Smart house measurements

Name: Smart house measurements
Creator: Zenodo
Published: 2023-02-10T10:37:08+08:00

Zenodo2023-02-14 更新2026-05-26 收录

数据链接：

https://zenodo.org/record/7628297 数据链接链接失效反馈

官方服务：

资源简介：

Load Forecasting Dataset Readme File VARLAB – The Centre for Research & Technology, Hellas [CERTH] - Informatics and Telematics Institute [ITI] - https://varlab.iti.gr/ Authors: Chrysovalantis-George Kontoulis, Georgios Stavropoulos, Dimosthenis Ioannidis Publication Date: February -, 2023 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No. 957406 (TERMINET). 1.Introduction This dataset features information from a smarthome located at Greece, which features the Mediterranean climate. The building is utilized as a modern workplace that is being used for various every day activities. It is equipped with numerous smart devices and appliances, from smart lights to smart a elevator, while also featuring PVTs. 2.Dataset Overview 2.1Dataset Collection The system is built on multiple communication protocols including EnOcean, Zigbee, Modbus, BACnet, and, LTE/IEEE 802.15.4 at 2.4GHz. For the sensor data collection, a raspberry Pi microcontroller was used, and data were subsequently transmitted to the storage database. The extraction period of the data is between 2021-01-01 through 2022-12-20. Along this period there is a total of 66619 unique recordings and the time granularity of the data is set to 15 minutes for all devices. 2.2Data Peculiarities The place is occupied from Monday to Friday from 9:00 AM GMT+2 (Greenwich Mean Time) all the way through 5:00 PM GMT+2. Note that the building is not active during Greek public holidays, but some computers or servers might be on and consuming electrical energy. Also, there are some irregularities in the data reporting consistency at summer, Christmas & Easter as the building is not occupied for a long time of period. Timestamps of the dataset are in the GMT+2 timezone. 2.3Dataset Structure This dataset includes a total of six features and it can be used for Electrical, Thermal and Cooling Load forecasting. Electricity Consumption is the consumption of the whole house, Air-condition Status is either 1 or 0 for on and off, respectively, Luminance is how bright a space is, Light Dimming is the dimming of the lights in each room. Finally we have the Indoor Temperature for each room and the Outdoor Temperature. Data are extracted from four rooms in total. Note that in rooms 1 and 3, there is only one indoor temperature device, thus values are identical for temperature_room_1 and temperature_room_3. Note that sensors have some null values, which is generally either due to inactivity, e.g., the Light Dimming sensor and the Air-condition Status are event-based or due to potential system downtime. The provided dataset is stored in csv format. A brief overview of the dataset is presented at the Table 3.1. Table 2.1 Dataset overview Censor Symbolic Naming Measurement Unit Electricity Consumption KWh_S_total kWh Air-condition Status status_room_0 status_room_1 status_room_2 status_room_3 - Luminance luminance_room_0 luminance_room_1 luminance_room_2 luminance_room_3 Lux Light Dimming dimming_room_0 dimming_room_1 dimming_room_2 dimming_room_3 % Indoor Temperature temperature_room_0 temperature_room_1 temperature_room_2 temperature_room_3 °C Outdoor Temperature airTemperature °C 2.4Descriptive Statistics Table 2.2 provides a brief overview of the key statistical characteristics of the data to. The table presents a summary of important metrics and measures, including measure of central tendency such as the mean, as well as measures of variability such as the standard deviation. Table 2.2 Descriptive Statistics Symbolic Naming Values Count Mean Std Min Max KWh_S_total 62877 71511,16 52235,30 2,22 135494,70 status_room_0 status_room_1 status_room_2 status_room_3 16689 14357 13302 13388 0,38 0,15 0,27 0,26 0,49 0,36 0,44 0,44 0,00 0,00 0,00 0,00 1,00 1,00 1,00 1,00 luminance_room_0 luminance_room_1 luminance_room_2 luminance_room_3 31676 14727 6799 23993 169,93 165,95 99.71 205,66 294,60 267,69 157,40 304,14 0.00 0.00 0.00 0.00 1024,00 1024,00 1024,00 1024,00 dimming_room_0 dimming_room_1 dimming_room_2 dimming_room_3 432 683 8 608 1,95 41.29 15,00 42,40 11,23 40.32 22,68 43,43 0,00 0,00 0,00 0, 00 100,00 100,00 50,00 100,00 temperature_room_0 temperature_room_1 temperature_room_2 temperature_room_3 26915 33786 34778 33786 27,50 24,28 23,89 24,28 4,44 2,96 4,52 2,96 17,54 13,95 7,95 13,95 44,30 34,62 35,59 34,62 airTemperature 47647 16,91 8,62 -4,52 40,28 3.Acknowledgment This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No. 957406 (TERMINET).

### 负荷预测数据集说明文档 VARLAB——希腊技术研究中心（CERTH, Centre for Research & Technology Hellas）信息与电信研究所（ITI, Informatics and Telematics Institute）——https://varlab.iti.gr/ 作者：Chrysovalantis-George Kontoulis、Georgios Stavropoulos、Dimosthenis Ioannidis **发布日期：** 2023年2月本项目获欧盟地平线2020研究与创新计划资助，资助协议编号：957406（TERMINET）。 ## 1. 引言本数据集包含位于希腊（地中海气候）的一处智能家居的相关信息。该建筑被用作现代化办公场所，承载各类日常办公活动。其内部署了丰富的智能设备与电器，覆盖智能照明至智能电梯，并集成了光伏光热（PVT, Photovoltaic Thermal）系统。 ## 2. 数据集概述 ### 2.1 数据集采集本系统基于EnOcean、Zigbee、Modbus、BACnet及2.4GHz频段LTE/IEEE 802.15.4等多种通信协议构建。传感器数据采集采用树莓派（Raspberry Pi）微控制器完成，采集完成后数据将传输至存储数据库。数据采集时段为**2021-01-01 至 2022-12-20**，期间总计生成66619条唯一记录，所有设备的数据时间粒度均设置为**15分钟**。 ### 2.2 数据特征该建筑的办公时段为周一至周五的GMT+2时区9:00至17:00。需注意，希腊法定节假日期间建筑无人员值守，但部分计算机或服务器可能仍处于运行状态并消耗电能。此外，夏季、圣诞节及复活节期间，因建筑长时间无人使用，数据上报的一致性存在部分异常。数据集时间戳采用GMT+2时区。 ### 2.3 数据集结构本数据集共包含6项特征，可用于电力、热力及冷负荷预测： - **总用电量（Electricity Consumption）**：整栋建筑的总耗电量 - **空调运行状态（Air-condition Status）**：取值为0或1，分别对应关闭与开启 - **照度（Luminance）**：空间光照亮度 - **灯光调光值（Light Dimming）**：各房间灯光的调光比例 - **室内温度（Indoor Temperature）**：各房间室内温度 - **室外温度（Outdoor Temperature）**：环境室外温度数据集覆盖总计4个房间。需注意，房间1与房间3仅部署了一台室内温度传感器，因此`temperature_room_1`与`temperature_room_3`的取值完全一致。传感器数据存在部分空值，通常源于两类情况：一是设备未激活，例如灯光调光值传感器与空调运行状态传感器为事件触发式传感器；二是系统临时停机。本数据集以CSV格式存储。数据集简要概览详见表3.1。 **表2.1 数据集概览** | 传感器 | 符号命名 | 测量单位 | | ---- | ---- | ---- | | 总用电量 | KWh_S_total | 千瓦时（kWh） | | 空调运行状态 | status_room_0、status_room_1、status_room_2、status_room_3 | 无单位 | | 照度 | luminance_room_0、luminance_room_1、luminance_room_2、luminance_room_3 | 勒克斯（Lux） | | 灯光调光值 | dimming_room_0、dimming_room_1、dimming_room_2、dimming_room_3 | 百分比（%） | | 室内温度 | temperature_room_0、temperature_room_1、temperature_room_2、temperature_room_3 | 摄氏度（°C） | | 室外温度 | airTemperature | 摄氏度（°C） | ### 2.4 描述性统计表2.2简要展示了数据集的关键统计特征，汇总了包括均值在内的集中趋势指标，以及标准差在内的离散程度指标。 **表2.2 描述性统计** | 符号命名 | 样本量 | 均值 | 标准差 | 最小值 | 最大值 | | ---- | ---- | ---- | ---- | ---- | ---- | | KWh_S_total | 62877 | 71511.16 | 52235.30 | 2.22 | 135494.70 | | status_room_0 | 16689 | 0.38 | 0.49 | 0.00 | 1.00 | | status_room_1 | 14357 | 0.15 | 0.36 | 0.00 | 1.00 | | status_room_2 | 13302 | 0.27 | 0.44 | 0.00 | 1.00 | | status_room_3 | 13388 | 0.26 | 0.44 | 0.00 | 1.00 | | luminance_room_0 | 31676 | 169.93 | 294.60 | 0.00 | 1024.00 | | luminance_room_1 | 14727 | 165.95 | 267.69 | 0.00 | 1024.00 | | luminance_room_2 | 6799 | 99.71 | 157.40 | 0.00 | 1024.00 | | luminance_room_3 | 23993 | 205.66 | 304.14 | 0.00 | 1024.00 | | dimming_room_0 | 432 | 1.95 | 11.23 | 0.00 | 100.00 | | dimming_room_1 | 683 | 41.29 | 40.32 | 0.00 | 100.00 | | dimming_room_2 | 8 | 15.00 | 22.68 | 0.00 | 50.00 | | dimming_room_3 | 608 | 42.40 | 43.43 | 0.00 | 100.00 | | temperature_room_0 | 26915 | 27.50 | 4.44 | 17.54 | 44.30 | | temperature_room_1 | 33786 | 24.28 | 2.96 | 13.95 | 34.62 | | temperature_room_2 | 34778 | 23.89 | 4.52 | 7.95 | 35.59 | | temperature_room_3 | 33786 | 24.28 | 2.96 | 13.95 | 34.62 | | airTemperature | 47647 | 16.91 | 8.62 | -4.52 | 40.28 | ## 3. 致谢本项目获欧盟地平线2020研究与创新计划资助，资助协议编号：957406（TERMINET）。

提供机构：

Zenodo

创建时间：

2023-02-10

Smart house measurements

资源简介：

相关数据集