有没有相关的论文或文献参考？
这个数据集是基于什么背景创建的？
数据集的作者是谁？
能帮我联系到这个数据集的作者吗？
这个数据集如何下载？
UCI HAR Dataset|人体活动识别数据集|智能手机数据数据集
收藏kaggle2023-02-17 更新2024-03-08 收录
下载链接：
https://www.kaggle.com/datasets/quanganh2001/uci-har-dataset
下载链接
链接失效反馈资源简介：
This is the the Human Activity Recognition Using Smartphones dataset
创建时间：
2023-02-17
AI搜集汇总
数据集介绍
构建方式
UCI HAR Dataset（Human Activity Recognition Using Smartphones Dataset）构建于智能手机传感器数据之上，通过收集来自30名受试者在执行六种日常活动（如步行、站立、躺下等）时的加速度和角速度数据。数据采集过程中，受试者佩戴三星Galaxy S II智能手机，传感器数据经过预处理，包括滤波和标准化，最终形成时间序列数据。
特点
该数据集的显著特点在于其高精度和多维度特性。数据集包含了时间域和频率域的特征，涵盖了三轴加速度和三轴角速度的详细信息。此外，数据集还提供了受试者的身份标识和活动标签，便于进行个性化和活动识别的研究。
使用方法
UCI HAR Dataset广泛应用于机器学习和数据挖掘领域，尤其适用于活动识别和行为分析。研究者可以通过加载数据集，利用分类算法（如支持向量机、随机森林等）训练模型，以识别和预测用户的活动类型。此外，数据集的高质量特征使其成为开发和测试新算法的理想选择。
背景与挑战
背景概述
UCI HAR Dataset，即UCI人类活动识别数据集，由Anguita等人于2012年在加泰罗尼亚理工大学开发。该数据集旨在解决穿戴式传感器在人类活动识别中的应用问题，通过收集来自智能手机的加速度计和陀螺仪数据，记录了30名受试者在执行六种日常活动（如行走、站立、坐下等）时的运动数据。这一数据集的发布极大地推动了机器学习在行为识别领域的应用，为研究人员提供了一个标准化的基准，促进了相关算法的开发与评估。
当前挑战
UCI HAR Dataset在构建过程中面临了多重挑战。首先，数据采集需确保传感器数据的准确性和一致性，以避免噪声干扰。其次，不同受试者的个体差异和活动执行方式的多样性增加了数据预处理的复杂性。此外，数据集需涵盖多种活动类型，以保证模型的泛化能力。最后，如何在有限的样本量下实现高效的学习算法，以准确识别和分类不同的活动，是该数据集面临的主要技术难题。
发展历史
创建时间与更新
UCI HAR Dataset创建于2012年，由Davide Anguita等人发布，旨在为人类活动识别研究提供标准化的数据集。该数据集自发布以来，未有官方更新记录。
重要里程碑
UCI HAR Dataset的发布标志着人类活动识别领域的一个重要里程碑。该数据集包含了来自30名受试者的智能手机传感器数据，涵盖了六种基本活动（如行走、站立、躺下等）。其标准化和公开性极大地促进了相关算法的开发与评估，成为许多研究论文和机器学习竞赛的基础数据集。此外，该数据集的广泛应用也推动了传感器数据处理和模式识别技术的发展。
当前发展情况
UCI HAR Dataset目前仍然是人类活动识别领域的重要参考数据集，尽管近年来出现了更多复杂和多样化的数据集，但其基础性和标准化特性使其在教育和研究中仍具有不可替代的地位。该数据集的成功应用不仅推动了传感器数据分析技术的发展，还为后续数据集的设计和评估提供了宝贵的经验。随着物联网和可穿戴设备的普及，UCI HAR Dataset的影响力仍在持续，为新一代智能系统的开发提供了坚实的基础。
发展历程
- UCI HAR Dataset首次发表，由Davide Anguita等人提出，作为人类活动识别研究的基准数据集。
- UCI HAR Dataset被广泛应用于机器学习和数据挖掘领域，成为研究人类活动识别的重要资源。
- 随着深度学习技术的发展，UCI HAR Dataset开始被用于开发和验证基于深度神经网络的活动识别模型。
- UCI HAR Dataset的数据质量和多样性得到了进一步的认可，成为多个国际会议和期刊中的标准测试集。
- UCI HAR Dataset继续被广泛使用，并在多个研究项目中作为基准数据集，推动了人类活动识别技术的发展。
常用场景
经典使用场景
在人体活动识别领域，UCI HAR Dataset 被广泛用于开发和评估机器学习模型。该数据集记录了30名受试者在佩戴智能手机的情况下进行的六种日常活动，包括行走、站立、坐下、躺下、上楼和下楼。通过分析传感器数据，研究人员可以构建分类模型，以准确识别和区分这些活动。
实际应用
在实际应用中，UCI HAR Dataset 为开发智能健康监测设备和系统提供了宝贵的数据支持。例如，通过分析用户的活动数据，智能手表和手机应用可以实时监测用户的健康状况，提供个性化的健康建议。此外，该数据集还被用于开发老年人护理系统，通过识别异常活动模式，及时发出警报，提高护理效率和安全性。
衍生相关工作
基于UCI HAR Dataset，许多经典工作得以展开。例如，研究人员开发了多种特征提取和降维技术，以提高活动识别的准确性。此外，该数据集还激发了关于数据隐私和安全的研究，探讨如何在保护用户隐私的前提下，有效利用传感器数据。这些衍生工作不仅丰富了活动识别领域的研究内容，也为相关技术的实际应用提供了理论支持。
以上内容由AI搜集并总结生成
数据主题
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集
LFW
人脸数据集;LFW数据集共有13233张人脸图像，每张图像均给出对应的人名，共有5749人，且绝大部分人仅有一张图片。每张图片的尺寸为250X250，绝大部分为彩色图像，但也存在少许黑白人脸图片。 URL: http://vis-www.cs.umass.edu/lfw/index.html#download
AI_Studio 收录
VoxBox
VoxBox是一个大规模语音语料库，由多样化的开源数据集构建而成，用于训练文本到语音（TTS）系统。
github 收录
中国区域交通网络数据集
该数据集包含中国各区域的交通网络信息，包括道路、铁路、航空和水路等多种交通方式的网络结构和连接关系。数据集详细记录了各交通节点的位置、交通线路的类型、长度、容量以及相关的交通流量信息。
data.stats.gov.cn 收录
CatMeows
该数据集包含440个声音样本，由21只属于两个品种（缅因州库恩猫和欧洲短毛猫）的猫在三种不同情境下发出的喵声组成。这些情境包括刷毛、在陌生环境中隔离和等待食物。每个声音文件都遵循特定的命名约定，包含猫的唯一ID、品种、性别、猫主人的唯一ID、录音场次和发声计数。此外，还有一个额外的zip文件，包含被排除的录音（非喵声）和未剪辑的连续发声序列。
huggingface 收录
Canadian Census
**Overview** The data package provides demographics for Canadian population groups according to multiple location categories: Forward Sortation Areas (FSAs), Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs), Federal Electoral Districts (FEDs), Health Regions (HRs) and provinces. **Description** The data are available through the Canadian Census and the National Household Survey (NHS), separated or combined. The main demographic indicators provided for the population groups, stratified not only by location but also for the majority by demographical and socioeconomic characteristics, are population number, females and males, usual residents and private dwellings. The primary use of the data at the Health Region level is for health surveillance and population health research. Federal and provincial departments of health and human resources, social service agencies, and other types of government agencies use the information to monitor, plan, implement and evaluate programs to improve the health of Canadians and the efficiency of health services. Researchers from various fields use the information to conduct research to improve health. Non-profit health organizations and the media use the health region data to raise awareness about health, an issue of concern to all Canadians. The Census population counts for a particular geographic area representing the number of Canadians whose usual place of residence is in that area, regardless of where they happened to be on Census Day. Also included are any Canadians who were staying in that area on Census Day and who had no usual place of residence elsewhere in Canada, as well as those considered to be 'non-permanent residents'. National Household Survey (NHS) provides demographic data for various levels of geography, including provinces and territories, census metropolitan areas/census agglomerations, census divisions, census subdivisions, census tracts, federal electoral districts and health regions. In order to provide a comprehensive overview of an area, this product presents data from both the NHS and the Census. NHS data topics include immigration and ethnocultural diversity; aboriginal peoples; education and labor; mobility and migration; language of work; income and housing. 2011 Census data topics include population and dwelling counts; age and sex; families, households and marital status; structural type of dwelling and collectives; and language. The data are collected for private dwellings occupied by usual residents. A private dwelling is a dwelling in which a person or a group of persons permanently reside. Information for the National Household Survey does not include information for collective dwellings. Collective dwellings are dwellings used for commercial, institutional or communal purposes, such as a hotel, a hospital or a work camp. **Benefits** - Useful for canada public health stakeholders, for public health specialist or specialized public and other interested parties. for health surveillance and population health research. for monitoring, planning, implementation and evaluation of health-related programs. media agencies may use the health regions data to raise awareness about health, an issue of concern to all canadians. giving the addition of longitude and latitude in some of the datasets the data can be useful to transpose the values into geographical representations. the fields descriptions along with the dataset description are useful for the user to quickly understand the data and the dataset. **License Information** The use of John Snow Labs datasets is free for personal and research purposes. For commercial use please subscribe to the [Data Library](https://www.johnsnowlabs.com/marketplace/) on John Snow Labs website. The subscription will allow you to use all John Snow Labs datasets and data packages for commercial purposes. **Included Datasets** - [Canadian Population and Dwelling by FSA 2011](https://www.johnsnowlabs.com/marketplace/canadian-population-and-dwelling-by-fsa-2011) - This Canadian Census dataset covers data on population, total private dwellings and private dwellings occupied by usual residents by forward sortation area (FSA). It is enriched with the percentage of the population or dwellings versus the total amount as well as the geographical area, province, and latitude and longitude. The whole Canada's population is marked as 100, referring to 100% for the percentages. - [Detailed Canadian Population Statistics by CMAs and CAs 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-cmas-and-cas-2011) - This dataset covers the population statistics of Canada by Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs). It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by FED 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-fed-2011) - This dataset covers the population statistics of Canada from 2011 by Federal Electoral District of 2013 Representation Order. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by Health Region 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-health-region-2011) - This dataset covers the population statistics of Canada by health region. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by Province 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-province-2011) - This dataset covers the population statistics of Canada by provinces and territories. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. **Data Engineering Overview** **We deliver high-quality data** - Each dataset goes through 3 levels of quality review - 2 Manual reviews are done by domain experts - Then, an automated set of 60+ validations enforces every datum matches metadata & defined constraints - Data is normalized into one unified type system - All dates, unites, codes, currencies look the same - All null values are normalized to the same value - All dataset and field names are SQL and Hive compliant - Data and Metadata - Data is available in both CSV and Apache Parquet format, optimized for high read performance on distributed Hadoop, Spark & MPP clusters - Metadata is provided in the open Frictionless Data standard, and its every field is normalized & validated - Data Updates - Data updates support replace-on-update: outdated foreign keys are deprecated, not deleted **Our data is curated and enriched by domain experts** Each dataset is manually curated by our team of doctors, pharmacists, public health & medical billing experts: - Field names, descriptions, and normalized values are chosen by people who actually understand their meaning - Healthcare & life science experts add categories, search keywords, descriptions and more to each dataset - Both manual and automated data enrichment supported for clinical codes, providers, drugs, and geo-locations - The data is always kept up to date – even when the source requires manual effort to get updates - Support for data subscribers is provided directly by the domain experts who curated the data sets - Every data source’s license is manually verified to allow for royalty-free commercial use and redistribution. **Need Help?** If you have questions about our products, contact us at [info@johnsnowlabs.com](mailto:info@johnsnowlabs.com).
Databricks 收录