Impact of Artificial Intelligence in the Truck or Logistics Industry
Artificial Intelligence development will play a key
role in the future of trucking. Not only can collect and monitor data, but observes
patterns, it will be able to make predictions based on these models. These
predictions will improve the capacity of the AI board to assist the driver and
navigation functions as well as background features such as data monitoring and
preventive maintenance. AI also increases the connectivity and communication
between other trucks on the road, improving Convoy and other common route
management systems. However, Artificial Intelligence is can be a costly and
time-consuming effort, which may not be possible for some companies to achieve
within a reasonable time.
Impact
of Artificial Intelligence in the Truck or Logistics Industry
Autonomous
Vehicles
In recent years many self-driven cars
and trucks have been a subject of interest to people. Artificial intelligence
is profitable for transport. Driverless vehicles make changes to the supply
chain and help reduce costs in logistics. Of course, we know about cars, but AI
allows unmanned automation to more vehicles. For example, these means of
transport such as trucks, vans or buses can also be automated for the transport
of goods. These types of vehicles can work alone or cooperate with someone.
However, in many countries, the government estimates that the driver must be in
the vehicle to completely control the situation on the road and analyze
possible risks. Of course, this statement may be altered in the future.
Traffic
management
Another problem with transportation that
people face daily traffic congestion. Artificial Intelligence is now set for
this problem too. Sensors and cameras everywhere embarked
on the road collecting a large number of voluminous traffic details. These data
are then sent to the cloud, where the analysis and the revelation of the
traffic pattern are done with large data analysis and a system powered by AI. Valuable
information such as traffic forecasts can be drawn from the data processing.
Commuters can be supplied with important details such as traffic forecasts,
accidents or roadblocks. Also, people can be informed about the shortest route
to their destination, helping to travel hassle of traffic. In this way, the
Artificial Intelligence can be managed to reduce not only unwanted traffic
but also to increase road safety and decrease delay times.
Innovative
payment systems
Technology transactions and payments On
track discs using a digital register, where all the data collected on the
payment in one report. Digital invoices merge all shipments within one invoice
which is sent by email or by the application. Machine Learning is applied
also optimizes the delivery notes that drivers must submit to process the
payment of their services. Finally, the platform used payment gateways to
ensure maximum security when making transactions.
Delay
predictions
Another burning issue facing the truck
industry today delays. The estimated costs due to delays are billions of
dollars worldwide, as well as financial losses, delaying a negative impact on
the customer experience. A negative experience can affect the value of a
transport company, which can result in client turnover. To solve these
problems, Artificial Intelligence helps us in the truck industry here.
Using
IoT to track the movement
Anyone who knows what the Internet of
Things or IoT would easily be able to imagine some ideas on how it can be used
in the logistics industry. Somehow the AI with IoT can completely
revolutionize the industry.
Real-time
decision making
In logistics, there is a wide range of
tasks that require data to make decisions. All these decisions will take
several minutes for the average human mind to calculate. But with the help of
avian influenza, there is an instant solution for as sifts through thousands of
data points. All this takes seconds and accuracy is a spot which is what makes
the AI much more exciting in this sector.
Optimization
of loads/routes
Spotting Secure route is a significant
part for our operators as such it is a problem that we converge on the most,
because it ensures the supply of loads that best fit the profile of a driver to
optimize the price offered to the Shipper through loads of road tests available
to try to offer several commands chained empty kilometers minimizing.
Therefore, in addition to internal development, GIS services are used for Geolocation,
geocoding and arrival time, among others.
Conclusion
The challenge now is digitizing the
supply chain is that companies are increasingly difficult to keep pace with new
advances in technology as they struggle to find ways to implement them in their
business models in particular for non-digital natives.
However, there is more pressure on the
leaders of the supply chain increasingly imperative to digitize. The increased
pressure of rising costs and expectations. And the cost of labor in this sector
will decrease continuously with the increased use of AI, providing higher
profits for industry players. The issue of long hours of driving and stopping
for a break will not be a problem with the fully automated fleets. The
integration of AI systems with a transportation management system can help
reduce costs and implementation time.
Fusion Informatics offers a solid
platform that the advantages for logistics and transport companies receive time
data on a perimeter of services, including asset control, monitoring the
vehicle station and communication with employees on the drive and the
management of human support, all increase the overall performance. And,
tracking not only vehicles using GPS and also increases business efficiency of
the supply chain with the help of deep learning algorithms and machine
learning, allowing you to make cost savings and optimize resource utilization.
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