DataScience.US
A Data Professionals Community

Edge-to-Enterprise IoT Analytics

Cisco estimates 50 billion devices will be connected to the Internet by 2020 and 500 billion devices by 2030. These devices generate data that analytic applications need to collect, aggregate and analyze to deliver informed, actionable insight.

25

The challenge is to build the right digital infrastructure and enable the right set of applications to harness this data. Traditional computing models send the data to the enterprise data center for analysis. This is impractical in many scenarios given the volume of data being produced and the requirement for real-time analysis and response times, often measured in milliseconds.

As a result, a new model for analyzing data at the edge of the network has emerged. This model moves the analysis and response close to the devices generating the data minimizing latency and reducing the load on the network and the enterprise data center.

Let me give you a few industry vertical use cases:

Smart Energy:  The Smart Grid, regarded by many as the next generation power grid, uses a two-way flow of electricity and information to create a widely distributed and automated energy delivery network that is safer, more reliable and more efficient, offering substantial benefits for both utilities and customers. Data collected by the devices are used to analyze and understand the energy consumption patterns and adjust the corresponding energy delivery, resulting in greater operating efficiency and environmental goals

Connected Automobile: The automotive industry is entering a period of profound change. Autonomous vehicles are close to reality using advanced machine-learning, powered by IoT data. Vehicle-to-vehicle and vehicle-to-infrastructure communications are being developed taking advantage of unified, secure network connectivity enabling transmission of real-time vehicle telematics, GPS tracking and geo-fencing, improving safety, mobility and efficiency, and proactive maintenance which decreases costs and vehicle downtime.

Smart Manufacturing: Smart Manufacturing solutions provide intelligent, timely information and collaboration that improves the quality of products and the efficiency with which they’re built. Smart Manufacturing enables continuous improvement of productivity through integration of Six Sigma DMAIC processes (Define, Measure, Analyze, Improve and Control). It also enables more accurate forecasts of product demand, greater visibility into supplier quality level, improved preventative maintenance, better asset management and safer factories.

The Edge-to-Enterprise solution announced today is designed, tested and validated by Cisco and SAS, and has three major tiers: Edge, Transfer and Enterprise

  • Edge –  Analytics at the edge means understanding the local context and sending only the important information back to the enterprise. In this case, Cisco 829 Industrial Integrated Services Routers are used. They are designed for deployment in harsh conditions and are running the SAS Event Stream Processing (ESP) client software. The combination enables collecting millions of events per second, filtering the data, analyzing it and detecting patterns of interest in real-time. The output of the analysis defines what alerts to issue, and which data to store and route forward. The Cisco Fog Director Software simplifies the deployment and management of applications and models on the edge routers. Cisco Fog Director is deployed on Cisco UCS C-Series Rack Servers or the Cisco UCS Mini. Advanced data protection and compliance are enforced by Cisco 3000 Series Industrial Security Appliances and Cisco Firepower 4100 Series Firewall appliances.

Continue Reading

Comments

This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Accept Read More

X