Multimodal physiological dataset from 15 subjects wearing chest and wrist sensors. Includes ECG, EDA, EMG, respiration, temperature, and accelerometry. CSV/pickle format. Used for stress detection and affective computing research.
Wearable IoT dataset with 18 physical activities from 9 subjects wearing 3 IMUs and a heart rate monitor. 54 columns including temperature, acceleration, and gyroscope data. CSV format. Used for HAR, activity classification, and intensity estimation.
Real-world wearable dataset from 15 nurses over one week in a hospital. Contains 11.5 million entries of EDA, heart rate, skin temperature, and orientation data collected via Empatica E4. CSV format. Used for occupational stress detection research.
Residential smart-home power dataset with 2,075,259 one-minute measurements from a French household over 47 months. TXT/CSV-style tabular format. Used for load forecasting, NILM, and energy behavior analysis.
Smart-home energy dataset with detailed electrical, environmental, and operational streams from 3 real homes plus minute-level electricity data from 400+ homes. Open portal export format. Used for sustainable home and demand analysis.
Long-duration smart-home utility dataset with two years of minutely electricity, water, and natural gas measurements plus weather and billing data. CSV/TSV/RData formats. Used for forecasting, NILM, and resource analytics.
Appliance-level and aggregate electricity dataset from 20 UK households sampled every 8 seconds. CSV files, one per home. Built for energy conservation, NILM, demand response, and smart-home automation research.
Open-access domestic electricity dataset from 5 UK homes with whole-house demand at 16 kHz and appliance channels at 6-second intervals. Research-paper dataset release. Used for NILM, load disaggregation, and smart-meter analytics.
Large-scale real-time air quality monitoring dataset from Dhaka, Bangladesh with 155,406 records. Captures CO, NO2, SO2, O3, PM2.5, and PM10 using IoT sensors with Arduino integration. Ideal for environmental analytics, pollution prediction, and smart city air quality management.
Two years of continuous IoT-based smart parking lot usage data collected via ThingSpeak platform. Features IR sensors and ESP32 boards monitoring slot availability, occupancy patterns, peak hours, and parking duration for urban parking management optimization.