Key highlights
Over 90 %
increase in anomaly detection precision
Over 60 %
more accurate than rule-based methods more accurate than rule-based methods
Over 85 %
CSAT score for the chat interface
Challenges
1.
Visualized anomaly data and generated reports with difficulty.
2.
Visualized anomaly data and generated reports with difficulty.
3
Lacked an easy way for users to interact and retrieve anomaly details.
Solution
1.
Integrated reconstructed data for further analysis using algorithms.
2.
Detected anomalies in sensor data, including outliers and sudden spikes, while enabling real-time monitoring.
3
Displayed graphical visualizations of anomalies with date and timestamp details, along with downloadable reports in CSV, Excel, or PDF.
4
Enabled users to ask questions and receive relevant responses about anomaly detection.
Impact
Data integration Algorithms analyzed reconstructed data.
Anomaly detection System detected anomalies and monitored data in real-time.
Data visualization Users downloaded reports in CSV, Excel, or PDF.
User interaction Users asked questions and received relevant responses.