By R. Bruce Striegler

“While I am going to focus on the ‘less than truckload’ transportation segment, hopefully you will see parallels to other transportation sectors like container shipping or full truckloads,” says John Maley, IBM’s global freight logistics leader. In the spring of 2015, IBM announced an investment of $3 billion in a new business division to establish an Internet of Things (IoT) unit. The Internet of Things refers to the growing network of sensors, communications and control interfaces, and applications platforms, on everything from smartphones to jet engines, allowing pre-programmed actions to occur continuously, or when predetermined triggers are exceeded. Instead of an Internet of connected computers, it’s an Internet of connected devices (or things) broadcasting amazing amounts of data. This cloud-based open platform is designed to help clients build IoT solutions, and IBM hopes this initiative will put the company at the forefront of a rapidly emerging new technology sector. The company will provide a common platform on top of which customers can build useful applications to take advantage of all that data.

In a recent Journal of Commerce webcast, two senior members of the IBM Internet of Things team explained the initiative. John Maley began by presenting a scenario that followed “a day in the life” of a freight pallet being shipped by truck from west coast to the east coast of the U.S. Maley details the multitude of steps of authenticating and documenting actions that occur on this transcontinental drive. Collection of data begins the instant a driver picks up the pallet. Along with photographs taken at various stages of the trip, the electronic data is submitted to a central digital platform. Monitoring and verifying the progress of the shipment is now so sophisticated that the system can detect road hazards or severe weather issues and provide re-routing information to the truck driver. On-board sensors monitor and “report” shifts in a freight load or temperature variations. The advanced process of IoT can even detect (in advance) when a previously-designated freight dock is in use and provide information to the truck driver on alternate delivery docks.

Also called ‘hyperconnectivity’, the Internet of Things is today’s new reality. This degree of hyperconnectivity is increasing the digital interconnection of people, and things, anytime and anywhere. Commercial wireless signals already cover more of the world’s population than the electrical grid, and the number of connected devices around the globe is expected to hit from 50 billion to a staggering one trillion in the next five years. This level of connectivity will have profound social, political and economic consequences, and increasingly form part of our everyday lives. The impacts will be felt through the cars we drive and medicines we take, to the jobs we do and the governance systems we live in, to even the business technology systems we use. This new era brings with it an acceleration of innovation and disruption. Across every industry, companies are discovering new audiences, creating new revenue streams, building new ecosystems, and inventing new business models – all online, all at an unprecedented pace. The Internet has evolved from being “nice-to-have” to an additional channel for growth and innovation.

John Maley says that from his made-up journey, one can see the immense volume of information that can be available from the Internet of Things but, “The bigger challenge is converting the vast amount of data that these technologies produce into information, then insight. IBM has and continues to invest in analytics and big data solutions to do just that; convert data to information and insight.”

In his highly-technical session, Tim Meyer, an associate partner at IBM Global Business Services, IoT Center of Competence, outlined mechanical and other technical specifications required to connect to the network so as to operate and benefit from a fully-functional Internet of Things. IBM estimates that 90 per cent of all data streams generated by devices such as smartphones, tablets, connected vehicles and appliances is never analyzed or acted on. As much as 60 per cent of this data begins to lose value within milliseconds of being generated. Mr. Meyer closed his presentation with a case study of a U.S.-based global mining equipment service provider using predictive analytics to prevent costly machine downtime. “Collecting and analyzing data through the Internet of Things is very much applicable to preventative repairs or maintenance. Millions of dollars may be saved if the mining company spots problems before they can interrupt production.” He says that a big data and analytics solutions pull in and integrate vast volumes of data from multiple sources, including streaming equipment sensor data. “If it detects a problem when analyzing the data, it sends alerts and optimized service recommendations to field technicians on their iPads so that they can make immediate repairs. This happens in near-real time, so the company can dispatch service personnel to the site before the machine operator ever sees a problem.”

IBM’s team says with new industry-specific data services and developer tools, the company will build on its expertise to help clients and partners integrate data from an unprecedented number of IoT and traditional sources. “We are offering companies ways to make use of the new and multiplying sources of data such as building sensors, smartphones and home appliances to enhance their own products.” One of the company’s first partnerships with the IoT unit was the Weather Network, which moved its data onto IBM’s servers so customers can use the data in tandem with the analytics tools that IBM provides. IBM is hoping that companies will be able to combine live weather forecasting with a range of business data, so businesses can quickly adapt to customer buying patterns or supply chain issues connected to the weather. “For example, insurance companies could send messages to policyholders in certain areas when hailstorms are approaching and advise them of safe places to park, preventing claims. Or retail stores could compare weather forecasts with past data to predict surges or drops in customer buying due to extreme weather, and to adjust staffing and supply chain logistics accordingly.”