The Internet of Things (IoT) has transformed how organizations interact with the physical world and their customers by connecting physical devices to the digital world. The data volumes and velocities involved in IoT implementations are staggering. Managing all that data and getting actionable from it is critical to the operational success of every organization engaged in IoT activities.
Panopticon Streaming Analytics enables organizations to process, manage, monitor, and analyze the incredible volume of real-time information streaming in from connected devices, vehicles, equipment, and sensors in the fast-evolving IoT world.
- Extract actionable insights from IoT data in real time – before it loses operational value
- Connect to and manage data flows from numerous, disparate streaming and static sources
- Give users who must resolve operational problems – and who understand what the organization is trying to achieve – the ability to design and deploy analytical user interfaces and directed data flows without dealing with costly, time-consuming custom development projects.
Streaming Analytics for Multiple IoT Applications
Application areas for Panopticon in IoT environments vary widely and include:
- Automotive (including connected and autonomous vehicles)
- Manufacturing (quality control, theft prevention, production planning)
- Energy (grid and smart meter monitoring, oil & gas drilling, capacity management)
- Logistics (quality of shipment conditions, item and storage incompatibility detection, fleet tracking, vehicle and machine autodiagnosis, air/temperature/ozone monitoring)
- Transportation (environmental monitoring of cargo, smart intersections, traffic management)
- Retail (proximity-based messaging, shopping behavior analysis, cashierless checkout)
- Telecommunications (equipment monitoring, intrusion detection & security, environmental detection)
- Security (perimeter security control, radiation and hazardous substances monitoring and control, liquid detection, smartphone payments)
Make Informed, Insightful Decisions Immediately Based on Real-Time Data
IoT implementations typically require real-time analytics because, unlike traditional batch-based flows where data is loaded in sets on a scheduled basis (hourly, daily, or whatever), the business requirements are fundamentally different:
- The data is more time-sensitive. People must be able to comprehend operational problems and anomalies based on up-to-the second data. They must be able to make informed, insightful decisions based on that data to resolve issues and take advantage of opportunities quickly – in seconds in some cases. Put another way, a good decision taken in time to make a difference is incredibly valuable, while any decision made too late is worthless.
- There are usually very large volumes of data. Even in cases where each IoT device or sensor generates only small amounts of data at long(ish) intervals, there are typically such large numbers of devices that the system must be capable of processing and displaying millions of data points in useful ways with real-time resolution.
The real power of the Panopticon platform lies in its ability to handle millions of events per second with nanosecond accuracy, combined with incredible ease of use. Engineers, quality control people, and other business users can build mission-critical analytics applications, connect to virtually any data source (including real-time message buses like Solace, Kafka, AMQP, and RabbitMQ, as well as historical data sources including InfluxDB, Hadoop, NoSQL databases, and SQL databases), and begin using the system in a few hours – without writing a single line of code.