MALLA REDDY ENGINEERING COLLEGE

Maisammaguda, Secunderabad, Telangana, India, 500100

BONAFIDE CERTIFICATE

This is to certify that this Real time research project work entitled “ ONLINE AUCTION
SYSTEM”, submitted by CH. YASHWANTH REDDY(23J41A0578),D. LOKESH
REDDY (23J41A0582),G.LOKESH GOUD(23J41A0587),MD. KAIF(23J41A05A5) to
Malla Reddy Engineering College affiliated to JNTUH, Hyderabad in partial fulfillment
for the award of Bachelor of Technology in COMPUTER SCIENCE AND
ENGINEERING is a Bonafide record of project work carried out under our supervision
during the academic year2024 –2025 and that this work has not been submitted elsewhere
for a degree.

SIGNATURE SIGNATURE
DR. Arun Kumar DR. Pilla Srinivas

Assistant Professor Professor& HOD-CSE

SUPERVISOR,CSE Malla Reddy Engineering College
Malla Reddy Engineering College Secunderabad,500100
Secunderabad,500100

Submitted for Real Time Research Project viva-voce examination held on

INTERNALEXAMINER

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 MALLA REDDY ENGINEERING COLLEGE
Maisammaguda, Secunderabad, Telangana, India 500100

DECLARATION
I here by declare that the Real time research project titled “ Online Auction System ”,
submitted to Malla Reddy Engineering College (Autonomous) and affiliated with JNTUH,
Hyderabad, in partial fulfillment of the requirements for the award of a Bachelor of
Technology in COMPUTER SCIENCE AND ENGINEERING, represents my ideas in
my own words. Wherever others' ideas or words have been included, I have adequately
cited and referenced the original sources. I also declare that I have adhered to all principles
of academic honesty and integrity, and I have not misrepresented, fabricated, or falsified
any idea, data, fact, or source in my submission. I understand that any violation of the above
will be a cause for disciplinary action by the Institute. It is further declared that the project
report or any part thereof has not been
previouslysubmittedtoanyUniversityorInstitutefortheawardofdegree.

Signature(s)

CH. YASHWANTH REDDY 23J41A0578

D. LOKESH REDDY 23J41A058

G.LOKESH GOUD 23J41A0587

MD. KAIF 23J41A05A5

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 MALLA REDDY ENGINEERING COLLEGE
Maismanaguda , Secunderabad , Telangana, India 500100

ACKNOWLEDGEMENT

We would like to express our sincere gratitude to Dr. A.Ramaswami Reddy,

Professor& Principal, MREC(A) for his invaluable support and encouragement
through out the course of our project.

We extend our heartfelt thanks to Dr. Pilla Srinivas, Professor and Head of the
Department of Computer Science and Engineering, for his insightful guidance and
continuous encouragement during the project.

Our sincere appreciation goes to our Project Coordinator, Dr.Arun Kumar,

Assistant Professor, Department of Computer Science and Engineering, for his
unwavering cooperation and assistance during the project work.

We are deeply grateful to our Project Guide, Mr.________, Assistant Professor,

Department of Computer Science and Engineering, for his consistent guidance,
direction, and support, which were instrumental in the successful completion of the
project.

We also wish to thank all the teaching and non-teaching staff of the department for their
valuable cooperation and support throughout the project.

CH. Yashwanth Reddy 23J41A0578

D. Lokesh Reddy 23J41A0582
G. Lokesh Goud 23J41A0587
MD. Kaif. 23J41A05A5
 TABLE OF CONTENTS

Chapters Title Page no.

1. Introduction 1
2. Proposed Model 4
3. Architecture 7
4. Literature survey 11
5. Output of project 14
6. Resume 16
7. Conclusion 17
8. References 18
 CHAPTER-1
INTRODUCTION

1. 1. INTRODUCTION

Auction means Latin work, which means growth. Auction is a bid, a method of selling;
Purchasing and providing services occur. The online auction system has many other names such
as e-auction and electronic auction. The client can more accurately specify the need for online
auctions or online bidding. Online bidding has become more widespread in all forms of industrial
use. Not only does it have the product or goods it needs to sell, it also has the services it can
offer. Due to their low cost, this spread caused the system to thrive.

Preferred bidders can manage and monitor the same database. The user’s data may be maintained
confidentially for the validity and integrity of the contract documentation. Multiple babies can
communicate very easily. This system allows multiple bids by single users. Developing a
userfriendly auction site where any product can be bid and providing value-added services to
bidders and sellers. The world of online auctions Marketplaces allow buyers and sellers to cross
geographical limits and purchase products from anywhere over the Internet

. The online auction market offers consumers lower prices, greater product selectivity and greater
efficiency compared to traditional online markets (Ghose et al., 200!). Seller's choice and the
product they produce make greater buyer certainty. It consists of three components: seller rating
scores and seller's shilling operations.

Certifications, description of product characteristics, product usage and book value. It seeks to
ensure buyers product accuracy. Decision Assistance tool also provides seller ratings by using
Feedback Scores. These feedbacks give previous winning bidders and evaluate online auction
 product vendors. These bidders give detailed seller ratings of all aspects of the seller, and give
scores for how accurate the description of the item is, how satisfied they are with the seller's
communication, and how quickly the seller is shipped to them.

1.2 ADVANTAGES:

1. There are no groups that sound like a traditional system, where customers have to sit and bid.

2. The convention excludes the usual frustration that usually happens when bidding on a
traditional system.

3. Led There is no scheduled schedule limit which means that the bidder can bid anytime and
anywhere.

4. The bidding process can be conducted on a global scale

1.3 Hardware:

1. Processor: Minimum 2.0GHz requires.

2. Ram: 2 GB.

3. Hard Disk: 100 GB.

4. Input device: Standard Keyboard and Mouse.

5. Output device: VGA and High Resolution Monitor.

1.4 Software:

1. Operating System: Windows 7.

2. Language: Java
3. Database: MySQL 5.0 & Above.

4. Tool: JDK 1.5 & Above, Eclipse IDE.

5. Server: Tomcat
 CHAPTER-2
PROPOSED MODEL

2.1 PROPOSED MODEL:

The auction system requires the information provided by the item seller to include machine
learning algorithms so that the final price can be accurately predicted. These algorithms are used
in products with complex features or details such as speed, memory size, etc. However, "soft"
products such as jewelry differ in the characteristics they used to compare different types of
objects. Features such as size, texture and color are present but are not the type of "defining"
brand style.

The auction system requires the information provided by the item seller to include machine
learning algorithms so that the final price can be accurately predicted. These algorithms are used
in products with complex features or details such as speed, memory size, etc. However, "soft"
products such as jewelry differ in the characteristics they used to compare different types of
objects. Features such as size, texture and color are present but are not the type of "defining"
brand style.
2.2 EXISTING SYSTEM:

Existing "ONLINE AUCTION SYSTEM" is manually controlled. Before each auction,

the auction date, venue and auction items are announced by the media. Those wishing to
participate in the auction should arrive at the venue on that day in time. This common
method most of the time prevents the craving for bidding process. Another painful thing
to do with the old system is to investigate each bidding process and make it out of cash.
Therefore the system should keep records of both buyers and sellers until the settlement
is resolved. This process is weird and time-consuming
2.3 SYSTEM IMPLEMENTATION:

System Implementation:

This section shows the artifacts of the proposed work in addition to the subsequent
implementation of system analysis and design. System analysis and configuration results of the
proposed system are presented. PHP programming language and HTML are used according to
their attributes to suit this purpose. To start using the proposed system, the user must register as a
bidder or vendor (as shown in figure 4), the proposed system to enable a user (bidder or seller)
displayed by a registered user (bidder or seller) on the OAS welcome web page Confirmed by
the site. An unregistered user must fill out a registration form to use the system. The bidding
interface is represented.
 CHAPTER-3
ARCHITECTURE

3.1 Three-tier architecture

For the realization of the on line auction system we used a 3-tier system architecture as shown on

this schema.

In such a structure, there are six 3 elements:

• Customer tier, responsible for data delivery, user experience and user interface control.

• An application server tier, which addresses the business logic of the program. In fact, business
objects that use "live" business rules are here, and are available to the customer-tier. This tier
protects data from direct customer access. For the project, we used JBoss as the application
server. • Data tier, responsible for data storage. As a data server, we used PostgreSQL, an open
source related database.

TOPIC:

UML was developed to provide the same criterion for defining Object Oriental Models models.
However, to successfully implement the UML concept, it must be employed with the Object
Oriented Analysis and Design method [55-59]. Object-Oriented Design and Design (OOAD)
analysis refers to a group of software development methods based on business structure. The
method summarizes the life cycle of the program development that identifies the delivery and
activities of the object-oriented project [60]. Business relationship diagrams define the data to be
managed by the system, while data flow will describe the operations [61, 62]. Object-based
software development using innovative methods, supported by computer-aided engineering tools
such as Rational Rose [5-case diagram, class diagram and sequence diagram was selected for
user needs analysis; Class drawings were chosen to represent the class structure. The proposed
OAS will help bidders charge faster and increase their chances of making a successful bid by
suggesting a higher price, and help the seller get a higher profit.

3.2 Use Case Diagram The use case diagram is the use case diagram [58, 62- 64], e.g., the
auction system interaction with users. In the proposed OAS the use case consists mainly of
register case, product research, product liability, view product details, change bid price, product
bid, specify time and bid price, etc. 1 shows a schematic diagram of the use of actions that can be
performed by the actors (Merchant, Bidder and Admin) at auction.

3.3 MODULES:

Basically 3 actors (Manager, Bidder and broker) will be in touch with the proposed program;
each can do the following:

Administration:

• Management can manage products

• Managers can manage departments

• Administration can handle users

• Management can handle bidding

• Management can create reports .Bidder can search for a product

 Winning bid

Bidder can view product details

• Bidder may change the bid amount

• Bidder can bid on the product

• Bidder can edit profile information.

Seller:

• The seller can ship the product

• The seller can specify the time and bid price

• The seller can view bidding information

• The vendor can edit profile information

Figure 1: The use case diagram.

 3.4 Class Diagram:

In the analysis and introduction of Object-Oriental, the class diagram is a very important part. It
describes the types of objects in the system and describes the tuli relation between the internal
class system [58]. Functions and Attributes

In class and the constraints applicable to the connection of objects can be shown by a class
diagram. Figure 5 shows the OAS class diagram. Figure 2 shows OAS entities, such as director,
product, bidder, seller and bidder, etc.
Figure 2: The class diagram of the proposed OAS.
 3.5 Sequence Diagram

The sequence diagram is one of the UML dynamic models [60, 65], and it defines the sequence of
interactions between objects at the time the use case is executed and prioritizes the time-relay
information

Objects. In general, the sequence diagram illustrates the single use-case behavior. Figure 3 displays the
bidder sequence diagram in the proposed OAS.

Figure 3: The bidder sequence diagram.

 CHAPTER-4

LITERATURE SURVEY:

LITERATURE SURVEY:

Online auctions have become an elaborate transaction strategy for e-commerce. Biggest online

The world's largest marketplace, eBay, is an attractive case study that enables online auction
studies using data Relationships with real people and transactions. In this paper, we present a
detailed research and analysis of multiple online. The auction features including: consumer
surplus, sniping, bidding strategy and their cross-relationships. Our mission assess the theoretical
foundations of online auctions and discover patterns and behaviors hidden by the absence of Real
and extensive transaction data. In our findings, we found a significant relationship between
sniping and high Surplus ratios, which represent uncertainty of real value in a competitive
environment. The main problem is wrong the umption is that the bidder's values are independent
of each other, leading to ineffective bidding. In that order Solve the inefficiencies of current
online formats, we introduce a customized decreasing price auction model for online.
Transactions. Conceptually, this model should address the complexities of competition in the
online environment

While enhancing social welfare. In recent years, the expansion of the World Wide Web has led to
an increase in the number of people Auction on the Internet. One of the hallmarks of online
auctions is the high need for successful implementation. The size of buyers and sellers on its
website. Consequently, auction sites with high traffic are the advantage over the volume limited.
This leads to more polarization of buyers and sellers towards a specific site. This is often called a
network effect in a variety of web and telecommunications Applications involving interactions
between a large number of entities. This effect is qualitatively known
Increase the value of the entire network, and its impact has never been modeled or rigorously
studied. In this paper, we build a Markov model to evaluate network effectiveness in the case of
web auctions. We show that the network effect

Web auctions are very powerful and can lead to a situation where an auctioneer can quickly

overtake it Competition sites. This leads to the natural steady balance of an online auction seller

For a given product and geographic area. For some reason the single player structure is unlikely

The approximation estimates in the model show the presence of a single dominant player in the
trend Web auction space.

There is growing academic interest in the popularity and success of online auctions. Although
there are many Research has been conducted to understand online auctions, and little effort has
been made to consolidate them assess the results of previous research and the status of research
in this area. The objective of this study. Explore the intellectual development of consumer
behavior in online auction research through a meta-analysis of Published auction research. The
results of this study are based on an analysis of 83 articles published on this topic

Mainly in information systems (IS) journals between 1998 and 2007. The results indicate
consumer behavior Research on online auctions can be classified into three main categories,
consumer behavior and

Auction results. Based on this literature review, suggestions for future research on auction
consumer behavior Potential new structures, unexplored relationships and new definitions and
dimensions and Suggestions for methodological improvements are made. This study answers the
question of how a person trades between a listing fee (i.e. cost) Bidding) and transaction potential
(i.e., the possibility of selling a product). Applying the tradeoff decision model in the auction
context, we consider the seller's online auction outlet option and Next start-up pricing strategies
when facing a trade-off between transaction potential and inventory fees. Results From a set of
laboratory experiments, it is suggested that the seller be prepared to bear the high cost instead.
Transaction opportunity. Furthermore, the higher the transactional transaction potential, the
higher the seller is likely to set Starting price despite high inventory fees. The implications of
theory and practice are discussed. Online auctions are becoming increasingly popular in
electronic commerce (EC). It has changed Consumer-to-consumer mainstream trading methods
(C2C), such as eBay. A stable cooperative field and Multi-agent system (mass), and then the
general concept of exchange is formed with the cooperation of agents. There is a lot of common
sense to get things done. Contribution to mass member and Self-interest. Based on the analysis of
cooperation and

Online Auction Participant Competition, The concept of overtime and history information is
introduced. As with existing incomplete information, the efficiency of Bidders will be short of
considering history information. This paper has advanced the mass flow framework and
negotiation Algorithms that enable bidders to participate honestly and actively in negotiations.
Both capable and improved transparency among participants.

Auction is an effective way to allocate goods or services to higher value bidders. Rapidly

The rise of e-bidders not only facilitates online transactions but also presents new and distinct
challenges. It is difficult to establish Trusts on Sellers, Buyers and Auctioneers without
Centralized Auction Websites or Platforms Collect bids and get auction results. However, these
third parties are unreliable, and harmful sellers or Buyers may refuse to pay for the goods or
payment according to the protocol. Also, open and anonymous. The online environment creates a
coalition of bidders to auction and unjustly auction participants Profit. Several auction models
have been proposed to address these issues, but they are simultaneously less expensive Achieving
decentralization (i.e., without a trusted third purpose), strong consensus (i.e., trust establishment),

Combination-prevention and practical implementation. We are the first decentralized

combination-resistant e-auction system.

An auction is to buy and sell goods or services by accepting them for bid

Bids, and then sell items to the highest bidder. Upcoming e-business applications include online
auctions. This auction will have a big impact on trading in B2B (Business to Business), as well as
B2B (Business to B) Consumer) and C2C (consumer to consumer) areas. Android app
development along with the recent web Services have brought many changes in the field of
mobile application development. In view of the above points, An Android-based mobile
application is designed to run online auctions to buy and sell products. The app provides a
solution for buyers and sellers from different geographical areas to come together Single venue
and easy bidding and participation. English auctions are the most popular auction, May the
application deals with other bidders such as the Dutch auctioneer. Our Android app for mobile
phones. Requires General Packet Radio Service (GPRS) and Wi-Fi technology to operate.
 CHAPTER-5

OUTPUT:

OUTPUT: HOME PAGE

Login and Registration Form

Product Registration Form

Bidding Form
 CHAPTER-6
RESUME:

The developed system is simple and changes can be made easily. The system was developed with
insight into the changes needed in the future.

One of the future improvements of our system is to improve system security by adding the option
to blacklist default bidders. These are also an option for rating sellers. An online payment
solution can be added to the system.
 CHAPTER-7

Conclusion

CONCLUSION:

The online auction system has made customers more efficient and efficient in their behavior and
has driven businesses to new heights, forcing many to make the adjustments and changes
necessary to reach a new market of knowledgeable consumers.

The rapid growth of e-auctions has led to an e-transformation in global retail infrastructure.
Thanks to a growing internet and higher incomes and a more savvy population, despite many
obstacles. Secure online payments, good for electronic stores, return policies and exciting
discounts help you understand the benefits of the auction system.

A better understanding of the behavior of the consumer online auction system can help
companies gain more online customers and increase their e-business revenue. At the same time,
consumers are more inclined to make purchases online, as they realize the benefits of e-auction.
With the popularity of the Internet, the number of Internet users continues to grow and more and
more Internet users are becoming online users, even regular online buyers.
 CHAPTER-8
REFERENCES:

[1] Hu Wenyan, Alvaro Bolivar, “Online Auctions Efficiency: A Survey of eBay Auctions”,
Alternate Track: Industrial Practice and Experience, 2008.

[2] Charu C. Aggarwa, Philip S. Yu, “Online Auctions: There can be only one”.

[3] Xiling Cui, Vincent S. Lai and Connie K.W. Liu “Consumer Behaviour in Online Auctions: A
Review”, Electronic Markets Vol. 18 No.4.

[4] Chuan-Hoo Tan, Hock-Hai Teo, Heng Xu, “Online Auction: The Effects of Transaction
Probability and Listing Price on A Sellers Decision Making Behaviour”, Electron Markets
(2010) 20:6779.

[5] Liang Zhang, Na Li, “Multi-Agent Negotiation System in Online Auction”, IEEE, Second
International Conference on Communication Systems, Networks and Applications, 2010.
[6] Shuangke Wu, Yanjiao Chen, Qian Wang, Minghui Li, Cong Wang, Xiangyang Luo, “Cream:
A Smart Contract Enabled Collusion-Resistant e Auction”, IEEE, Transactions on
Information Forensics and Security, 2018.
[7] Hamid-Reza Ghasemi, Gholam-Reza Mohammadi, “Architecture - oriented approach for
detecting fraud in the online auction”, IEEE, 8th International Conference on e-Commerce
with focus on e-Trust, 2014.
[8] Zhang Jie, Zhang Yaping, “Research on Duration and Bid Arrivals in eBay online Auctions in
the Internet”, IEEE, 2011.
[9] Benjamin J. Ford, Haiping Xu and Iren Valova, “A Real-Time Self-Adaptive Classifier for
Identifying Suspicious Bidders in Online Auctions”, Published by Oxford University Press on
behalf of The British Computer Society, 2012.
[10] Janhavi Baikerikar, Vaishali Kavthekar, Esmond Dsouza, Steffie Fernandes, Mureil
Dsouza, “Hammer Down-An Online Auction Application”, IEEE, 2017.