Big Data and AI in the logistics industry can help you make wonders with your business and set things to a completely new level of performance. Learn how exactly in our new themed feature.
AI in logistics continue making an increasing impact on practically all spheres of our life, considerably boosting our overall predictive capabilities and maintenance potential. The field of transportation isn’t an exception. Logistics automation allows for corporate carriers as well as affiliate shippers to make more business-efficient solutions. AI ultimately helps to ship agents figure out shipping situations on the go. The result is the dramatic economy of time, money, and other resources dedicated to your regular shipping.
Нow Much Do Autonomous Vehicles Change Logistics?
It is predicted that the mass employment of AI in the logistics and chain supply markets would expand by 42,9% throughout the period of 2017-2023 and will have reached $6,5 billion in the global budget by 2023. This means that almost half of all existing establishments will be using AI in some way or another in their operation. That’s why transportation companies increasingly pay attention to AI-based software solutions and tools for logistics purposes.
Roughly, software tools of such kind can be subdivided into two major groups. The first includes any pieces of software that are used directly in the process of shipping and are connected to the vehicles. The second group of solutions involves tools for the organization of shipping – in particular, automation of many related processes.
AI-Based Car Technologies
According to the Tractica company’s expert predictions, global supplies of storage and logistic robots will considerably accelerate in the following five years – from 194,000 units in 2018 to 938,000 units per year by 2022. Artificial Intelligence in cars is called for utterly securing the road traffic and facilitating the work of drivers, shipping agents, and dispatchers.
The AI niche as a whole gains a pretty rapid pace, with various logistics startups introduced here and there. In 2016, venture investments in American startups focused on AI-based systems grew from $26 billion to $39 billion.
Autonomous cars can work 24/7, doing their routes without even requiring a live driver in the first place. Such cars are equipped with sets of indicators – distance gauges, stereovision systems, geolocation systems, and hydro stabilizers. As for software, it must consist of the neural network and computer vision-based AI.
Pilotless vehicles operate based on the Bayesian mapping and localization method. In essence, the data collected from the car’s indicator is juxtaposed with the map indicators.
Pros & cons
Pilotless cars are quite efficient:
- Decrease the road accident chances & don’t involve any human fatalities in the case of emergency
- Reduce the cost of shipping by lowering driver salary expenses
- Provide centralized management for the shipping traffic, allowing to build better routes more efficiently
- Bypass the need in individual cars due to the novel carsharing services
- May allow making road strips narrower, which, in the long-term perspective, can increase the roads’ car passing capacity
- Allow shifting former driver employees’ focus on other, more consistent tasks
- Handle shipping stuff in hazardous areas & under rough weather conditions.
The cons in the matter, however, include:
- Responsibility issues in case of accidents
- Vulnerability to hacking attacks or unauthorized access
- A decrease in working positions for drivers.
Automated monitoring technology
This technological solution is to provide a high level of shipping security. The vehicle’s interior is equipped with a special camera that tracks the driver’s state – his movements and such.
Implementation of the computer vision-based AI
Such systems work similarly to face recognition solutions. Computer-vision AI solutions are based on neural networks. Special cameras are used to scan human faces while being online and capture the driver’s facial features that may tell about their exhaustion – the position of eyelids, gestures and mimics, frequent yawning, and such. The system can also help control the use of phone while driving to stay focused on the road.
If the employee gets distracted for some reason while driving, the exhaustion indication system makes a sound signal notification. A duty operator receives a notification as well, allowing them to anticipate and, perhaps, timely prevent a potential incident. In the worst-case scenario, the reason for an accident can be easily extracted from the camera recordings.
A GPS tracker is one of the first technologies to explicitly illustrate how AI helps in logistics. These are electronic devices to locate objects in space and you pretty much know how it works in essence if you’ve ever ridden a taxi cab.
Types of trackers
There are several major kinds of GPS trackers used by modern shipping companies:
- Personal devices that work with the battery or accumulator
- Stationary is powered by the car’s lighter socket
- Autonomous GPS trackers are mobile devices to use without additional charges for up to three years straight.
Additional GPS tracker features
Advanced modern car trackers may also include:
- A built-in microphone
- An accelerometer that marks the start & endpoint of the vehicle’s motion
- A special SOS feature that notifies a user every five minutes about their car being compromised in the case of an accident
- Record of all passing points
- Remote door, engine or lights blocking can be enabled by sending an SMS
- Additional indicators that control the amount of gas, temperature, moto hours, opening and closing of doors, etc.
Automated storage systems
Automated storage systems are digitized systems that provide automated, centralized management of a storage area.
Principle of work
Every other storage management system’s basic architecture can be subdivided into three major components:
- A client app for employees to input, change, and remove data, make requests and clarifications, etc.;
- A database server. The client can request, add, change or remove data on it;
- User-initiated data processing capabilities that return the processed information back to the database.
Goal of implementation
A centralized storage management system will help you accelerate solving a significant number of routine tasks, reducing staff expenses dramatically and minimizing the chances of errors. The tasks for automation are:
- Barcode printing & data correspondence check
- Storage by the according cells
- Orders & groups of orders management
- Goods admission & dispatch processes
- Supply replenishment
- Order sorting & packaging
- Goods shipment & accompanying papers
- Supply management
- Staff management
- Distribution facility operation management
- Container management
- Goods storage management.
Shipping Processes Automation Tools
There is a huge number of various available software solutions that help managing shipments either on the local or international levels. First of all, you should pay attention to the tools for routing shipments and working with big data bulks.
AI vehicle routing
Routing software can help solve numerous tasks on the agenda of both a full-blown transportation company and a small corporate autopark.
Pros of logistics routing software
The specialized software tools that analyze and build optimal routes autonomously are good at:
- No downtime
- Accelerating order shipping;
- Minimizing losses due to senseless mileage
- Boosting customer loyalty thanks to the overall speed of performance.
Routing software functionality
Most solutions of such kind have the following set of features:
- Optimized routing based on the type of cargo, vehicle, weather, shipping specifics & customer desires
- Driver scheduler capabilities
- Forming packaged & individual shipments
- Building multi-chained routes
- Journey sheet composition.
Big data processing planners
Big data in the logistics industry are useful for analyzing and coordinating major manufacture and management decisions.
The main types of logistics data can be grouped as follows:
- Order processing-based data
- Schedule & shipment or dispatch data, etc.
Which data is processed by Big Data solutions?
For the shipping company performance, most tools feature the following capabilities:
- Statistics collection (a number of completed & canceled orders, refusals, a number of certain-type shipments, etc.). All the data can later help to more efficiently interact with clients & build working ad campaigns.
- Expense account to help plan expenses more thoroughly & build additional expenses statistics.
- Storage operation management. Features that help to assess the business of the storage facility, defining peak workload hours & planning staff management more efficiently.
- Scheduling. Storage performance control, shippings scheduling, & work time planning do wonder in this line of work.
- Punctuality. Automated systems help to minimize shipping delays.
- Driver data. The company can compose custom driver lists & extract the respective statistics by individuals.
- Checklists with special customer requirements for particular orders.
All in all, the employment of AI in logistics helps to significantly optimize time, finances, and resource expenses as well as the overall company performance. Specialized software tools help automate the shipping process – from storing to transporting the goods to a particular destination. Smart technologies are pretty fruitful for your business workflow of the logistics company of any scale and size.