![]() The data represents many use cases, device types, and device behavior patterns, giving you more accurate insights about potential service or security issues. We continuously train IoT Control Center Anomaly Detection with data from 220+ million IoT devices that have connected to IoT Control Center since 2018. The accuracy of anomaly detection depends on the volume and variety of data used to train the machine learning model. What’s unique about IoT Control Center Anomaly Detection Visualize anomalous behavior and trends by geography, device type, rate plan, and more. ![]() Helps you troubleshoot affected devices by providing details such as:.Helps you focus effort where it’s most important by grouping anomalies by severity (critical, major, minor).Detects anomalous device or network behavior-for example, a spike in activity at unusual times-and swiftly alerts your CX team.Uses AI/ML to analyze your network’s data consumption and device connectivity patterns over months to understand normal behavior.Consider it if you have customers with 10,000+ devices, maintain a dedicated CX team, or want to earn more managed services revenue. IoT Control Center Anomaly Detection is built for CSPs who want to deliver a superb customer experience for their high-value IoT customers. Identifying outlier events early and taking swift action are required-delays in detecting and resolving issues alienate customers and increase support costs and customer credits.Įarly warning system pinpoints hidden service and security issues But if the 0.2% of devices are offline, say all of their delivery trucks, or all devices in a small region, there can be a significant impact to business. For example, suppose a summary report shows that 99.8% of a particular customer’s 100,000 devices are online. Sustaining your IoT business requires keeping support costs down.īut when you serve customers with 10,000 or 100,000+ devices-Electric Vehicle (EV) chargers, smart meters, connected vehicles, rented power tools, and more-potential service and security issues can remain hidden in massive amounts of data. Spotting connected device issues-needles in haystacksīuilding a sustainable IoT business requires providing a superior customer experience, including high service reliability, device security, and cost management. Avoid having to issue credits to appease customers whose bills include unexpected data charges. Reduce manpower spent on monitoring-it’s automatic. Receive detailed alerts about suspicious behavior so you can pinpoint affected devices and take the right action to protect your customers’ assets, information, and business. ![]() Prompt action helps to avoid service issues or unexpected customer data charges. Discover unusual activity that typically escapes notice. It helps your CX teams deliver white-glove service by pinpointing issues hidden in massive amounts of device and connectivity data so you can resolve them quickly-before they affect customers’ business. Delays in detecting anomalous activity can lead to service disruption, security breaches, and unexpected data charges that chip away at customer loyalty.Ĭisco IoT Control Center Anomaly Detection uses an AI/ML-based early warning system for potential issues affecting your customers’ IoT devices and connections. The problem? Summarized reports can mask anomalous activity for, say, a particular device type or region. That’s tricky for customers with tens of thousands of Internet of Things (IoT) devices. To rise to the challenge, Communications Service Providers (CSPs) are forming Customer Experience (CX) teams to detect and resolve service and security issues before they disrupt the customer’s operations. Meet both goals with Cisco ® IoT Control Center Anomaly Detection, our early warning system for issue troubleshooting and resolution.Įnterprise IoT customers have high expectations for service reliability. Keep high-value customers happy with proactive supportīuilding a sustainable IoT business requires providing a superior customer experience- while keeping costs down.
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