But they use the most data of all smart home devices currently available. We argue that shared home behavior datasets are critical in order to test, compare, and enhance smart home and telemedicine technologies such as user modeling, activity recognition, assessment of … CASAS serves to meet research needs around testing of the technologies using real data through the use of a smart homes environment located on the WSU Pullman campus. Please see the Smart* home page for general information about the project, or the Smart* Tools download page for software that was used in the collection of this data. This dataset contains 3 weeks minute level aggregated energy data, and the ground truth occupancy status data for the same periods. A French corpus of audio and multimodal interactions in a health smart home. The deeproof dataset contains satellite images of roofs along with the planar roof segments of each roof. 2. GHOST-IoT-data-set Smart-home network traffic IoT dataset GHOST -- Safe-Guarding Home IoT Environments with Personalised Real-time Risk Control -- is a European Union Horizon 2020 Research and Innovation funded project that aims to develop a reference architecture for securing smart-homes … There was no mobile signal at the meter itself, so it wasn’t possible to record the gas data in this home. The SHiB is a low cost and easily deployable kit designed to collect data from a wrist-worn wearable in a home … Various sensors were used … Download Matlab dataset in zip format . This also happened in Building03 but in this case we were able to install a pulse logger to take the measurements (see the ‘manufacturer’ and ‘model’ attributes of the sensor on the gas meter in Buidling03 for details). If we want to build a Smart Home AI that was predicted in movies like HER, 2001: A Space Odyssey, and Blade Runner 2049, then the idea stems to something much greater. The apartment dataset contains data for 114 single-family apartments for the period 2014-2016. Smarthome has been recorded in an apartment equipped with 7 Kinect v1 cameras. I n this whitepaper, you will learn how creating a smart home artificial intelligence is made possible with the right dataset. The goal of the Smart* project is to optimize home energy consumption. they are ‘fixed’) and are not supplied by a central heating system. In this article we describe an unlabelled dataset of measurements collected from multiple environmental sensors placed in a smart home to capture human activities of daily living. Yes, each dataset has a contact person who was involved with the collection and curation of the dataset. Electrical dataset (aggregated and individual circuits): Electrical data from circuits (and aggregate): Electrical data from individual energy meters: Electrical data from dimmable and non-dimmable switches: Voltage and frequency data on both electrical phases: Generation data (solar, wind, and battery voltage): Electrical data over a single 24-hour period from 443 unique homes. Please send an email to this person with your query. All calendar timestamps are present in the dataset but for some timestamps, the measurement values are missing: a missing value is represented by the absence of value between two consecutive semi-colon attribute separators. Available here is a wide variety of data collected from three real homes, including electrical (usage and generation), environmental (e.g., temperature and humidity), and operational (e.g., wall switch events). This dataset includes the weather and the normalized solar generation data to learn the physical blackbox model (BuildSys'18). It mainly smart speakers (NUGU, Google Home Mini) answer to questions of play music, and home cameras (EZVIZ, TP-Link) stream images to a cell phone, and smart bulb (Hue) turn on/off or control the light color of bulbs. Hot and colds taps in baths and sinks were not recorded, plugs – only plugs which had an appliance sensor installed were recorded. UK Homeowner Survey: Perceptions of Smart Home Benefits and Risks (University of East Anglia) – this is a dataset of a national survey of 1,054 homes conducted to measure perceptions of smart homes. The remaining 2 homes are within 20km of the weather station. The cmu/zigbee-smarthome dataset (v. 2020-05-26) Captured Zigbee packets from commercial smart home devices. The current version just has the letters X and Y. Smart medical devices are explicitly designed to track hugely private data and send it to your doctor or nurse. Questions? IoT datasets play a major role in improving the IoT analytics. In the case of the IoT, more specifically when it comes to smart homes, there is a lack of open-source datasets available for public access and unfortunately some of them disappear (from the Internet) after being active for a couple of months. REFIT has published 4 open access datasets. This Python notebook gives instructions on how to convert the XML file into csv files for use in spreadsheets or relational databases. Available here is a wide variety of data collected from three real homes, including … A medium resolution setting … Ultimately, if you've decided to join the smart home … Code and dataset: physicalmodel-data-release.tar.gz (163 MB). Download (19 MB) New … This dataset includes: - Building survey data for the 20 homes. The subjects are senior people in the age range 60-80 years old. This dataset contains solar generation data for 81 homes across the United States. The files are named Home_N_X_Y.csv, where N is the home number, X and Y are the coarse latitude and longitude. All questions regarding these traces should be directed to Erik Risinger. REFIT Smart Home Interviews (University of East Anglia) – this dataset contains qualitative data collected using semi-structured interviews and a structured survey at four time points during the REFIT field trial of smart home … Building05 had a gas meter located in the basement. This repository holds dynamic and static data of a smart home use case. Smart* Data Set for Sustainability The goal of the Smart* project is to optimize home energy consumption. All boilers, cookers, fixed heaters, heat pumps, hot water cylinders, lights, meters, openings, persons, radiators, radiator valves, room thermostats, solar photovoltaic arrays, sensors and surfaces are recorded by the building survey. Real world data sets for Activity Recognition with Ambient Sensing. real smart homes, ranging from measurements of security/privacy violations in the wild [6, 7] to training machine learning algorithms for modeling device behaviors [11,12] or inferring device identities [3,13].
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