IoT in Logistics: Edge vs. Cloud Computing Analytics

The Internet of Things is giving the trucking and logistics industry the visibility it needs to improve efficiency and safety. However, like any technology, IoT deployment decisions must be driven by a cost-benefit analysis. That includes the decision of which analytics types should be at the edge or in the cloud.  

Sensors in an IoT deployment can generate reams of data, and that data has to go somewhere to be analyzed. “You can send the data to a cloud instance or a centralized on-premises data center, but that requires data transmission, and when you’re looking at the transportation industry, there are a lot of areas where data transmission over cellular or satellite becomes prohibitively expensive or the connectivity just isn’t there,” explained Sean Riley, global industry director for manufacturing & transportation at Software AG.

Connectivity is a pretty black and white issue — either you have it, or you don’t. Cost is a little more nuanced. Organizations should consider how much data their devices generate. 

“If devices are sending redundant information, it doesn’t make sense to continually send that to the cloud. It will eat up your cellular bill,” said Suneil Sastri director of product management at SOTI. “That’s the general challenge with IoT. If you look globally, we’re looking at 75 billion endpoints by 2025 that will create somewhere around 163 zettabytes of stored data. It’s really critical for organizations to rein that in so that they’re not experiencing costs in respect to storing and transmitting that data,” he said.

The edge can help relieve some of those costs, whether the use case is monitoring cargo temperature to maintain the integrity of the cold chain, assessing cargo space to minimize the transportation of dead space, or detecting wear and tear on the vehicle to improve truck maintenance.  

Thin Edge vs. Thick Edge

When it comes to the edge itself, some experts differentiate between the thin versus thick edge. The thick edge, Riley explained, is when compute is performed on a server that’s on the transportation asset. “It can do more than the thin edge because it has significantly more computing power,” he said. 

However, the thick edge also requires more physical space. “You won’t put a server on a truck. But if you’re talking about container shipping, there’s plenty of room on the freight liner to put a server somewhere in there,” Riley said. 

The thin edge is used for the majority of IoT use cases in trucking. In this scenario, a computing device or “gateway” sits on the truck or another asset. Instead of sending data directly over a cellular network, the sensors send all data to this device. “A compute device aggregates data from the different endpoints, computes the data and performs tasks such as machine learning or artificial intelligence, and in a much faster, almost real-time way compared to what the cloud is able to do because it is closer to where the data is being generated,” said Michael Schallehn, partner and IoT expert, Bain & Company.