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Technologies Impacting Overland Freight Optimization

What’s covered in this article:

  • Benefits of freight optimization technologies

  • The potential of real-time data collection and sharing

  • Driver safety

  • AI and automation

  • Innovative possibilities to enhance the logistics industry

Recently, supply and demand volatility has caused uncertainty in the logistics industry. Freight optimization technologies have increased in relevance, as they could help improve the health of a business by reducing costs and increasing sales. Optimization leads to downtime reduction and higher utilization levels, resulting in better productivity.

Take a trucking carrier, for instance. An optimized fleet would mean fewer unused equipment, less maintenance needs, and better use of the company’s resources. This optimization process leads to number of benefits, including higher efficiency and productivity, reduced costs, better route planning, and lower fuel consumption. Drivers also benefit from optimization. They feel safer as result of the information provided and critical data logged, which in turn can then be used to improve existing processes.

By leveraging technology, logistics stakeholders can have visibility into freight movement, forecast accurate ETAs, track freight provenance, and more.

By leveraging technology, logistics stakeholders can have visibility into freight movement, forecast accurate ETAs, track freight provenance, and more. Optimization through technology helps improve cost and time efficiency, while adding flexibility to unforeseen circumstances like rerouting and a better general reaction to disruptions.

The Internet of Things

It is easy to see why the Internet of Things (IoT) impacts innovation in general. The possibility to create a network of devices, vehicles, and appliances that can actively share data in real-time through any kind of cloud service is immediately attractive as it creates immense value through data-based insights.

IoT solutions come with a variety of possibilities. It can help improve shipment tracking, monitor freight conditions, understand product provenance, and more. Current technology accounts for solutions such as RFID labels, GPS and tracking devices, truck ELDs, cargo sensors and automated barcode readers. This allows businesses to phase out manual entry of data and physical paperwork. Another benefit of IoT is the standardization of collected data, making it much easier to analyze and create real-time information-fed tools.

Big Data

By collecting real-time data across every step of the supply chain and analyzing it through artificial intelligence or statistics (predictive analytics), companies can get a wealth of information to make well-informed decisions.

Good quality standardized information is a requirement for Big Data, but forecast and proactive optimization possibilities are huge. By collecting real-time data across every step of the supply chain and analyzing it through artificial intelligence or statistics (predictive analytics), companies can get a wealth of information to make well-informed decisions.

IoT devices can capture significant amounts of data shared through many devices, which is streamlined over the cloud. By analyzing this data, insights on logistics trends can be forecasted and used to proactively adapt to supply chain volatility. This is an invaluable asset as it can help prevent losses by optimization, inevitably ticking carbon emissions goals.

AI and Machine Learning

Artificial Intelligence has already significantly impacted the logistics industry with intelligent transportation, route planning, and demand planning. Combined with other cutting-edge technologies, AI has spun off a variety of solutions including autonomous last-mile delivery robots, warehouse picking systems, and predictive maintenance software.

Furthermore, through machine learning, AI-based systems will evolve to adapt to different circumstances and unforeseen changes. That said, this does not mean that human input is no longer needed. Augmented Intelligence—the combination of AI with human intelligence—is an improved version of AI, combining inputs from human planners (experience, responsibility, customer service, flexibility, common sense, etc.) and AI technology, to automate operations that were previously manned.

FMS (Fleet Management Software)

FMS is a tool that integrates the different aspects of fleet management into a single piece of software. Traditionally, FMS solutions have been very rigid programs that are difficult to update and don’t allow for incorporating new technologies into the same system. Recent innovation has made FMS solutions highly modular and web-based, enabling much easier integration with other technologies.

Besides GPS and geo-tracking, FMS solutions have real-time reporting, collect data from all the IoT-enabled devices in the network, and are accessible from any place with an internet connection. The ability to deal with a significant increase in the amount of data collected might be the most decisive reason to start thinking about updating your FMS.

CMT (Collision Mitigation Technology)

A collision avoidance system, also known as a driver assistance system, is a safety system designed to prevent a collision or decrease its severity in the few seconds before it occurs. These systems are traditionally based on dash cams and GPS data, but with current technologies, more sensors and real-time data sources can be added to the system, making them a more powerful tool.

Forward collision warning system (FCW), lane departure warning system, pedestrian detection system, or automatic braking system are parts of a CMT that have a great impact on the security of the driver, vehicle, and cargo. Additionally, these components also help decrease fuel consumption and cut down maintenance costs. With the use of AI, these components can identify potential hazards and alert drivers in real-time, all while sending real-time data to the FMS to be analyzed.

ELD (Electronic Logging Devices)

ELDs, or electronic logging devices, are mandated to be used by drivers of commercial motor vehicles (CMVs) to record driving time automatically. An ELD captures the Hours of Service (HOS) records, reads data on the vehicle’s engine, and records timestamps and miles driven.

Relevant information is collected and shared in real-time, by combining the data gathered through sensors in the truck and IoT devices. Leading solutions in the market allow for the data to be accessed through any smartphone with the credentials, enabling the driver and fleet manager to check the information at any time. AI-driven analysis of all this data provides valuable insights that help make adjustments and proactive decisions.

Autonomous Technology

Autonomous vehicles—be it trucks or drones—are amongst the most widely discussed technology trends within the transport industry. Though this technology is yet to go mainstream, pilot programs have proven quite successful. Last-mile delivery, which remains a time and energy-consuming segment, could be an ideal candidate for the implementation of autonomous technology. Pavement robots can be deployed for last-mile delivery, helping reduce delivery costs and carbon emissions.

Techniques like platooning, a long line of heavy vehicles heading in the same direction, can be especially suitable for autonomous vehicles. Using remote monitoring, trucking companies can arrange vehicles so that the combined line of trucks work to combat wind resistance and traffic congestion. Platooning also works as a safety feature for the public as well. Instead of many trucks dotted all over the roads, this method creates a single, predictable large vehicle file.

Warehouse Automation

Warehouse automation adds value to warehousing operations by automating the execution of menial, repetitive tasks, thus allowing human workers to focus on more complicated tasks. This includes both warehousing robots that physically assist with floor operations and specialized software that automates workflows.

Automated Guided Vehicles (AGV), Automated Storage and Retrieval Systems (AS/RS), or “Cobots” (Collaborative Robots) are automation technologies that help warehouses expedite order fulfillment and better manage inventories. Warehouse robots cut down time spent in retrieving and transporting items around the warehouse floor, significantly reducing picking times.

Blockchain

Blockchain is used as a registry accessed by any user in a peer-to-peer network, making it a distributed ledger. This means that different participants in the supply chain can consult and validate various document transactions with total transparency in the logistics industry. Blockchain allows users to share information, ultimately apply data analytics, and get insights into optimizing processes and workflows.

The trade-off is that to be completely functional, blockchain requires that logistics companies digitize, standardize, and cleanse their data so an ecosystem of supply chain partners can emerge. This eventually helps blockchain to build a trustworthy network that brings true end-to-end visibility into operations.

Community-Based Applications

Low-profile technologies can also be an extraordinary asset to help drivers make their work easier. By having a few selected apps installed on your smartphone, tasks like finding the best price on gas, the safest route based on real-time data, or a safe parking spot are much more manageable.

Some community-based apps help gather information on truck stops and rest areas, showing and rating nearby parking locations based on security, facilities, and availability. Some apps will silence your smartphone message notifications and send automated response texts while on the road to ensure driver safety.

Adopting technology tools and implementing them will help companies stay resilient, by cutting losses and optimizing the use of resources.

Today, technology offers many innovative possibilities to enhance and improve processes and workflows to a level that will profoundly change the way the logistics industry works. Adopting technology tools and implementing them will help companies stay resilient, by cutting losses and optimizing the use of resources.

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