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.