Edge Computing Brings Critical Insights to IoT Enterprises

More devices, more data, more problems

With the greater number of connected devices in operation, the sheer volume of data being collected is astronomical. Capturing, aggregating, and analyzing data becomes a greater challenge. Not all data is useful, yet some time sensitive data such as autonomous vehicles, noxious gas monitoring, healthcare, safety equipment, and other scenarios are at risk. A split-second delay of data going to the cloud and back to the device could be disastrous or deadly. Other data sites face the challenge of location where the use of IoT in rugged environments such as an offshore oil refinery, underground mine or deepwater well can result in unstable links with limited bandwidth and variable latency. 

The solution is edge computing – or an edge/cloud hybrid model where time-sensitive data is processed at the edge and less urgent analytics can be determined in the cloud. Edge changes possibilities and enables new scenarios that are/were not possible/effective with cloud processing. Connected Industry is paying attention, and a 2015 report by IDC forecasts that by 2019 45% of IoT created data will be stored, processed, analyzed and acted upon close to or at the edge of the network. 

Scalability and cost reduction in wind farming

Edge computing is fundamentally ‘distributed computing’, meaning it improves their saliency, reduces network load, and is easier to scale.According to researchers, Wikibon, a typical wind farm was embedded with security cameras and other sensors with a distance of 200 miles between the wind farm and the cloud. Through processing data and the edge transmitting summary data to the cloud, they reduced traffic flow by 95% and reduced the cost of management and processing to $29,000 from $81,000 over three years. 

Real-time data insights