度（%）、环境光（lux）、二氧化碳（ppm）、VOC （ppm）、声压级（dB）在2-5分钟的时间间隔内的信息，以及来自pir传感器和门接触传感器的基于事件的数据。此外，每个数据点的时间和位置信息以时间戳、用户ID、房间和国家的形式提供。该数据集来自4个不同的欧洲国家，共有62名用户在他们的住宅环境中收集。不同的装置有不同的传感器组，这意味着并非在每个位置测量所有参数。实地试验的目标群体是65岁以上的老年人。在项目期间，可以显示数据可用于估计房间内的存在，仅基于环境数据，其中pir传感器的输出用作代理标签。该数据集的缺点是缺乏经过验证的基础真值，这使得监督学习方法变得困难。数据集的优势在于各种传感器，包括声压和不同国家的长周期（近1年）高频测量。在现实世界的住宅环境中收集数据是具有挑战性的，但是通过公开这个数据集，我们为研究人员提供了一个宝贵的资源来探索智能家居应用、存在检测和日常生活中的环境监测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.