Real-Time Streaming Detection for Water & Energy Network Leaks & Faults

SeafaringIT

StageSur site4 à 6 moisDate limite : 23 févr. 2026
Streaming DataBackend microservices (Nest, Kafka)Flink/Spark StreamingAnomaly detectionbackend APIsTime-series AnalysisDevopsIndustrial Dashboards

Postuler

Description

  • Goals:
  • Build a real-time streaming pipeline to detect leaks and anomalies in water/energy networks
  • Enable near-instantaneous detection to reduce losses and risks
  • Provide actionable insights for supervision and maintenance
  • Student roles: Data engineers, streaming specialists, ML engineers, backend engineers, DevOps engineers
  • Expected outcomes: Real-time streaming platform with sensor ingestion, anomaly detection, contextual correlation, dashboards, and operational procedures
  • Key features:
  • Real-time ingestion from sensors (simulated and real)
  • Streaming anomaly detection with scoring and prioritization
  • Contextual correlation (zones, historical patterns, weather)
  • Real-time supervision API and dashboards
  • Alert management and escalation
  • Performance monitoring (latency, false positives)
  • Operational runbooks; integration with SCADA/monitoring systems
  • Technologies: Apache Kafka, Apache Spark/Flink, anomaly detection algorithms, stream processing, PostgreSQL/TimescaleDB, Redis, FastAPI, BI tools (Grafana, Kibana), Docker, Kubernetes