Artificial Intelligence in Logistics: Applications and Proposed Solutions

This report discusses the role of Artificial Intelligence (AI) in logistics and explores five different types of AI applications. It proposes three AI-based solutions for warehouse management, logistics and shipping autonomous vehicles, and data robustness and cleaning using Natural Language Processing (NLP). The report also provides potential advantages and disadvantages of each proposed solution.

Running head: PROFESSIONAL SKILLS IN ICT
Professional Skills in ICT
Name of student
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Author’s Note

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Executive summary
In this current era of technology most of the large business organizations are incorporating
Artificial Intelligence (AI), to establish successful supply chain management in their operational
and functional activities. Different types of applications of AI in logistics are elaborated and also
three AI based solution are proposed in this paper. The report had included the key issues in
application that were included in Artificial Intelligence. As when investigated there was five
different types of applications; Chatbots for the operational procurement, Supplier Relationship
Management (SRM) for Predictive and Machine Learning Analytics, Machine Learning for
Warehouse Management, Natural Language Processing (NLP) for Data Robustness and
Cleaning, Logistics and Shipping Autonomous Vehicles was found. The findings in the report
had proposed three AI application. Those are Machine Learning for Warehouse Management,
Logistics and Shipping Autonomous Vehicles, Natural Language Processing (NLP) for Data
Robustness and Cleaning. It had been recommended to connect Logistic Technology providers,
Logistics and Supply Chain and have a Self-driving car and Flying warehouse whose detail
description had been given in the report.

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Table of Contents
Introduction......................................................................................................................................2
About Artificial Intelligence............................................................................................................3
Role of Artificial Intelligence (AI) in Logistics..............................................................................3
Five different types of applications.................................................................................................5
Three AI based application proposed..............................................................................................8
Conclusion.......................................................................................................................................9
Recommendation.............................................................................................................................9
References......................................................................................................................................11

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Introduction
In the recent year, it has been seen that there was immense progress in Artificial
Intelligence (AI). The field of research is thriving which increases the important areas of
research with a number of the application having core technology. In AI there is rapid progress
which often increases the operational power with hardware advancements. There are many
practical applications which have an AI, and it has enabled technologies to cover different fields
of understanding of speech recognition, predictive analytics, process automation, biometrics,
natural language processing, machine and deep learning (Ghahramani, 2015). In the past, the
researchers of AI envisaged a system that is computational where human intelligence is exhibited
and achieve a level of skills for decision-making and problem solving. The organisation has been
running for 20 years with around 200 staff working in it. The organisation has the capabilities to
provide logistics solutions for manufacturing, mining and warehousing. Therefore, the
organisation has explored options to provide services that are based on AI. The main head office
is in Sydney and operates in other states of Australia and Oceania region. There are high
symbolic, formalised AI constraints especially board games attempt a complex and decision
making environments. Many businesses have seen AI has increases the cost of employment of
human and different ways were used by industries (Russell, Dewey & Tegmark, 2015). There are
developments and implementation in small cities and medical sciences, in movies there are some
special effects and the type of work the back-office could even manage. Many critics have been
rise from the fields of ICT which uses AI for an unethical takeover over a human by the
machines (Müller & Bostrom, 2016).

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About Artificial Intelligence
Artificial Intelligence (AI) consist of different fields from machine vision to expert
systems. John Mccarthy has coined the term AI in the year 1956. The computer system mainly
processes the Artificial Intelligence were learning, reasoning and self-correction are included.
Size, speed and data diversity increase business globally. AI can recognise the data patterns more
efficiently than a human for business insights (Hill, Ford & Farreras, 2015). The history of AI
has been a pioneer in computer science. The AI goal is to stimulate the performance of the
human for the task to make the program to be the best. The use of artificial intelligence captures
the human brains that have limited domains. In the revolution of the computer the system
develops intellectually, reason rationally and effectively interprets the real time environment
(Scherer, 2015). The mathematician and scientist have changed there thinking about artificial
intelligence. The artifact of intelligent in Greek mythology has appeared to be available after
World War-II. It was possible for the complex activities to get stimulated by professional
expertise. The best example of an intellectual system is the chess playing program (Hricik,
Morgan & Williams, 2018). The chess engine is designed to play as the opponent can count the
move in a million ways which the human beings are incapable of. The gaming, business,
medicine, controlling flights, academia, weather forecasting is getting revolutionised by artificial
intelligence. The technique of AI organises and efficiently use the knowledge that is perceivable,
easily modifiable and useful in many situations (Wong & Bressler, 2016).
Role of Artificial Intelligence (AI) in Logistics
It is essential that the organisation work processes are operating with a highest possible level
that has a well-oiled logistics team. The world of professional has grown with digitisation, and
with the addition of artificial intelligence (AI) the resources are getting maximise the time, and

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spending of money get reduces (Lu & Burton, 2017). The four important things to know about
AI and their role it plays in logistics are discussed below:
1) Common Solutions and Problems: The Artificial Intelligence has explored the businesses
through the breakthrough of recent technologies. The shipper's demand has increased as it
has pushed the businesses to the logistical teams (Yaseen et al., 2015). The technology can
offer the most common solutions such as the risk mitigation and redundancies for cost
reduction, forecast the traditional techniques, resource management. The automation
business can seamlessly update the IT systems and enhance the process of data analysis that
could bolster the logistical processes (Schölkopf, 2015).
2) Load cost: It is tricky to predict the price because the shipping cost varies in every season
and even on a day-to-day basis. Such conditions of AI could be monitored that could choose
the price at the time of delivery and headed a shipment (Chen et al., 2017). The algorithm as
monitors the traffic through a series of parameters for traffic, weather and socio-economic
which help the organisation to challenge the socio-economic to reach a price that is fair for
both the parties to agree upon.
3) Optimizing Inventory: In democratisation and information accessibility the role of AI is
essential as it offers a fair price for the technology were both parties ensure a fair deal which
could monitor the load capacity and inventory to avoid faltering of trucks at the t, time of
delivery (Patil, 2016). The number of trucks and the inventory supplier could be managing
and secure by the technology for delivery. AI has offered data analysis to know about the
movement of the carriers for the freight will the level of price and service.
4) Unforeseen CIA circumstances are tackled: For the logistical business, the organisation may
find the series of circumstances that could affect the product expected delivery date (Yang,

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2018). The logistical workflow of the organisation gets affected by the carrier bankruptcies,
strikes of the employee, hurricanes and floods.
Five different types of applications
1. Chatbots for Operational Procurement: Chatbots have being develop through artificial
intelligence. The specialist is now implementing chatbots in to the activities of supply chain
management. This help the organization to utilize the tech-aided work-tools. The chatbot
with machine learning and deep AI can hold conversation that are small and have patterns to
understand. Chatbots can be used in value chain and are applicable for information
acquisition and customer service. The chatbot technology is the AI application that the
organization realize that the marketplace of AI gets explore to automation and computer
assisted activity so that the organization could stay competitive. The tasks are related to
streamlining procurement through augmentation and automation that has Chatbot capability.
It require access to set intelligent data and robust them. The procuebot is a brain or a frame
of reference. Chatbots could be utilized so that:
 Supplier could speak during the trivial conversations.
 Actions could be set and send to suppliers with regard to governance and compliance
materials.
 Placing the request for purchasing.
 Internal questions are research and answer in regard to procurement functionalities or
supplier.
 Documenting or filing or receiving invoices that could requests for payments.

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2. Supplier Relationship Management (SRM) for Predictive and Machine Learning
Analytics: The Suppler Relationship Management (SRM) provide strategic and operative
processes that begin with the strategy of purchasing, procurement controlling and supplier
management for ordering process. The SRM system objective is for close link suppliers.
The selection and sourcing form a right supplier increases the concern that could enhance
the CSR, supply chain ethics and supply chain sustainability. There are risk related to
supplier which have become a ball and chain for the brands that is globally visible. The
Supplier Relationship Management (SRM) has generated an action for Data sets such as the
audits, supplier assessments and providing credit scoring for further decisions in regard to
the supplier. The passive gathering of data could be made active by Machine Learning and
intelligence algorithms. The supplier selection has become intelligible and productive. It has
a platform were success could be achieve with first collaborations. For the inspections of the
human information are easily available and it get generated through machine to machine
automation. It provides multiple scenarios with best supplier as per the user desires.
3. Machine Learning for Warehouse Management: The application that run the Machine
Learning algorithms could easily analyze large, diverse data sets, improve demand
forecasting accuracy which is the most challenging aspects for supply chain management
and predict the production that are demandable for the future (Pavlik, 2016). The Machine
learning is very effective with factors that have no tracking or it may even quantify over
time. It reduce the freight costs, improve the delivery performance of the supplier and
minimize the risk that the supplier receive with collaborative supply chain networks. The
Machine learning has its core constructs that could ideally provide insight to improve the
performance of the supply chain management. New products are forecasting that are drive to

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new sales were strong results are obtained through machine learning (Kitano, 2016). The
organization could extend the supply chain assets that include engines, machinery,
warehouse equipment and transportation that could be collected through IoT sensors.
4. Natural Language Processing (NLP) for Data Robustness and Cleaning: The Natural
Language Processing has the ability were the program of the computer could be easily
understood through human speech when spoken. NLP interact with computer and human
languages. It has an activity for the computer which is easy to analyze, understand and
generate the language that are natural. It has a linguistic forms, methods and activities of
communication that could publish, translate, and read. With advances in NLP we could
easily send text message through phone. It is not enough to get a sequence of words even
parsing sentences are not enough either (Meiring & Myburgh, 2015). There is a very limited
domain the computer has that provide an understanding which is presently possible for
limited domains. The interaction is possible for the computer were human can understand
the spoken language that is natural.
5. Logistics and Shipping Autonomous Vehicles: The local and regional shipping could be
considered as the most and largest antiquated industries. There are several trucks that require
on-site human judgment. The technology are autonomous and the process is highly unlikely.
The features for automation are payment, scheduling and pricing that could streamline the
cumbersome process for shippers, carriers and drivers. Cargo ships are container ships that
put larger effort to automate for the industry (Lieto et al., 2015). The individual self-driving
trucks are automated and has big change for the truck industry. The individual self-driving
trucks could not reduce the costs of transportation but could test with the convoys that are
connected to sensors, GPS and Wi-Fi were it has cameras so that it can be connected to the

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trucks. The speed and the direction is determined by the leading vehicle along with other
convoy to automatically steer and change the speed.
Three AI based application proposed
The organisation need to use some AI based application which helps in expanding the
business logistics. There had been made some analysis for some of the AI application by
considering its potential advantages and disadvantages based on the investigation done of the
above application and provide a legal, social and ethical point of view. For the organisation to
grow it has proposed the following system and provides with some potential advantages and
disadvantages:
1. Machine Learning for Warehouse Management:
The warehouse and inventory-based management forecast supply flaws has become a
disaster for the company that is based on customer. The forecasting engine along with the
machine learning keeps on looking for algorithms and data streams with different
forecasting hierarchies. For the forecasting loop there is an endless Machine Learning with
self-improving output. It has the capabilities to reshape the warehouse management.
2. Logistics and Shipping Autonomous Vehicles:
The organization could use the intelligence in logistics and shipping that could focus on the
supply chain management. The lead time and transportation expenses of the shipping get
reduce and add operations of elements that are environmental friendly, reducing the costs of
the labor and widen the gap in between the competitors.
3. Natural Language Processing (NLP) for Data Robustness and Cleaning:

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AI and Machine Learning has NLP element to stagger the potential that is deciphering the
foreign language in large amounts in a streamlined manner. NLP will be built in the data sets
with regard to the suppliers and decipher for information that are untapped, it has language
barrier. The technology of NLP could be streamline the compliance and auditing actions
which are unable because of the language barriers that is existing between the bodies of the
buyer and the suppliers.
Conclusion
The above study provides information that the logistic world which is a complicated one
as it needs a lot of planning, the ability to adjust and resilience for unforeseen circumstances that
happen. The organisation could logistically automate the work process which is an alternate
route for derailing the vehicles for bad weather and road construction. The technology can
reduce the amount of time spent and money that determine the logistics to replenish the
organisation by determining the best vehicle to carry a load. This has proved that AI machines
are more capable than the human intelligence. Prediction is difficult for AI to achieve cognitive
ability and in-depth knowledge about the human being. Thus, the impact of logistics turns to
innovate the technology with practical solutions. The business systems data, machine learning,
create operational efficiencies to make the business decisions better. The use of AI computing
techniques can teach systems to recognise the patterns and issue an action or recommendation on
it.
Recommendation
After investigating about the AI and its application that has proposed the recommendation being
provided as per the study:

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1. AI in Logistics and Supply Chain: From the experience of the customer friction could be
removed with the physical artificial intelligence by combining the analytics and the
customer data. The “Uberization” and mobile technology would be better to improve the
businesses where there is a demand for shorter delivery from retailers and the same is
expected from the manufacturers.
2. Connecting to Logistic Technology providers: The organization could have risk and
opportunities for corporate supply chain. The e-commerce and its operation is demandable
as it increase the efficiency were the organization could need automation and technology for
their supply chain market. The purchasing behavior and expectations of delivery are closely
aligned with the consumers’ habits. The organization businesses are growing keener which
could the inventory closer to the customers. The AI and IoT will help the logistic industry to
successfully support other verticals.
3. Self-driving car and Flying warehouse: The self-driving vehicles is the astonishing
technology to safe the human drivers. The data is gathered through multitude of sensors
which include 360-degree car views. In that way accidents and traffic jams could be avoided
by potentially communicating. Self-driving cars are particularly useful to save costs, make
deliveries more efficient and faster, and are useful for the delivery companies. Vehicles are
widely use to improve the driving autonomously on the busy roads. It could also ensure
proper legal framework. The patent of flying warehouse that is patent by Amazon could visit
places that make autonomous drones for developing a project. Technology has been
evolving rapidly that flying warehouse in the upcoming future it would resemble the
portrayed futuristic movies.

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