Spark New Zealand is advancing its IoT Control Center platform powered by Cisco with new features to help businesses improve service reliability and reduce operational costs using machine learning and artificial intelligence.
IoT deployments generate vast amounts of data per day, making it impossible for enterprise customers to personally monitor their IoT deployment and catch issues when they arise. This can lead to larger problems impacting service reliability, increasing cost, and compromising security.
Cisco is solving this challenge for Spark with two new modules added to the Cisco IoT Control Center connectivity platform that use advanced proprietary machine learning algorithms to process massive amounts of data in near real time for its enterprise customers. New modules include:
- Anomaly Detection: monitors each enterprise customer independently and trains itself on the device’s behaviors to determine what is normal and what is abnormal, flagging any anomalies, allowing the customer to review and address potential issues as quickly as possible.
- Cost Optimization: analyzes the entire device deployment and determines the optimal rate plan for each device based on actual data usage for the current billing cycle, saving enterprises up to 15% off their typical connectivity costs.
Tony Agar, Spark IoT lead
By adding these enhancements to Cisco IoT Control Center, we continue to strengthen our IoT capabilities to reduce customer operational and billing issues and enhance our value to enterprise customers. Through our partnership with Cisco we are able to help businesses become more productive, resilient and sustainable through innovative technology.
Masum Mir, Vice President and General Manager, Cable, Mobile and IoT, Cisco
Spark continues to differentiate itself by driving innovation to help its customers realize the full potential of IoT to help lower costs, and automate services. With these advancements to Cisco IoT Control Center, Spark enterprise customers can detect and address potential issues with their IoT deployments as early as possible, simplify cost management and minimize unexpected charges.
