5 Ways AI Will Transform the Logistics Industry
This is a guest story by tech blogger Camille Peters.
Artificial Intelligence (AI) is taking an increasingly central role in the logistics industry. As the world’s logistical requirements continue to become even more complex, big-data driven applications have already stepped in to streamline logistics on a global scale. Supply Chain 24/7 put it best in 2016 when they explained that “The impact of data-driven and autonomous supply chains provides an opportunity for previously unimaginable levels of optimization.” And if the future of digitally-optimized logistics looked bright in 2016, it’s positively ablaze today.
Previously on AltexSoft, we tackled already rampant digitization, which has continued to increase its presence. It has advanced the travel and hospitality industries – but that’s just the tip of the iceberg. Booking trips and ordering goods online are only one part of a huge logistics equation. Now, we’ll take a closer look at some of the AI-powered trends that we can expect to see in the other sectors that make up the supply chain.
Intelligent and Automated Warehousing
In Andover, England, a large warehouse run largely by robots is able to fulfill 65,000 orders (approx. 3.5 million grocery items) over the course of a week. This is the full operational capacity of the “hive-grid-machine” that was designed and built by British online grocer Ocado. The automated and intelligent warehousing system is fully capable of moving, lifting, and sorting grocery items, which are then packaged and sent out by Ocado’s employees.
While the tasks assigned to the bots seem simple enough, their primary mission is to use space as efficiently as possible. Ocado’s warehousing robots can stack stored items up to 17 boxes high. The algorithm that runs the operations places rarely ordered items at the bottom and frequently accessed items on the top. This minimizes the amount of time it takes to complete the majority of the company’s online orders. That’s fully in line with Ocado’s goal to “disrupt itself” – to continually improve its own technology, set the standard for efficiency in the warehousing, logistics, and hospitality industries, and eventually, sell their patented technology to other companies with similar requirements and concerns.
On a broader scale, this coincides with expert predictions that multiple operations in the logistics and warehousing industries will be fully automated circa 2030. Vero Solutions believes that 30 percent of UK warehousing jobs will become fully automated in the next few years, with physical jobs the most likely to be the first candidates for conversion. Next are any operations that involve processing and collecting data – the lifeblood of multiple-intelligence optimization applications.
The end goal of automated warehousing is computer vision. This is where the AI will learn and evolve as it works to improve operations. Computers will soon be capable of recognizing and organizing inventory, and even administrating quality control for a variety of stock without the need for human oversight. If the company has more than one warehouse, the AI in each location will be able to communicate with each other to find the best logistical solutions.
Meanwhile, if you want to learn about the warehouse management features that the logistics industry currently offers, peek at our article describing the main modules of logistics management systems.
Blockchain Can Greatly Improve Supply Chain Reliability and Integrity
It’s no secret that the world’s supply chain regularly deals with problems related to efficiency, reliability, and security. Some experts believe that these issues can be addressed through the application of blockchain technology in key supply-chain transactions. This includes all transactions related to the supply process – from purchase to internal exchanges that include storage, delivery, and auditing.
This is just one of the many practical applications of blockchain explains metrics expert Bernard Marr, author of Big Data in Practice and Key Performance Indicators. Marr explained that the very nature of blockchain technology gives it plenty of opportunities to transform the supply chain and logistics industry for the better. Known primarily as a decentralized digital ledger used for trading cryptocurrencies, blockchain is already being used by several corporations to optimize their own supply chains.
This is possible because of the way blockchain works. Each blockchain transaction is encrypted as an indelible record or block that contains every significant detail about the transaction. This block is instantly copied into the digital ledger of every article that’s included in the chain. Stacked on top of one another, the now immovable blocks form a data “blockchain” that can be cross-referenced with every process of the transaction. This way, it’s easy to maintain transparency and accountability. Not only does this make transactions more secure, it also eliminates the need for huge amounts of operational paperwork.
Furthermore, the records also reflect raw and accurate operational data, which can then be used to further optimize the supply chain. This is already being applied by some of the world’s largest and richest corporations, including Nestle, Unilever, Walmart, and Dole. Considering its ability to provide reliability and integrity in an increasingly complex system, blockchain technology is poised to take over logistical transactions in the near future. In fact, its transparency- and efficiency-related benefits will also be crucial to the safe use of AI in a variety of exchanges and supply-chain processes.
Already being realized in the UK via a system called the Customs Freight Simplified Procedures (CFSP), it is administered by Her Majesty’s Revenue & Customs. In a nutshell, the CFSP is a streamlined customs taxation system that allows for faster release of goods that come from countries outside of Europe. This system includes the Simplified Declaration Procedure (SDP), which is used for releasing goods through most customs processes. True to its moniker, the SDP allows for quicker transactions, which is why a lot of importers use the procedure for moving perishable goods. Meanwhile, the system’s Local Clearance Procedure (LCP) is a similar option for the storage of goods before they are released through customs procedures. Combined with blockchain technology in customs transactions, this type of simplified customs declaration has the potential to completely restructure many sectors of the supply chain.
The increased data reliability introduced by these new technologies may also pave the way for back office AI in logistics. The digitization of transaction data has become increasingly more secure and widespread. This allows AI to take over menial but technical paperwork. International Banker explains that back-office data integrity services hinge on factors like data accuracy, compliance with regulatory requirements, and overall contribution to operational efficiency. Banks, accounting firms, and insurance companies already utilize this type of technology to streamline the processing of client data. The logistics industry is making moves to take advantage of this tech as well.
Smart Roads Can Help Maintain Infrastructure, Improve Traffic, and Increase Road Safety
Smart-road technology is becoming increasingly common in the US. National Geographic points to one notable example of smart road technology that’s currently undergoing live testing. In Sandpoint, Idaho, a startup company called Solar Roadways has developed a “smart highway” made of durable solar panels that can withstand up to 250,000-pound loads. They’re made of transparent tempered glass tiles. Underneath these tiles are photovoltaic cells that collect solar energy, which can then be used to power nearby buildings, street lamps, and other public infrastructure. The tiles are also equipped with LED lights, the uses of which include, but are not limited to: marking traffic lanes for controlling or redirecting traffic, and conveying messages to motorists such as warnings about upcoming hazards. And since the road panels can be heated, they’ll also be able to stay ice-free during the winter months.
NBC reports on a similar initiative in Colorado. Startup company Integrated Roadways has teamed up with Colorado’s Department of Transportation to test their own “smart pavement slabs” over a half-mile stretch of Highway 285 – a notoriously accident-prone part of the national highway system. This smart road technology is designed to connect to motorists’ cell phones to provide instant traffic reports and road hazard warnings. More importantly, the pressure-sensitive slabs can detect all manner of road activity, allowing for the smart and immediate prediction of emergencies or disruptions on the road. In turn, this allows emergency services to redirect traffic and very quickly respond to any incidents.
This is all possible through the IoT (Internet of Things) – the concept by which “smart” objects with different capabilities can exchange data among themselves via built-in web connections. It’s the same technology that was first introduced to the world as GPS-enabled dog collars, smart refrigerators, smartphone-controlled lighting and ventilation, as well as fitness tracking bracelets. The creation and development of these domestic – and mundane – smart objects have doubtless contributed to the still burgeoning popularity of the IoT. And today, on a much larger technological front, IoT technology has become largely responsible for the development of self-driving vehicles – another modern, practical application of current AI-based trends.
Self-Driving Cars Are Inevitable
The entire logistics industry will benefit from the continuing, rapid development of self-driving AI. Companies like NVIDIA are at the forefront of developing faster and more efficient microchips capable of responding to real-world road conditions. While enterprises like Google and Apple are interested in autonomous vehicles primarily for transporting employees around their own vast complexes, self-driving vehicles are already seeing an increased presence on public roads.
It may be a while until we see an actual delivery service with fully autonomous vehicles. But given how the technology has recently been successfully tested in the US, self-driving AI has the potential to eliminate (or at least greatly decrease) human error in the logistics equation. It all depends on how safe the technology is in practice, not just in theory. Until autonomous vehicle engineers find a way to completely eliminate the potential of lethal accidents due to malfunctioning self-driving software and/or hardware, we may have a long way to go before self-driving fleets can replace the nation’s large population of cargo drivers. And even in that aspect of the logistics industry, AI is taking an increasingly active role.
Vehicle Telematics Can Streamline the Supply Chain
Telematics is a complex term that encompasses several aspects of the long-distance telecommunications and big data industry. These days, the term has come to refer mainly to vehicle telematics – the use of GPS-enabled vehicle operational data, which is being used in delivery fleets. Verizon Connect reveals the vast possibilities of this new type of fleet-tracking software. Heavy trucks equipped with Electronic Logging Devices (ELDs) can now be tracked by their fleet operators in real time. This allows managers to find and implement more efficient driving routes for deliveries, which can greatly cut down on delivery time. This also makes it easier to assign the right people and resources to the right job. In terms of operational improvement, there are even larger opportunities. While AI-enabled machine learning via fleet tracking software can identify the patterns that emerge from collated operational data, managers can then use the data to craft increasingly creative, efficient solutions to present and future logistical problems.
No matter how you view these coming changes to the world of logistics, AI and its supporting technologies are about to take over the entire global supply chain. AI is not yet perfect because multiple-intelligence applications and algorithms are still in their infancy. Compared to the prevailing technologies and methods currently used in the global supply chain, AI is a relative newcomer to the industry.
But as the world’s brightest engineers continue to develop AI and all related support technologies at an astoundingly rapid rate, we’re bound to see more tech-powered innovations in the logistics industry before the decade ends. Just as the global supply chain swells to become increasingly complex and unmanageable, so too will AI evolve and mature with greater proficiency at performing progressively more complex tasks. Whether it’s warehousing, transportation, or delivery completion, AI technology can step in to fill in the gaps of human limitations.
Camille Peters graduated from university with a degree in computer science, and has been exploring her passion for the subject through her blog posts. She is interested in the future of AI and machine learning, and believes that it will improve the world greatly. The best part of her work is predicting where AI technology will go next and which industry it will next disrupt.
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