#IndustrialIOT is a trend from decades that enabled thousands of Industries to collect and store data from their assets. Utilization of these data to extract information is a crucial part.
#EdgeAnalytics is an approach to extract information from data on the premises either on Sensor Nodes, Gateways or Local Servers instead/before performing analysis on cloud/Centralized server end. Providing real-time analysis of cyber-physical devices in a network.
Edge analytics has gained attention as the Industrial Internet of Things (IoT) model of connected devices has become more prevalent. In many organizations, streaming data from #manufacturing machines, industrial equipment, pipelines and other remote devices connected to the #IoT creates a massive glut of operational data, which can be difficult -- and expensive -- to manage.
Credence Robotics' Alphonso Industrial Gateways are powerful enough to make to host Real-Time edge #analytics on-device meanwhile beaming data collected from 200+ Wireless Sensor Nodes to a Server/Cloud via Various Communication channels like: Ethernet (IEEE 802.3), Wireless LAN (IEEE 802.11 b,g), SigFox, GPRS and 4G.
How does Edge Analytics Benefit You ?
Decrease Latency & Downtime: Analyzing data as it is generated can decrease latency in the decision-making process on connected devices.
Gain valuable insights: Analyzing data On-premises gives insights of your device performance which helps you in optimizing Quality and enhance production.
Overcome information overload: Edge analytics systematically analyzes #data to make you understand issues of your device and helps taking effective decisions when you have too much Data.
Reduce operations costs and increase #performance through Alphonso predictive maintenance.
When Should you consider Edge Analytics ?
Even though edge analytics is an exciting area, it should not be viewed as a potential replacement for central data analytics. Both can and will supplement each other in delivering data insights and both models have their place in organizations.
One compromise of edge analytics is that only a subset of data can be processed and analyzed at the edge and only the results may be transmitted over the network back to central offices. This will result in ‘loss’ of raw data that might never be stored or processed. So edge analytics is OK if this ‘data loss’ is acceptable.
If the latency of decisions (& analytics) is not acceptable as in flight operations or critical remote manufacturing/energy, edge analytics should be preferred.