CleanTech IoT - Europe
Processing Real-Time Data from 10K+ Sensors with Predictive Maintenance
Overview
A European CleanTech company deployed smart energy sensors across industrial facilities but lacked the data infrastructure to turn raw sensor telemetry into actionable insights. The goal was a real-time IoT platform with predictive maintenance and energy optimisation.
The Challenge
The company had 10,000+ IoT sensors generating millions of data points per hour with no scalable ingestion pipeline. Maintenance was reactive, energy waste was unmeasured, and the data science team had no platform to run ML models against live data.
Key Pain Points
The Solution
Architected an end-to-end IoT data platform on AWS with MQTT ingestion, time-series storage, edge computing for low-latency decisions, and an ML pipeline for predictive maintenance.
Phase 1: Data Platform Foundation (Months 1-4)
- Designed MQTT broker architecture for sensor ingestion
- Deployed AWS IoT Core and Kinesis Data Streams
- Set up TimescaleDB for time-series storage at scale
- Built data pipeline with schema validation and deduplication
- Created real-time monitoring dashboard with Grafana
Phase 2: Edge Computing & Alerting (Months 5-9)
- Deployed AWS Greengrass edge nodes at 50 facilities
- Implemented local anomaly detection with sub-second latency
- Built PagerDuty-integrated alerting for critical thresholds
- Developed digital twin models for each facility
- Established data quality scoring and lineage tracking
Phase 3: ML & Predictive Maintenance (Months 10-16)
- Built Apache Spark feature engineering pipeline
- Trained predictive maintenance models on 18 months of historical data
- Deployed models to edge nodes for real-time inference
- Created maintenance scheduling engine with priority scoring
- Integrated with ERP systems for work order automation
Phase 4: Energy Optimisation & Scale (Months 17-20)
- Launched energy optimisation recommendation engine
- Expanded to 10,000+ sensors across all facilities
- Delivered carbon footprint tracking and ESG reporting module
- Built self-service analytics portal for facility managers
- Achieved ISO 50001 energy management certification
Technologies Used
Results & Impact
Business Impact
The IoT platform changed how we think about energy. We went from guessing to predicting — maintenance costs collapsed and our ESG scores improved dramatically. An exceptional outcome.
Project Highlights
Real-time sensor monitoring dashboard
Predictive maintenance alert system
Energy optimisation analytics
Key Takeaways
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