Industrial Equipment Maintenance Data
Real-time sensor data for industrial equipment with maintenance history. Designed for developing predictive maintenance models, failure mode analysis, and maintenance planning systems.
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Real-time sensor data for industrial equipment with maintenance history. Designed for developing predictive maintenance models, failure mode analysis, and maintenance planning systems.
View DatasetIndustrial equipment sensor data with real-time measurements for predictive maintenance and decision support. Combines temperature, vibration, pressure readings with maintenance costs and failure probability scores.
View DatasetSpecialized IoT dataset measuring environmental factors impact on student mental health. Combines air quality, noise levels, temperature, humidity with wellness surveys from university campus.
View DatasetSimulated run-to-failure degradation data from turbofan jet engines. This dataset is widely used as the benchmark for predicting Remaining Useful Life (RUL) in industrial systems.
View DatasetClinical recordings of individual and mixed heart/lung sounds captured via digital stethoscope IoT sensors.
View DatasetBenchmark dataset from Bosch for process monitoring of milling machines based on high-resolution acceleration data.
View DatasetReal-time indoor air quality from IoT sensors tracking CO2, VOCs, PM2.5 for building health and occupancy correlation.
View DatasetChemical sensor measurements tracking CO, NO2, NOx, O3, SO2, PM10 with hourly granularity for environmental health.
View Dataset945 IoT sensor records from IBM's official repo monitoring equipment with pressure measurements for machine failure prediction.
View DatasetHourly air quality measurements from distributed IoT stations across major cities tracking PM2.5, CO2, NO2, and Ozone levels.
View DatasetMulti-sensor data (pressure, temperature, flow) from a hydraulic test rig for fault diagnosis of cooler, valve, pump, and accumulator.
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