Predictive Maintenance
Monitor equipment health and reduce unexpected downtime before faults escalate.
Industrial Data Analytics
Traditional to advanced industrial data analytics.
Learn, prototype, and apply IIoT analytics, vibration monitoring, electrical signature analysis, anomaly detection, and machine learning for industrial operations.
IIoT
connected sensors, machines, and operational data
MCSA
non-intrusive current and electrical signature analysis
ML
anomaly detection, classification, forecasting, and analytics
Industrial Data Analytics
Transform raw plant data into strategic value.
The WordPress export describes Indus Analytics as a practical resource for Industrial IoT data analytics: connected sensors, devices, and machines collecting real-time operational data and turning it into actionable insight for reliability, process efficiency, energy optimization, and measurable ROI.
Anomaly Detection
Identify point, contextual, and pattern anomalies in industrial sensor data.
Process Efficiency
Use IIoT and analytics to improve production decisions and operating performance.
Data Quality
Validate sensor, historian, PLC, SCADA, CMMS, and ERP data before modeling.
Approach
An end-to-end workflow for industrial ML and analytics projects.
- Understand the objective Define users, business value, current limitations, and how the output will be used.
- Choose the right learning setup Decide between anomaly detection, classification, regression, forecasting, or online learning.
- Engineer useful features Combine time-domain, spectral, envelope, and domain-specific features from real signals.
- Measure and iterate Track precision, recall, false alarms, missed events, and usefulness for plant teams.
Core Topics
Content pillars from the WordPress export.
IIoT-Based Vibration Monitoring
Measure machine vibration, identify patterns, and detect developing failures before breakdowns.
Current/Electrical Signature Analysis
Use non-intrusive current and voltage signals to assess motors, drives, pumps, and compressors.
ML Playground
Upload, simulate, preprocess, and train industrial ML models from an interactive dashboard.
Python Codes and Guides
Beginner-friendly Python resources for vibration analysts and engineers using Colab and AI.
AI + SCADA
Explore how AI, ML, and SCADA systems reshape operational efficiency and quality control.
Digital Transformation
Move beyond dashboards toward long-standing plant problems that IIoT can actually solve.
Insights
Published posts and learning tracks.
Podcast
Anomaly Detection: A Common ML Application for Industrial Data
Guide
Unlocking Hidden Patterns with Matrix Profile Time-Series Analysis
Practice
The Importance of Data Quality in Industrial Data Analysis
Workflow
End-to-end ML and Analytics Projects
IIoT
3 Keys to Successful Machine Learning Application in Industrial IoT
Methods
Effective Strategies for Selecting Anomaly Detection Algorithms
Digital
Best Practice for IIoT or Digital Transformation
Build
Vibe Coding: The Fastest Way to Bring Engineering Ideas to Reality
Contact
For paid services, bring a signal, dashboard, or plant question.
The exported WordPress contact page says "FOR PAID SERVICES." This refreshed site keeps that intent and gives visitors a clearer path to discuss industrial analytics support.