IoT in Logistics: Deciding between Edge vs. Cloud Computing Analytics

IoT in Logistics: Edge vs. Cloud Computing Analytics

When it comes to logistics analytics, which is best for connectivity: edge computing, cloud computing or a mix of the two?

Written by Crystal Bedell
8th August 2019

Difficulties still have to be overcome when analyzing data at the edge. Whether the gateway is running simple threshold rules or a predictive model, organizations need a way to deploy and manage the analytics. “To be able to do that without it becoming an arduous task, you need to be able to access the gateway remotely as well as deploy those models in a structured, automated manner,” Riley said. “Deploying that many predictive models to the edge without automation is a cumbersome task requiring dedicated staff.” For a regional provider with 150–250 trucking assets, the lack of automation could tip the cost-benefit equation in an unfavorable direction, he said.

Going to the Cloud

Just because a use case leverages the edge, doesn’t mean that the cloud is out of the picture. According to Riley, sending the data to the thin edge reduces data transmission to the cloud by 99.8%, enabling organizations to economically leverage the cloud for more advanced use cases.

“When you use the thin edge, you always use the cloud or an on-prem central datacenter. You want to get a hold of all that data that is on the edge device because predictive models take care and feeding, and they have to be changed over time because of the refinement of them or changes in the operating parameters of the pieces of equipment that are being used. You want to obtain that data so that you can change those parameters or perform prescriptive analytics,” Riley said.

The cloud offers efficiency of scale as well as advanced capabilities needed to perform these tasks. “There are much better capabilities to extract insights out of the data in the cloud. A lot of the machine learning today takes place in the cloud, and all the training is happening in the cloud,” Schallehn said.

“Many organizations are moving a lot of business workloads to the cloud because cloud computing becomes a workhorse for those organizations to analyze vast amounts of data, to gather insights from the data, do some form of machine learning and act on that data and send to relevant devices or apps that the organization is using. So, cloud computing does play a critical role in organizations getting the maximum benefit of their IoT,” Sastri said.