THE CHALLENGE:
Increasingly, sensor data plays a ‘mission critical’ role in ensuring that industrial operations remain safe and efficient.
An ever-growing number of sensors makes it increasingly challenging for operators to track and interpret sensor data accurately and in real-time. This can result in unmonitored malfunctioning sensors, poor data quality or even forged sensor data.
In the long term, poor data quality greatly harms the efficiency of data analytics, predictive maintenance and strategic planning.
EXISTING SOLUTIONS:
Existing solutions that attempt to address these problems tend to be static, pre-configured, heavy in manual resources and not scalable.
They cannot detect and interpret subtly misleading data that stems from partial malfunctions or misconfigured sensors. This compromises safety and leads to poor data quality.
In addition, current solutions cannot adequately protect the data streams generated by large numbers of sensors. This results in a vulnerability to sensor data manipulation by attackers.
APERIO'S SOLUTION:
Aperio has developed a fully-automated machine learning solution that ensures sensor data integrity across the entire industrial network.
It uses advanced proprietary algorithms to ‘learn’ each sensor’s unique fingerprint. It then checks each sensor's data signal in real-time and alerts operators if any anomalies or issues are detected.
It is easy to deploy, requires zero configuration and can scale without limitation. This way, Aperio ensures the ongoing safety of industrial operations and helps customers to extract maximum value from operational data.
