The Internet of Things (IoT) has gained much momentum as a means of retrieving data for use, via the Internet, in predictive analytics and big data analysis.
Such data aggregation is making great strides in the trucking industry, where fleet management stands to benefit handsomely from IoT and the data and information it provides to fleet managers and supply chain leaders.
Greater Overall Efficiency
For trucking, IoT started out with local sensors on the truck or asset picking up data such as speed, fuel consumption, odometer readings and other information. The data would then be manually downloaded and processed on some periodic basis. Now, however, fleet trucks are outfitted with computers, antennas and more sophisticated sensors that send data wirelessly back to a central location where others can see the data in real-time. With asset management software it can be processed within an IoT platform, and key analytics may be provided to management. This allows the management and monitoring of many details including driver performance, speed optimization, route planning, idling and other operations to achieve greater overall efficiency.
According to a Wall Street Journal article, Siaia LTL Freight utilizes an IoT configuration to monitor parameters related to its fuel consumption, and were able to improve fuel efficiency by 6% and save about $15 million in its first year of IoT operation. For the logistics industy, IoT is estimated to rise to$1.9 trillion in value over the next ten years or so in the United States - and an overall $8 trillion in IoT value generated globally, according to the 2015 DHL and Cisco Internet of Things Trend Report.
Additionally, drivers can utilize a customized app on their mobile phones that allows them to log in data while enroute, that is transmitted back to a central location for additional processing. Everything from geographic location, cargo information, license and permitting information - all can be entered via the app and transmitted for multiple purposes. It allows fleet managers to be more efficient and better manage the details of their operations.
Asset Management and Optimiziation
Gathering volumes of data via IoT enables cognitive computing, or the simulation of human thought processes via the power of computer processing. This is the same type of computing used in developing humanoid robots and designing computers to play and win on the television game show Jeopardy! It involves data mining, natural language processing and other complex computing technologies to drive predictive analytics.
For the trucking industry, there is no limit to the many things that such analytics can provide. When data that sensors retrieve is processed by software such as IBM Maximo Asset Management - an enterprise asset management (EAM) software solution - any organization can actually engineer how they would like to manage their fleet assets. They may also use this in concert with an IoT technology such as Watson IoT Platform. They may create applications used for fleet operations as well as maintenance, hazardous material transport, hazardous waste disposal, and so many others.
Great Outcomes to Come
Not only can the cognitive analytics be fed into smart algorithms that optimize routes using programs such as IBM ILOG - software used in optimization and modeling - but it may also used in other applications like aiding in the computing of truck loading information and synchronizing with cargo and other logistics data to give the supply chain a boost of efficiency. IoT on fleet assets allow them to be used as smart tags, RFID and other devices used to transmit and process data.
In an article in SupplyChain24/7, IoT is suggested to not only link the supply chain together, but also help retain drivers - a continuous challenge to the trucking industry - but also as a means of tackling cumbersome paperwork. It helps drivers with the burden and drudgery of paperwork required of their jobs. As a result, they will have more available time, and can be on the road delivering their shipments.
Overall, IoT has made great strides for the trucking industry and the entire logistics industry as well; still, it has many miles ahead of it. Cognitive analytics made possible by IoT, optimization software and asset management software acting all in concert, will produce remarkable results in years to come as the transportation industry comes of age in the new and emerging era of technology. Big data computation and the predictive and cognitive analytics it provides, is not mature yet. There is more, much more, and many great outcomes yet to be realized.