Real-time device tracking has become essential for today’s intelligent IoT devices. In numerous applications, including telematics, security, smart cities, and health care, real-time tracking quickly identifies emerging issues and boosts situational awareness. Unfortunately, most streaming analytics platforms perform limited analysis in real time and do not track individual devices.
This talk describes how software technology for in-memory computing can address this challenge. Using the digital twin model, this technology can independently track and analyze millions of IoT devices, provide feedback in milliseconds, and continuously visualize aggregated statistics every few seconds. The digital twin model enables fast processing of incoming telemetry by maintaining immediately accessible state information for each IoT device. It also simplifies application design with object-oriented techniques and enables transparent performance scaling.
Join us to learn about the next generation in streaming analytics for IoT using in-memory computing and digital twins.
11:30AM - Day 1