Use Case

Real-Time Anomaly Detection Framework for Vehicle Sensor Data

Built an analytics platform that monitors multi-channel vehicle sensor data from ECU / CAN bus in real time and instantly detects abnormal behavior.

Overview

To meet the need for real-time sensor monitoring and instant anomaly detection during vehicle testing, we built an analytics platform that stream-processes multi-channel data from ECU / CAN bus.

                Benefits
                Real-time detection of abnormal behavior during driving tests
Simultaneous multi-channel monitoring reduces missed anomalies
Detection latency kept in the 100ms range, enabling instant response

              

Vehicle sensor real-time anomaly detection screen

Target Industries

Automotive
Transportation Equipment

Challenges Before / Changes After

Before

Data collection and post-processing took days to surface anomalies after tests
Limited number of channels could be monitored visually
Anomaly criteria differed by engineer

              After
              Real-time anomaly detection during tests catches issues immediately
Automated simultaneous monitoring of 256 channels
Unified detection criteria eliminate inconsistency

            

Implementation

Multi-Channel Real-Time Data Ingestion

Captures up to 256 channels simultaneously from ECU / CAN bus via a stream-processing pipeline.

Real-Time Anomaly Scoring

Computes anomaly scores in real time from time-series patterns in sensor data.

Anomaly Detection Dashboard

Provides all-channel monitoring, anomaly alerts, and drill-down analysis.

Input Formats

ECU / CAN bus data (RPM, temperature, speed, throttle, etc. — real-time stream)

Output Formats

Anomaly scores, real-time alerts, analysis logs

Integrations

Vehicle data collection systems, test-management tools

Project Summary

Team & Timeline

Algorithm design → stream-processing platform → dashboard implementation
Vehicle testing team / data platform team / a.s.ist engineers
Built in integration with existing vehicle data collection systems

              Outcomes
              Detection latency below 120 ms achieved
256-channel simultaneous monitoring realized
Established rapid response workflow through instant in-flight alerts

            

Contact Us

We propose end-to-end support — from building the real-time analytics platform to operational design — for vehicle sensor data.

Building multi-channel real-time data ingestion
Design of real-time anomaly scoring
Development of anomaly detection dashboards