For years, false alarms have overwhelmed central monitoring stations. Up to 95 percent of all incoming alerts were false, creating a situation that wasted time, money and led to frayed relationships between the service providers and their customers. Now, advanced, cloud-based artificial intelligence (AI) software is taming the problem.
The change is like night and day. Stations deploying the software report that 90 percent or more of false alarms are filtered out, enabling operators to protect customers’ people and property better. The software handles many of the repetitive tasks involved with monitoring thousands of customer cameras, freeing operators to oversee more complex work.
Here’s a look at some ways this new solution is benefiting both central station operators and their customers.
Better Security
The average operator is exposed to three alarms per minute — each one needing verification and notification of first responders in cases of criminal activity. Those thousands of false alarms received throughout a day limit how much time station operators can spend on genuine activations, and true alarms can be missed. So, reducing the noise of false alerts goes a long way in enhancing customers’ security.
Improved Employee Performance and Morale
Monitoring video camera feeds all day is a demanding job in itself. Add hours of reviewing false alarms and it’s easy to understand why many station operators burn out. False alarm reduction software enables them to concentrate on genuine alerts, providing them with a greater sense of accomplishment, better performance and higher morale.
Reduced Operating Expenses
By retaining experienced employees, central stations reduce the costs of recruitment and training. Also, false alarm fines — up to $500 in some U.S. cities — are typically billed to the central station, leaving management with the difficult choice of charging customers or writing off the fees as a business loss. Integrator-run stations successfully use false alarm reduction software, as do third party or wholesale operations and enterprise organizations managing their video monitoring services.
Also, cloud-based AI software requires no hardware devices at the customer’s site. Initial installation and future upgrades are quickly and remotely integrated with station operating software and customer cameras without incurring on-site installation costs.
Increased Revenue
By providing better service, stations may realize more income through reduced customer attrition. Fewer false alarms leave operators with more time, enabling station managers to add customers without the need to hire more employees or make investments in new equipment and facility space.
And as skilled labor becomes more expensive and harder to find, stations can look to software to help fill gaps. However, AI software is meant to augment, not replace, human operators. Improved station performance may enable managers to seek more competitive service level agreements (SLAs) from customers.
So How Does It Work?
Today’s false alarm reduction software took nearly a decade to create. It’s an expensive and time consuming task to train the software’s neural networks — which mimic the way the human brain learns — to recognize the difference between a person or an animal, blowing leaves or a spider web across a camera lens. During the training process, the software is shown millions of images of people wearing various types of clothing and in different environments. The software’s neural network consists of layered nodes, each examining a portion of an image before calling it a true or false alarm. System accuracy increases as humans correct mistakes. Once deployed, the software continues to learn and improve. Developers also repeat the above process by using vehicles as the subject.
The final product should easily integrate with a station’s existing operating software, as well as with customers’ cameras. The scalable software makes it ideal for any growing station and customer business. Dashboards enable managers to monitor the software’s performance, including its ability to reduce false alarms. Idle cameras are shown, providing the customer with an opportunity to replace a failed device or move an active unit to a better position.
What’s Next?
Research into ways to improve and enrich the AI-based software continues. In the not-too-distant future, expect to see enhancements capable of identifying certain human behaviors likely to lead to criminal activity — before they become a security issue.
Recent developments in artificial intelligence software have largely eliminated false alarms, improved customer security, enhanced the performance and morale of central station operators and enabled monitoring managers to more effectively grow their businesses. It’s a win-win-win solution.
For years, false alarms have overwhelmed central monitoring stations. Up to 95 percent of all incoming alerts were false, creating a situation that wasted time, money and led to frayed relationships between the service providers and their customers. Now, advanced, cloud-based artificial intelligence (AI) software is taming the problem.
The change is like night and day. Stations deploying the software report that 90 percent or more of false alarms are filtered out, enabling operators to protect customers’ people and property better. The software handles many of the repetitive tasks involved with monitoring thousands of customer cameras, freeing operators to oversee more complex work.
Here’s a look at some ways this new solution is benefiting both central station operators and their customers.
Better Security
The average operator is exposed to three alarms per minute — each one needing verification and notification of first responders in cases of criminal activity. Those thousands of false alarms received throughout a day limit how much time station operators can spend on genuine activations, and true alarms can be missed. So, reducing the noise of false alerts goes a long way in enhancing customers’ security.
Improved Employee Performance and Morale
Monitoring video camera feeds all day is a demanding job in itself. Add hours of reviewing false alarms and it’s easy to understand why many station operators burn out. False alarm reduction software enables them to concentrate on genuine alerts, providing them with a greater sense of accomplishment, better performance and higher morale.
Reduced Operating Expenses
By retaining experienced employees, central stations reduce the costs of recruitment and training. Also, false alarm fines — up to $500 in some U.S. cities — are typically billed to the central station, leaving management with the difficult choice of charging customers or writing off the fees as a business loss. Integrator-run stations successfully use false alarm reduction software, as do third party or wholesale operations and enterprise organizations managing their video monitoring services.
Also, cloud-based AI software requires no hardware devices at the customer’s site. Initial installation and future upgrades are quickly and remotely integrated with station operating software and customer cameras without incurring on-site installation costs.
Increased Revenue
By providing better service, stations may realize more income through reduced customer attrition. Fewer false alarms leave operators with more time, enabling station managers to add customers without the need to hire more employees or make investments in new equipment and facility space.
And as skilled labor becomes more expensive and harder to find, stations can look to software to help fill gaps. However, AI software is meant to augment, not replace, human operators. Improved station performance may enable managers to seek more competitive service level agreements (SLAs) from customers.
So How Does It Work?
Today’s false alarm reduction software took nearly a decade to create. It’s an expensive and time consuming task to train the software’s neural networks — which mimic the way the human brain learns — to recognize the difference between a person or an animal, blowing leaves or a spider web across a camera lens. During the training process, the software is shown millions of images of people wearing various types of clothing and in different environments. The software’s neural network consists of layered nodes, each examining a portion of an image before calling it a true or false alarm. System accuracy increases as humans correct mistakes. Once deployed, the software continues to learn and improve. Developers also repeat the above process by using vehicles as the subject.
The final product should easily integrate with a station’s existing operating software, as well as with customers’ cameras. The scalable software makes it ideal for any growing station and customer business. Dashboards enable managers to monitor the software’s performance, including its ability to reduce false alarms. Idle cameras are shown, providing the customer with an opportunity to replace a failed device or move an active unit to a better position.
What’s Next?
Research into ways to improve and enrich the AI-based software continues. In the not-too-distant future, expect to see enhancements capable of identifying certain human behaviors likely to lead to criminal activity — before they become a security issue.
Recent developments in artificial intelligence software have largely eliminated false alarms, improved customer security, enhanced the performance and morale of central station operators and enabled monitoring managers to more effectively grow their businesses. It’s a win-win-win solution.
