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IoT, Fog Computing and Real-time Transportation Management

 

How can the Internet of Things assist in dramatically improving transport across the world? Let's take a look at fleet management, and how fog computing can reduce inefficiencies at scale.

 

Challenges for Transportation Fleets  

Many problems for transportation fleets exist with or without IoT.  However, with IoT, problems can be managed, reduced, and resolved much more efficiently.  Regarding the technology itself, the expansion of IoT and its critical mass is driving the need to constantly develop and deploy new IoT solutions.  Trucking fleet issues include sleepy drivers, traffic, road hazards, fuel inefficiency, and mechanical breakdown.  Climate changes and global warming present the need to implement environmentally-friendly initiatives.  As the number of self-driving cars increases, drivers will need enhanced vehicle-to-vehicle communication abilities. Cities are installing their own IoT systems, and fleets will need to modernize to stay connected. All of these problems require on-board computers and the corresponding systems and applications to make it all work – i.e., the IoT.

 

How IoT is Used With Transportation Management

 

prx_train_back.jpg

 

Managing a fleet of vehicles fits into a computer system of any kind, even without IoT, because it is a process that easily lends itself to abstraction, geometry, algebra, and statistics.  For example, preventive maintenance is well-suited to predictive data, as seen in this Apache Spark machine learning on brake pad maintenance. The IoT-enabled trucks can collect information on brake pads, truck mileage, and rotor heat to predict when the brake pads should be changed.

 

 So, drivers already understand the importance of analysis and are familiar with the tools of optimization. With IoT, fleet managers can track truck machinery, driver safety, and adherence to policies.  This puts the dispatcher in the field with the driver, figuratively speaking, allowing decisions and resolutions to be made in real-time. 

 

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Fog Computing on Vehicles

As the possibilities for IoT and transportation are near-endless, let’s narrow our look to just one of the main ways IoT can empower global transportation business: reducing inefficiencies.  We’ll use fleet management as a specific business and fog computing (the operations between physical devices and cloud data centers) to show how the IoT can reduce inefficiencies at scale.

 

Key to understanding the challenges of effective fleet management are dead zones, areas where there is no cellular coverage. Without a signal, data from the vehicle cannot be communicated to the cloud. However, it is not necessary to consult the cloud for every change on the vehicle and/or the truck’s designated route.  Many operations on a vehicle are best handled by the driver and local systems, e.g., a failed brake, flat tire, and the need to go around traffic/hazards.  IoT and fog computing ensure the vehicle can make decisions as needed, in real-time and later, once free from the dead zone, sync with the cloud and update the global fleet manager’s view.

 

IB, on the Open Fog Consortium, explains:

 “The growth in IoT is explosive, impressive – and unsustainable under current architectural approaches. Many IoT deployments face challenges related to latency, network bandwidth, reliability and security, which cannot be addressed in cloud-only models. Fog computing adds a hierarchy of elements between the cloud and endpoint devices, and between devices and gateways, to meet these challenges in a high performance, open and interoperable way.”

 

As we’ve seen with just these few examples, fog computing, when utilized by transportation enterprises, has the potential to fix and prevent mistakes that are made when devices and their resources are incorrectly deployed to the cloud. This system brings decision-making closer to the computing endpoint and saves time, energy, and other resources.  IoT and the real-time solutions it offers is a natural fit to mobile fleet management systems.

 

 

Watch relayr's Train Demo