A Mini Project Report

On

“Use of AI and IoT in Vending Machine”

By

“Divyanshu Singh”

“2300520700026”

Under the guidance of

“Dr. Raji”

In partial fulfillment of the requirement for the award of the

Degree of Master of Business Administration

Submitted at

DEPARTMENT OF BUSINESS ADMINISTRATION

INSTITITUTE OF ENGINEERING AND TECHNOLOGY
JANKIPURAM LUCKNOW, UP-226021

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 Department of Business Administration Institute of

Engineering & Technology Lucknow

Student Declaration

I undersigned, hereby declare that the project titled “Use of AI

and IoT in Vending Machine” submitted in partial fulfillment
for the award of Degree of Master of Business Administration is
a bonified record of work done by me under the guidance of “Dr.
Raji” Assistant Professor. This report has not previously formed
the basis for the award of any degree, diploma, or similar title of
any University.

Date:
Place: Lucknow

Divyanshu Singh
2300520700026
Engineering & Technology Lucknow

2
 Department of Business Administration Institute of

CERTIFICATE FROM INSTITUTION

This is to certify that Mr. Divyanshu Singh, Second Semester

student of Master of Business Administration, Institute of
Engineering & Technology, Sitapur Road, Lucknow has
completed the project report “Use of AI and IoT in Vending
Machine” in partial fulfillment of the requirements for the award
of the Degree of Master of Business
Administration.

Date:
Place: Lucknow

Dr. Durgawati Kushwaha

Co-Convener

Engineering & Technology Lucknow

3
 Department of Business Administration Institute of

CERTIFICATE FROM FACULTY GUIDE

This is to certify that Mr. Divyanshu Singh, second semester

student of Master of Business Administration, Institute of
Engineering & Technology, Sitapur Road, Lucknow has
completed the project report entitled “Use of AI and IoT in
Vending Machine” Towards partial fulfilment of the
requirement for the award of the Degree of Master of Business
Administration under my supervision.

Date:
Place: LUCKNOW

Dr. Raji

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 ACKNOWELDGEMEN

This report is an outstanding prospect to convey my gratefulness to those

people whose timely help and guidance went a long in finishing this project
work from commencement to achievement. I would like to thank the
Director of Institute of Engineering and Technology, Lucknow, ‘Dr. Vinit
Kansal’ and our Coordinator of Department of Master of Business
Administration, ‘Dr. Virendra Pathak’. This was really a good way of
learning and I really learned a lot from this project.
I would also like to thank to my mentor and Convener of Master of
Business Administration, ‘Dr. Raji’ for rendering their valuable time and
providing me full knowledge which was needed in order to successfully
completion of this report.

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Preface:

The study of vending machines as a distribution channel

explores their evolution, operationalchallenges, and
technological advancements. Vending machines offer
unparalleled convenience, distributing a wide range of products
efficiently. However, issues like stock management, technical
malfunctions, payment limitations, security
concerns, and regulatory compliance hinder their
effectiveness. This study delves into these challenges, examines
the impact on operations and customer satisfaction, and
evaluates emerging technological solutions. By understanding
and addressing these issues, the study aims to enhance the
reliability, efficiency, and customer experience of vending
machines, contributing to their continued growth and innovation
in the modern marketplace.

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 Table of Content:
Chapter Content Page No.

1 ⚫ Introduction 08-11

⚫ Issue and Challenges 12-13

⚫ Application Of AI & IoT to 14-18

Overcome these Challenges

⚫ Problem Statement 19

2 ⚫ Significance 20-21

⚫ Objectives 22-23

⚫ Impact of Technology 24-26

5 ⚫ Limitation 22-24

⚫ Conclusion 29-30

⚫ References 31

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Introduction:

A vending machine is an automated device that dispenses a variety of

products to consumers in exchange for payment. These machines are a
staple of modern convenience, offering easy access to items such as snacks,
beverages, personal care products, and even electronics. They can be found
in a wide range of locations, including office buildings, schools, shopping
centers, transportation hubs, and hospitals.

History

The concept of vending machines dates back to ancient times, with the
earliest known device described by the Greek engineer Hero of Alexandria
in the 1st century AD. Hero's machine dispensed holy water when a coin
was inserted. Modern vending machines, however, began to take shape in
the late 19th and early 20th centuries, with the introduction of machines
that sold postcards, gum, and snacks.

How Vending Machines Work

1. Product Selection: Customers choose the product they want using

buttons, keypads, or touchscreens.

2. Payment: Customers make a payment using cash, coins, credit/debit

cards, or mobile payment systems.

3. Dispensing: Once the payment is accepted, the machine dispenses

the selected product into a retrieval area where the customer can
collect it.

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A vending machine is an automated device that dispenses products to
consumers after they insert payment. These machines can sell a wide
variety of items, such as:

• Snacks (chips, candy, cookies)

• Beverages (soda, water, coffee)
• Health and beauty products (toothpaste, deodorant)

Artificial Intelligence (AI)

AI refers to the simulation of human intelligence processes by machines,

especially computer systems. These processes include learning (the
acquisition of information and rules for using the information), reasoning
(using rules to reach approximate or definite conclusions), and self-
correction. AI technologies include:

1. Machine Learning (ML)A subset of AI that involves the use of

algorithms and statistical models to enable computers to learn from and
make decisions based on data.

2. Natural Language Processing (NLP): Enables machines to

understand and respond to human language.

3. Computer Vision: Allows machines to interpret and make decisions

based on visual inputs from the world.

4. Robotics: AI systems that control robots to

perform tasks autonomously.

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5. Expert Systems: AI programs that mimic the decision-making
abilities of a human expert.

Internet of Things (IoT)

IoT refers to the network of physical objects (“things”) that are embedded
with sensors, software, and other technologies with the goal of connecting
and exchanging data with other devices and systems over the internet. IoT
components include:

1. Sensors and Actuators: Devices that collect data from their

environment and perform actions.

2. Connectivity: The communication protocols and networks (e.g.,

Wi-Fi, Bluetooth, 5G) that connect IoT devices to the internet.

3. Data Processing: The use of edge computing or cloud computing to

analyze and process data collected by IoT devices.

4. User Interface: The means by which users interact with IoT devices
and the system as a whole.

Integration of AI and IoT

When AI and IoT are combined, they create a powerful synergy that
enhances the capabilities of each technology:

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Smart Decision Making: IoT devices collect vast amounts of data, and AI
processes this data to make intelligent decisions, such as predicting
maintenance needs or optimizing energy usage.

Automation: AI enables IoT devices to operate autonomously, adjusting

their behavior based on real-time data and predefined rules.

Enhanced User Experience: AI analyzes data from IoT devices to provide

personalized services and recommendations to users.

Predictive Analytics: AI algorithms use data from IoT sensors to predict

future events, such as equipment failures or demand for products.

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Issue And Challenges:
1. Stock Management

• Stockouts: Running out of popular items can lead to missed sales

opportunities and customer dissatisfaction.
• Overstocking: Excess inventory, especially for perishable goods,
can lead to waste and increased costs.

2. Technical Malfunctions

• Mechanical Failures: Problems with the dispensing mechanism,

payment systems, or other components can render the machine
inoperative.
• Software Issues: Bugs or glitches in the machine's software can
disrupt operations, particularly in modern machines that rely on
complex software for inventory and payment processing.

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3. Payment Problems

• Limited Payment Options: Machines that only accept cash can be

inconvenient for customers who prefer using cards or mobile
payments.
• Payment Processing Failures: Issues with payment systems can
lead to failed transactions and frustrated customers.

4. Security Concerns

• Vandalism and Theft: Vending machines can be targets for

vandalism and theft, leading to loss of inventory and repair costs.
• Fraudulent Transactions: Machines may be susceptible to fraud,
such as counterfeit money or hacking of payment systems.

5. Maintenance and Servicing

• Regular Maintenance: Vending machines require regular

maintenance to ensure they remain operational, which can be
logistically challenging and costly.
• Response Time: Delays in addressing technical issues or restocking
needs can lead to downtime and lost sales.

6. Location and Accessibility

• Optimal Placement: Finding the best locations for vending

machines to maximize visibility and sales can be challenging.
• Accessibility: Ensuring that machines are accessible to all users,
including those with disabilities, is essential but can be difficult to
implement in certain locations.

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7. Customer Experience

• User Interface: Complicated or unintuitive interfaces can deter

customers from using the machine.
• Product Visibility: Poor product visibility or lack of information
about products can negatively impact the customer experience.

8. Regulatory Compliance

• Health and Safety Standards: Vending machines, especially those

dispensing food and beverages, must comply with health and safety
regulations, which can vary by region.
• Payment Regulations: Ensuring compliance with financial
regulations for payment processing can be complex.

Application of AI & IOT Technology to Overcome these

Problems:

1. Stock Management

Stockouts:

• IoT Sensors: Real-time monitoring of stock levels using IoT sensors

can provide accurate inventory data.
• AI Predictions: AI algorithms analyze historical sales data and
current trends to predict demand and ensure timely restocking.

Overstocking:

• Inventory Optimization: AI can predict optimal stock levels to

minimize overstocking, particularly for perishable items, reducing
waste and costs.

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 • Automated Ordering: IoT-enabled machines can automatically
place restocking orders based on AI predictions, ensuring balanced
inventory levels.

2. Technical Malfunctions

Mechanical Failures:

• Predictive Maintenance: IoT sensors monitor the health of machine

components, and AI predicts potential failures, allowing for
proactive maintenance.
• Remote Diagnostics: IoT allows for remote
diagnostics and troubleshooting, reducing downtime
and the need for on-site repairs.

Software Issues:

• Continuous Monitoring: AI systems continuously monitor

software performance and can detect and correct bugs or glitches in
real-time.
• Automatic Updates: IoT enables remote software updates, ensuring
machines run the latest and most stable versions of their software.

3. Payment Problems

Limited Payment Options:

• Multiple Payment Systems: IoT-enabled machines can integrate

with various payment systems, including cards, mobile payments,
and contactless options, providing convenience for all customers.
• AI Fraud Detection: AI can detect unusual transaction patterns and
flag potentially fraudulent activities, enhancing security.

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Payment Processing Failures:

• Redundant Systems: AI and IoT can ensure that backup payment

systems are in place to handle failures.
• Real-time Monitoring: IoT provides real-time monitoring of
payment systems to quickly identify and resolve issues.

4. Security Concerns

Vandalism and Theft:

• Surveillance Systems: IoT-enabled cameras can monitor machines

for suspicious activities and alert authorities.

• AI Analysis: AI can analyze video feeds to detect vandalism or theft

attempts in real-time.

Fraudulent Transactions:

• Secure Payment Processing: AI can enhance payment security by

detecting counterfeit money and preventing hacking attempts.
• Blockchain Technology: Integrating blockchain with IoT can

provide a secure and transparent transaction history. 5. Maintenance

and Servicing

Regular Maintenance:

• Predictive Maintenance: AI predicts when maintenance is needed

based on data from IoT sensors, reducing the frequency of scheduled
maintenance and lowering costs.

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 • Automated Servicing Alerts: IoT can automatically alert service
personnel when maintenance is required, ensuring timely
interventions.

Response Time:

• Remote Monitoring: IoT allows for remote monitoring and

diagnostics, enabling quicker response to issues.
• Efficient Scheduling: AI can optimize maintenance schedules and
routes for technicians, reducing downtime.

6. Location and Accessibility

Optimal Placement:

• Data-Driven Decisions: AI analyzes foot traffic, demographic data,

and sales patterns to determine the best locations for vending
machines.
• Real-time Adjustments: IoT data can help in
relocating underperforming machines to better spots.

Accessibility:

• User-Friendly Interfaces: AI can design intuitive and accessible

user interfaces that cater to all users, including those with
disabilities.
• Voice Assistance: IoT-enabled voice recognition can assist users

who have difficulty with traditional interfaces. 7. Customer

Experience

User Interface:

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 • Personalized Interfaces: AI can tailor the interface based on user
preferences and past interactions, making it more intuitive.
• Voice and Gesture Controls: IoT can integrate advanced
interaction methods such as voice commands and gesture controls.

Product Visibility:

• Interactive Displays: IoT-enabled screens can provide detailed

product information and interactive visuals.

• AI Recommendations: AI can recommend products based on user

preferences and purchase history, enhancing the customer
experience.

8. Regulatory Compliance

Health and Safety Standards:

• Real-Time Monitoring: IoT sensors ensure that temperature and

humidity levels are within the required ranges for food safety.
• Automated Reporting: AI can generate compliance reports
automatically, ensuring adherence to health and safety standards.

Payment Regulations:

• Secure Transactions: AI ensures that payment processes comply with

financial regulations, using encryption and secure protocols.
• Audit Trails: IoT and AI provide transparent and traceable transaction
records, facilitating regulatory audits.

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Problem Statement:

Vending machines, while convenient and efficient for product distribution,

face several challenges that hinder their effectiveness. Stock management
issues, such as stockouts and overstocking, lead to missed sales and
increased costs. Technical malfunctions, including mechanical failures and
software glitches, disrupt operations and customer transactions. Limited
payment options and processing failures inconvenience customers and
cause lost sales. Security concerns, such as vandalism, theft, and fraudulent
transactions, result in inventory loss and repair costs. Regular maintenance
is logistically challenging and costly, and delays in addressing issues cause
downtime. Finding optimal locations to maximize visibility and ensuring
accessibility for all users are difficult tasks. Poor user interfaces and
inadequate product visibility negatively impact customer experience.
Finally, compliance with varying health, safety, and financial regulations
adds complexity to operations. Addressing these issues is critical to
enhancing the reliability, efficiency, and customer satisfaction of vending
machines as a distribution channel.

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Significance of This Study:

• Operational Efficiency Improvement: Understanding and addressing

the challenges such as stock management, technical malfunctions,
payment problems, and maintenance issues can significantly enhance
the operational efficiency of vending machines. This improvement can
lead to reduced downtime, lower operational costs, and increased
profitability for businesses operating these machines.

• Customer Satisfaction Enhancement: By resolving issues related to

user interface, product visibility, and payment options, vending machine
operators can enhance the overall customer experience. This can lead to
increased customer satisfaction, repeat business, and positive word-of
mouth, ultimately driving higher sales and revenue.

• Market Expansion Opportunities: Overcoming challenges related to

optimal placement and accessibility can open up new opportunities for
expanding the market reach of vending machines. Identifying strategic
locations and ensuring accessibility for all users can attract more diverse
customer demographics and increase machine utilization rates.

• Risk Mitigation and Security Enhancement: Addressing security

concerns such as vandalism, theft, and fraudulent transactions can
mitigate risks associated with operating vending machines.

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 Implementing robust security measures can protect inventory and
minimize repair costs, ensuring sustainable operation and profitability.

• Compliance and Regulatory Adherence: Understanding and adhering

to health, safety, and financial regulations is crucial for operating
vending machines legally and responsibly. Compliance ensures
operational continuity and avoids potential legal issues or fines, thereby
safeguarding the reputation and longevity of the business.

• Technological Integration and Innovation: Studying these

challenges encourages the adoption of advanced technologies such as
IoT for real-time monitoring, predictive maintenance algorithms, and
secure payment systems. These innovations not only mitigate current
challenges but also future-proof vending machine operations against
evolving market demands and technological advancements.

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Objectives of this study:

• Identify Key Challenges: To systematically identify and analyze the

main challenges encountered by vending machines in distribution
channels, including but not limited to stock management issues,
technical malfunctions, payment problems, security concerns,
maintenance and servicing challenges, location optimization
difficulties, customer experience issues, and regulatory compliance
hurdles.

• Understand Impact on Operations: To assess how these challenges

impact the operational efficiency, reliability, and profitability of
vending machines. This involves quantifying losses due to stockouts,
downtime from technical failures, revenue implications of payment
processing issues, costs associated with security breaches and
maintenance delays, as well as the impact on customer satisfaction and
brand reputation.

• Explore Technological Solutions: To explore and evaluate

technological advancements and innovations that can mitigate or
eliminate these challenges. This includes studying the effectiveness of
IoT for real-time inventory monitoring, predictive maintenance
algorithms to prevent breakdowns, secure payment systems to prevent
fraud, and advanced analytics for optimizing machine placement and
product offerings.

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• Enhance Customer Experience: To propose strategies for improving
the customer experience by addressing issues related to user interfaces,
product visibility, payment options, and accessibility. This objective
aims to increase customer satisfaction, promote repeat business, and
attract new customers through enhanced convenience and service
quality.

• Optimize Operational Practices: To recommend best practices and

operational strategies for vending machine operators to optimize stock
management, minimize downtime, improve security measures,
streamline maintenance procedures, and ensure regulatory compliance.
These recommendations aim to enhance operational efficiency, reduce
costs, and maximize revenue generation.

• Support Strategic Decision-Making: To provide data-driven insights

and recommendations that support strategic decision-making processes
for businesses involved in vending machine operations. This includes
insights into market expansion opportunities, potential ROI of
technological investments, and compliance strategies to mitigate legal
and regulatory risks.

• Contribute to Industry Knowledge: To contribute to the body of

knowledge within the vending machine industry by conducting a
comprehensive study that advances understanding of operational
challenges, technological solutions, and best practices. This objective
aims to foster innovation, collaboration, and continuous improvement
within the industry.

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Impact of Technology Advancement:

1. Improved Operational Efficiency

IoT and Real-Time Monitoring: Technology allows vending machines to

be equipped with sensors and IoT devices that monitor inventory levels in
real-time. This helps in preventing stockouts and overstocking by enabling
timely restocking and inventory management.

Predictive Maintenance: Advanced analytics and machine learning

algorithms can predict potential failures in vending machine components.
This proactive approach minimizes downtime and reduces maintenance
costs by addressing issues before they escalate.

Automation: Automated systems for inventory replenishment and

maintenance scheduling streamline operational processes. This reduces
human error, enhances efficiency, and ensures machines are always
operational.

2. Enhanced Customer Experience

User-Friendly Interfaces: Touchscreens and interactive displays provide

intuitive interfaces that make it easier for customers to browse products,
select items, and complete transactions quickly and efficiently.

Personalization: Technology enables vending machines to offer

personalized recommendations and promotions based on customer

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preferences and purchasing history. This enhances customer satisfaction
and encourages repeat business.

Mobile Payments and Contactless Options: Integration with mobile

payment platforms and contactless payment methods improves
convenience for customers who prefer cashless transactions, thereby
increasing transaction speed and reducing wait times.

3. Security and Fraud Prevention

Secure Payment Systems: Advanced encryption and secure payment

gateways protect customer financial information and reduce the risk of
fraudulent transactions. This instills trust and confidence among users.

Surveillance and Remote Monitoring: CCTV cameras and remote

monitoring systems deter vandalism and theft. Operators can monitor
machine activity in real-time and respond quickly to security breaches.

4. Data-Driven Decision Making

Analytics and Insights: Technology enables the collection and analysis of

vast amounts of data on customer behavior, sales patterns, and machine
performance. This data provides valuable insights that inform strategic
decision-making, such as optimizing product offerings and machine
placements.

Operational Optimization: Data analytics help in identifying optimal

locations for vending machines based on foot traffic, demographic data,
and consumer preferences. This maximizes visibility and sales potential.

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5. Regulatory Compliance

Compliance Management: Technology facilitates adherence to health,

safety, and financial regulations by automating compliance checks and
documentation. This ensures that vending machines operate legally and
avoid regulatory penalties.

6. Innovation and Adaptation

Emerging Technologies: Continuous advancements in technology, such as

artificial intelligence (AI) and machine learning, offer opportunities for
further innovation in vending machine operations. For example, AI can be
used for predictive maintenance and personalized customer interactions.

Integration with Ecosystems: Vending machines can be integrated into

larger digital ecosystems, such as smart cities or retail environments,
enhancing connectivity and interoperability with other IoT devices and
platforms.

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Limitations:

Generalization: Findings may not be universally applicable due to

variations in vending machine technologies, market conditions,
geographical locations, and regulatory environments. What works in one
region or for one type of machine may not necessarily apply elsewhere.

Data Availability and Quality: Access to comprehensive and accurate

data from vending machine operators and users may be limited. This could
impact the depth and reliability of analysis and conclusions drawn from the
study.

Technological Constraints: The study's focus on technology

advancements assumes that all vending machines are equipped with
modern technologies like IoT, AI, and secure payment systems. However,
many machines, especially older models, may not have these capabilities,
limiting the generalizability of technological solutions.

Time Constraints: The study may not capture long-term trends or changes
in consumer behavior, technology, or regulatory landscapes over extended
periods. This limitation could affect the study's relevance and applicability
to future scenarios.

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Bias and Subjectivity: Researchers' perspectives and biases could
influence the interpretation of results and recommendations. It's essential
to mitigate bias through rigorous methodology and diverse perspectives.

Ethical Considerations: The study should consider ethical implications,

such as privacy concerns related to data collection from vending machine
transactions and user behaviors.

Operational Realities: Practical challenges in implementing

recommended solutions, such as cost constraints, technological feasibility,
and operational complexities, may hinder their adoption by vending
machine operators.

External Factors: External factors beyond the scope of the study, such as
economic fluctuations, global events, and competitive dynamics, may
impact the effectiveness of proposed solutions.

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Conclusion:

In conclusion, while vending machines offer significant

convenience in product distribution, they face several operational
challenges that impact their efficiency and customer satisfaction.
Issues such as stock management, technical malfunctions, limited
payment options, security concerns, maintenance complexities,
optimal placement, customer experience, and regulatory
compliance are critical areas needing improvement.

Advancements in technology provide promising solutions. IoT

enables real-time monitoring for inventory management,
predictive maintenance algorithms reduce downtime, and secure
payment systems enhance transaction reliability. User-friendly
interfaces and personalized recommendations improve customer
experience, while compliance software ensures adherence to
regulations.

Addressing these challenges not only boosts operational

efficiency, reduces costs, and increases profitability but also
enhances customer satisfaction and expands market reach.
However, limitations like technological constraints, data
availability, and practical implementation challenges need careful
consideration.
Overall, integrating advanced technologies and adopting best
practices can transform vending machines into more reliable,

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secure, and customer-friendly distribution channels, paving the
way for sustained growth and innovation in the industry.

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References:

Academic Papers

AI and IoT Integration:

1. Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi,
M. (2014). Internet of Things for Smart Cities. IEEE Internet
of Things Journal, 1(1), 22-32.
2. Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013).
Internet of Things (IoT): A Vision, Architectural Elements,
and Future Directions. Future Generation Computer Systems,
29(7), 1645-1660.

Smart Vending Machines:

1. Chen, C. H., Huang, H. C., & Tsai, S. B. (2016). A Study of a

Smart Vending Machine. Mathematical Problems in
Engineering, 2016.
2. Kamran, M. A., & Jeong, Y. S. (2018). Intelligent Vending
Machine with Energy-efficient Sensor Node. IEEE Access, 6,
3169-3179.

Books

AI and IoT:

1. Vermesan, O., & Friess, P. (Eds.). (2014). Internet of Things -

From Research and Innovation to Market Deployment. River
Publishers. Link
2. Janakiram, M. S. V. (2019). Industrial IoT (IIoT): A Complete

Guide to Implementing IoT in the Industrial Sector. Packet

Publishing. Link AI in Business Applications:

1. Barlow, M. (2016). Real-Time Big Data

Analytics:
Emerging Architecture. O'Reilly Media.
2. Kaplan, A., & Haenlein, M. (2019). Siri, Alexa, and other
Digital Assistants: The Future of Marketing. Business
Horizons, 62(1), 15

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