TabularScore 71

IoT Sensor Readings

Contributor0x1c2d...3e4f

ListedMar 30, 2026

Purchases156

About this Dataset

10 million sensor readings captured at 1 Hz from 240 industrial IoT devices across a manufacturing facility over an 18-month period. Sensors measure temperature, vibration, pressure, current draw, and humidity. Each anomaly event has been manually verified by a maintenance engineer and labeled with fault type (bearing wear, overheating, pressure leak, electrical fault). The dataset includes pre-fault windows of 60 seconds to support predictive failure modeling. Three months of readings contain intermittent humidity channel data loss.

Validation Report

Quality Analysis

Quality Score72 / 100

Issues

!Sensor drift artifacts in 8% of vibration channel readings
!3% missing timestamp records across November 2023
!Humidity channel data absent for a 90-day window

Strengths

1 Hz high-frequency continuous sampling
18-month uninterrupted observation window
Ground-truth anomaly labels verified by maintenance engineers
Pre-fault sequence windows included for each event

Category & Use Cases

TabularIndustrial Time-Series Anomaly Detection

Recommended Use Cases

Predictive maintenance systemsIndustrial IoT monitoring dashboardsAnomaly detection model benchmarkingEquipment failure signature analysis

Originality Check

Similarity to Known Datasets26%

Industrial sensor data with proprietary equipment profiles and manually verified fault labels not replicated in academic IoT benchmarks.

⚠ Note: Similar sensor datasets exist in academic IoT repositories. This dataset provides higher temporal resolution and engineer-verified labels.

Access Price

0.5OG

On-Chain Proof

Storage Hash

0xd3e4f5a6…d7e8f9a0

Report Hash

0xb7c8d9e0…b1c2d3e4

View on 0G Explorer

156

Total Purchases

Mar 30, 2026

Listed