2475

Get a Live Demo

You need to see DPS gear in action. Get a live demo with our engineers.

White Paper Series

Check out our White Paper Series!

A complete library of helpful advice and survival guides for every aspect of system monitoring and control.

DPS is here to help.

1-800-693-0351

Have a specific question? Ask our team of expert engineers and get a specific answer!

Learn the Easy Way

Sign up for the next DPS Factory Training!

DPS Factory Training

Whether you're new to our equipment or you've used it for years, DPS factory training is the best way to get more from your monitoring.

Reserve Your Seat Today

Dealing with Nuisance Alarms

The function of a network alarm management system is to inform you of events that threaten the network so that you can take corrective action. Ideally, the system stays quiet until an event that requires human intervention occurs.

But what happens when your system constantly bombards your staff with status events or non-alarms that require no action other than an acknowledgement? Your staff becomes desensitized to alarm reports, and they start to believe that all alarms are nonessential alarms. The staff stops responding to critical alarms, defeating the function of the alarm management system.

T/Mon Alarm Notification

These self-defeating, nonproductive alarms are called nuisance alarms, and they can have devastating effects.

But your network monitoring system doesn't have to play the boy who cried wolf. Advanced monitoring systems have many features that can reduce or eliminate nuisance alarms.

Do you really need to know about all alarms?
The first thing to determine is whether the alarm is needed at all. If the alarm is simply a status indication and no action is ever required, you may want to turn the point off by setting it to "No Log". You can still have the alarm report go to your history file for future data analysis.

Or it might be that the alarm by itself is not relevant, but it is important when occurring in combination with other alarms. In this case, you can use a derived alarm feature to report that alarm only in that circumstance. Keep in mind that one of the circumstances could be that the condition is only an alarm on a given day of the week or time of day.

If problems are self-correcting, there might not be a need to know something happened if it has already been fixed. You can filter these alarms by using an alarm qualification time that says the condition must be in existence for a given number of minutes before an alarm is declared. You may want to use alarm qualifications for things like power failures, fades, etc. There is also a more powerful alarm qualification feature that will alert you when an alarm point fails more than a given number of times in a specified time period.

Enough already, I hear you
Now, let's assume that you have a point that must be monitored, but unfortunately it enters an oscillating condition that creates a lot of alarm activity. In this case you would want to use an "alarm silencing" feature that turns off that alarm point for a specified amount of time. This saves you time because if you already have taken action to fix the problem or scheduled a correction time for the problem, there is no need to be continuously reminded of the problem.

Enhancing Alarm Management with AI Integration

While traditional methods for managing nuisance alarms rely on filters, silencing features, or alarm qualifications, integrating artificial intelligence (AI) into your network monitoring system is the next step. AI-powered monitoring tools analyze alarm patterns and predict the likelihood of recurring issues. These processes allow for proactive rather than reactive management.

Here's how AI can transform your alarm management process:

  1. Dynamic Alarm Thresholding
    AI systems can automatically adjust alarm thresholds based on historical data and real-time environmental conditions. For example, if your system detects an increase in temperature during summer months, AI can set higher alarm thresholds for heat-sensitive equipment, reducing unnecessary alerts.
  2. Root Cause Analysis
    When multiple alarms are triggered simultaneously, identifying the root cause can be overwhelming. AI algorithms can cross-reference alarm patterns with historical incidents to pinpoint the source of the issue. This reduces response times and makes sure that your team addresses the underlying problem.
  3. Anomaly Detection
    By monitoring normal operating patterns, AI can flag anomalies that may not yet be critical but indicate developing issues. These early warnings allow for preventive maintenance, minimizing the risk of major outages or failures.
  4. Smart Notifications
    Instead of bombarding your team with every alarm, AI prioritizes alerts based on severity and the potential impact on your network. It can also direct notifications to the most relevant personnel, allowing for efficient resource allocation.
  5. Learning Over Time
    AI systems continuously learn and improve as they process more data. This means your alarm management system becomes increasingly adept at distinguishing between critical issues and routine noise. This effectively eliminates false alarms over time.

Implementing some or all of these strategies will cause your system to run quieter and become easier to manage... provided it's a system advanced enough to handle the strategies mentioned above.