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Category: Sentinel IT

Sentinel Network is a web application that combines network monitoring and prognostic health management (PHM) technologies. The main feature of Sentinel Network is its ability to predict the remaining useful life of network assets such as power supply devices (UPS) and battery backups. This reduces network downtime by permitting condition-based maintenance of these critical assets prior to catastrophic failure.


  • Application: IT Networks
  • Sensor: ITProbe
  • Data Type: Management Information Base (MIB)
  • Reasoner: ARULE
  • GUL: Sentinel Dashboard


Sentinel Network monitoring technology includes network discovery, IT asset inventory, and real-time device health monitoring.
A baseline network configuration is committed to the Sentinel Network database after initial network discovery. An SNMP agent is used to retrieve WMI data from IT devices. A built-in troubleshooter will resolve switch configuration management issues. The application also generates three types of alerts, which are sent via email to notify network administrators about events in the network.


Sentinel Network comprises different features that enable users to proactively manage their network.
The discovery features allow users to be aware of the assets connected or disconnected from the network. This allows a better inventory of the network devices. Sentinel Network also includes two types of monitoring: Lightweight and Full. These features permit the user to monitor events occurring in the network.
Sentinel Network offers several benefits for companies to help reduce costs. The main feature of Sentinel Network is prognostics, which helps to:

  • Reduce maintenance cost
  • Minimize downtime cost
  • Enable efficient maintenance planning


Remote monitoring

A web application that can be accessed remotely from any computer on the local network or
through the internet.

Network management Offers a more efficient and effective way to manage your network.
Real-time monitoring Graph representation of IT devices’ performance, such as CPU, memory, hard drive and more.
Customized thresholds Allows users to establish thresholds to monitor network devices’ state of health.

The only network monitoring software that offers prognostics and health management
(PHM). The application uses a complex algorithm to predict the remaining useful life of power
supplies (or UPS battery backup) within a network.

Zero downtime

Network discovery, network configuration monitoring, WMI and registry monitoring, etc.
Generate three classes of alerts: critical, warning, and informational. The administrator
specifies the content of the email alert to include relevant location and fault information.

Troubleshooting Ability to perform troubleshooting actions for switches



Adaptive Remaining Useful Life Reasoner for Prognostics and Health Management (PHM) Applications
ARULE Product Brief
Ridgetop’s Adaptive Remaining Useful Life Estimator (ARULE) is a powerful reasoner to determine the remaining useful life (RUL) and state of health (SoH) of complex systems. Working from acquired sensor data, ARULE employs an advanced prediction method related to extended Kalman filtering (EKF) to produce new RUL and SoH estimates for each new sensor data point.
ARULE is versatile and can be used for determining electronic and mechanical fatigue damage. The reasoner calculates fault-to-failure progression (FFP) signatures, accurate RUL (time-to-failure) estimates, and SoH estimates, which provide an early warning indicator for system maintenance personnel to schedule service to the system prior to catastrophic failure.

ARULE relies on diagnostic sensor data and a predefined model to produce an RUL estimate. It requires a sensor to "sense" data that are above a predefined "good-as-new" floor and below a "failed" ceiling. A new RUL estimate is produced based on changes to the model space; additionally, the new RUL estimate is used to produce a new SoH estimate.


  • Power systems
  • Battery management systems
  • Actuator control systems
  • Cable connection integrity