IOT PREDICTIVE MAINTENANCE
predictive
IoT Predictive Maintenance & Failure Prevention
An industrial IoT predictive maintenance system analyzing vibration, thermal, and telemetry sensors to forecast machinery failures days in advance, reducing unplanned downtime by 40%.
# Time-Series Forecasting# IoT Sensor Data# LSTM# Grafana# Prophet
Contract formatContract development
Development system4 people
Development period4 months
Key Features
Core System Capabilities
Optimized modular design for both End-Users and Enterprise Management Admin
01
Field Engineer side
- Equipment health status dashboard
- Predictive failure alert notifications
- Remaining Useful Life (RUL) estimation
- Work order maintenance ticket creation
4 features
02
IoT & Predictive AI side
- High-frequency sensor stream ingestion (MQTT)
- LSTM / Transformer time-series anomaly detection
- Acoustic & vibration spectral analysis
- Automated baseline anomaly scoring
4 features
03
Plant Manager side
- Plant-wide machinery uptime metrics
- Maintenance cost reduction ROI portal
- Sensor hardware health monitoring
- ERP / CMMS work order integration
4 features
Development Scope
Project Life Cycle & Phases
Phase 01
Requirement definition
Phase 02
UI/UX design
Phase 03
Time-Series AI tuning
Phase 04
Development
Phase 05
Unit / Integration testing
Phase 06
Operation and Maintenance
Tech Stack Architecture
Technologies Used in Project
Languages & Core Frameworks
Python, C++, TensorFlow Lite
AI Tools & GenAI Models
Prophet Time-Series, Edge Impulse ML, Antigravity IoT Predictor, Gemini 1.5 Flash
Databases & Vector Storage
InfluxDB Time-Series, PostgreSQL
Infrastructure & Cloud Services
MQTT Broker, AWS IoT Core, Docker Edge
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