Press Release Summary:
- Provides fast and simple way for industrial companies to implement anomaly detection for specific machines and processes
- Delivers quick and easy development of smart sensors for real-time anomaly detection through intelligent IoT endpoints
- Smart sensors functionalities include baseline algorithms, triggered events and simple closed-loop feedback
Original Press Release:
SensiML Analytics Toolkit Delivers Quick and Easy Anomaly Detection for Industrial Applications
- Critical use of AI for industrial IoT with broad applicability across machines and industries
- Rapidly customizable smart sensor technology simplifies practical implementation
Portland, OR – October 9, 2019 – SensiML Corporation, a leading developer of AI tools for building intelligent IoT endpoints, today 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. 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 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 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 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.”
The SensiML Analytics Toolkit is available now. For more information, visit https://sensiml.com/products.
SensiML, a subsidiary of QuickLogic, offers cutting-edge software that enables ultra-low power IoT endpoints that implement AI to transform raw sensor data into meaningful insight at the device itself. The company’s flagship solution, the SensiML Analytics Toolkit, provides an end-to-end development platform spanning data collection, labeling, algorithm and firmware auto generation, and testing. The SensiML Toolkit supports Arm® Cortex®-M class and higher microcontroller cores, Intel® x86 instruction set processors, and heterogeneous core QuickLogic SoCs and QuickAI platforms with FPGA optimizations. For more information, visit www.sensiml.com.