SensiML™ Corporation, a leading developer of AI tools for building intelligent IoT endpoints, announced that its SensiML Analytics Toolkit delivers quick and easy development of smart sensors for real-time anomaly detection through intelligent IoT endpoints. This approach addresses a broad spectrum of industrial equipment, processes, and industries. By simplifying the development and implementation of anomaly detection devices, SensiML enables companies to focus their scarce and valuable technical resources on application-specific functionality, not hand-coded ML and dataset manipulation.
Anomaly detection works by regularly monitoring equipment and constantly measuring key variables such as temperature, vibration, sound, motion, flow, and other time-series sensor data. The AI-based analysis is used to establish “normal” and “outlier” behavior. Detected anomalies can then be flagged for immediate intervention or recorded for later analysis. Anomaly detection can be part of a larger Condition Monitoring (CM) or Predictive Maintenance (PdM) program for a company or can be used independently in a more targeted way.
The SensiML Analytics Toolkit provides a fast and simple way for industrial companies to implement anomaly detection for their specific machines and processes. For example, using SensiML-generated algorithms, technicians can transform traditional sensors into customizable, machine-specific anomaly detectors during initial machine installation or during a later retrofitting. Some of the new functionality available through the use of these “smart sensors” include:
- Baseline algorithms that can adapt with edge learning to improve insight with the use
- Triggered events that can optionally report feature vector results or corresponding raw sensor data
- Simple closed-loop feedback that can involve operators in system tuning as appropriate
“These are truly exciting times for industrial IoT innovation. Ubiquitous sensors combined with today’s highly efficient endpoint processors and sophisticated AutoML tools like SensiML now make it practical to the instrument virtually all aspects of the smart factory. Complex industrial processes can be now be characterized by their many component subprocesses and analyzed using distributed processing where it makes the most sense,” said Chris Rogers, CEO of SensiML. “Through the use of anomaly detection with adaptive smart sensor hardware and our AI Toolkit, developers of sensor modules can offer new innovative solutions that efficiently monitor plant equipment, optimize processes, and lower operating costs to improve the bottom line.”