AI-based IoT Sensor Data Analytics
IoT Doctor is an application that can ingest data from numerous IoT devices and sensors of high quality and alert the user of bad incoming data so that the inherent problem is fixed and this data is not further used for descriptive, predictive or prescriptive analytics.
Identification of error prone data
"Fingerprinting" for detecting tampered sensors or devices
Mitigating the use of tampered data
Automated monitoring of data integrity
& equipment firms
IoT Data Analytics for real time “health” score for a device
IoT Doctor by Scry Analytics Discovers correlation between sensors and devices of various types for flagging spurious data by using multiple sensors & devices close to each other, to detect anomalies.More Detail
- 25+ proprietary AI-based algorithms
- Can simultaneously accommodate more than ten million variables (i.e., devices and sensors)
- Real-time validation against system-generated device fingerprint of each device and sensor
- Noise detection and reduction using specific filters
- Time-series, and frequency domain analyses
- Real-time dashboards and detailed view
- Reinforcement learning via human intelligence and machine learning
Concentio has been built using
the following technologies
Generic rule-based machine learning
Big data integration
Big data analytics
Key Differentiators &
Ready to Use UI
Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ existing workflow.
Customizable graphs and alerts based on prescriptive analysis as per client requirements.
Generates a device fingerprint based on time-series data to predict anomalies in the incoming data.
Real-time check for missing, out of range, abrupt changes in gradient or lack of correlation with other data.