What you need to prepare for the year 2020.
The IoT may have as great an impact on transportation as the invention of shipping containers and overnight delivery.
Seismic shifts in technology can drive certain companies out of business. For example, when the first two international airlines (Pan Am and TWA) could not adapt to deregulation and the resulting drop in air fares, they went bankrupt. Shifts like these usually leave vacancies for modern businesses to fill.
Market forces usually require transportation companies to regularly seek out new ways of lowering costs and staying competitive. Inefficient operators are outshined by their competitors. Globalization exposes carriers and fleet operators to new levels of competition from low-cost rivals in neighboring regions.
With profit margins at their lowest points, the companies surviving today will allegedly be among the first to use the IoT and big data to optimize operations.
Let’s look at the specific items transportation companies can quantify to improve overall efficiency. For now we’ll focus on truck fleet operations, but the ideas presented also apply to passenger and cargo airlines, taxis, buses, ocean shipping, and local delivery vans.
Trucks are the perfect IoT business use case as there is a consistent need to monitor vehicles on roads from central locations. The tools to do this include the IoT cloud, big data databases, analytics, the ERP system, onboard sensors, and wireless communications.
There are several metrics to measure on a moving truck. Intel says the average heavy truck generates 10MB per kilometer of data.
The IoT serves several goals. First, it offers preventive maintenance to ensure vehicles remain in service. IoT solutions can also change delivery routes in real-time to meet shifting customer requirements, road conditions, and other factors. They’ll also ensure vehicles consistently operate safely, conserve fuel, and adhere to environmental emissions regulations.
Manufacturers already ship many of their machines and devices with the IoT on board. Rolls Royce for example, monitors engines for customers, while Goodyear and other tire makers put RFID chips into their tires.
Fleet operators themselves can locate GPS, heat, humidity, vibrations, and other sensors on brakes, engines, refrigerated trailers and lights. Data gathered is uploaded to the IoT cloud using cellular connections.
How do fleet operators use this data?
The biggest change we can expect in fleet operations is the advent of big data and analytics software through the cloud. This lets trucking companies process streaming and unstructured data and run algorithms accordingly. The output of this analysis creates work orders in the ERP system, sends notifications to drivers, and allows dispatchers and managers capture what is occurring in real-time on dashboards.
But what does all this mean?
Well, consider the situation from ten years ago. Trucking companies used satellites to upload data and download metrics manually from vehicles. Data was loaded into warehouses so BI (business intelligence) could be run, but these processes took excessive amounts of time, rendering operations relatively inefficient in the long run.
Now, open-source databases like Spark, Storm, Kafka, and Hadoop allow companies to process data in real-time and require little-to-no conversion periods. Also, companies no longer require statisticians, as statistical models are built into programming languages that allow programmers and end-users alike to gain insight from data. For enterprises without programmers, cloud companies exist to do this work for them.
Consider the classic transportation problems taught in business schools. Students are taught to use linear programming and set routes for entire fleets so they can meet customer deliveries while driving the shortest distances. This is how routes are set before big data and the IoT. On-board metrics and the big data cloud can have trucks change courses or routes as conditions change. If a supplier’s warehouse has run out of inventory, or another truck has cracked a brake drum, these problems can be addressed and fixed accordingly.
Another goal is to keep vehicles in operation. 18 wheelers require regular changes to their brake pads. In the absence of the IoT, companies can only do this on fixed schedules. Thus, brakes are changed too often, and money is ill-spent. With the IoT, a company monitors brake rotor temperatures and kilometers driven and uses predictive models to accurately determine when a truck’s brakes need to be changed. Scania trucking company describes the problem here, and here is Spark ML code to show how to run predictive models against brake data.
The IoT also shows which drivers are not operating vehicles safely, and which ones are more likely to damage engines or waste fuel.
There is another factor that will likely force transportation companies to adopt the IoT. No one is discussing driverless trucks yet, though the fleet of driverless passenger vehicles is consistently growing. Cars will be equipped to talk with each other, and trucks will not be left out of the loop.
Highways themselves will be equipped with sensors to report road and traffic conditions and several cities are already streaming data on traffic conditions along with crowdsourced applications like Waze.
Trucking and transportation companies need to prepare for the IoT now. Otherwise, they risk losing their competitive edge and having IoT technology forced upon them when they aren’t ready. Manufacturers are already building the IoT into their machines; trucking companies can tap into this data as they build transportation models, and the growth of IoT and big data means standards are emerging to invoke complexity and low-costs for businesses. Companies who choose to embrace the IoT and move forward will emerge victorious, while those who refuse could face threats of permanent closure.