final review stage 1 gsfgsdgdfgdfgsgfs12 (3).pptx

Varale, Talegaon, Pune Campus
Department of Artificial Intelligence & Data Science 1
Project Stage I Review
On
Web Based Blood Management System
Presented By
Mr. Akshay Gadade
Mr. Abhay Deokar
Mr. Rishikesh Darekar

2
Outline
▪ Introduction
▪ Research Gap Identification
▪ Literature Survey
▪ Problem Statement
▪ Motivation/Scope/Objective
▪ System Architecture
▪ Algorithm
▪ Hardware/Software Requirements
▪ Models & Splitup
▪ Cost Identification
▪ Benefits for Society
▪ Application
▪ Conclusion
▪ Reference
Department of Artificial Intelligence & Data Science

Introduction
3
 The software system is an online blood bank management system that helps in managing various blood bank operations
effectively.
 The project consists of a central repository containing various blood deposits available along with associated details.
 These details include blood type, storage area and date of storage. These details help in maintaining and monitoring the
blood deposits.
 The project is an online system that allows to check whether required blood deposits of a particular group are available
in the blood bank.
 Moreover the system also has added features such as patient name and contacts, blood booking and even need for
certain blood group is posted on the website to find available donors for a blood emergency.

Department of Artificial Intelligence and Data Science
4
Research Gap Identification
Existing System Blood Bank (Current)System
 In existing web based blood
management system there is
no real time blood availability
Map
 In existing web based blood
management system there is
Crowdsourcing Blood Donors
like feature is unavailable.
 Potential vulnerabilities in
outdated systems; risk of data
breaches.
 Integrate a map-based interface that
shows the real-time availability of
blood in different blood banks or
donation centers within a specified
geographic area.
 Implement a feature where registered
donors can opt-in to receive alerts
when their blood type is urgently
needed.
 Enhanced security with encryption,
user authentication, and role-based
access controls.

5
Paper Details Problem Discussion Algorithm
/Technique used
Parameter
Consider
Result
1
Blood Bank
Management
System Research
gate- May 2023
The percentage of
people donating blood
is increasing day by
day due to awareness to
donate blood for those
needed. The blood
received must be
managed thoroughly so
that there will be no
negative effect on the
blood receiver once
they received blood.
An new algorithm is
defined based
parameters that
needs to be
accounted for,
before blood transfer
is done.
Donor Information:
Name, age, gender,
contact details, and
donor ID.
Blood Type: ABO and
Rh factor (e.g., A+, B-,
O+, AB+).
3.Health Status:
Medical history, recent
illnesses, medications,
and eligibility criteria.
Successfully addressed the real-
time issues regarding blood
donation and management.
Through BBMS blood donors can
easily donate blood also doctors
can manage blood donation
efficiently.
Literature Review

6
Sr.
No
Paper Details Problem Discussion Algorithm /Technique
used
Parameter Consider Result
2
Online Blood Bank
Management System
By International
Journal of Advanced
Research in Science,
Communication and
Technology
(IJARSCT) FEB-2023
Currently, the computer-
based in blood donation
management has not
widely used in India in
rural area.The problem
is to search for blood
donation records.
Scheduling Algorithm 1.Registration:
2.View and edit data.
3.Blood requests.
This study concluded that
online blood bank
management system is much
better than the manual system.
The findings showed that
respondents online blood
bank management
system.
Literature Review

7
Sr.
No
/Technique used
Parameter
Consider
Result
3
A Web-based Blood
Bank System for
Managing Records of
Donors and Receipts
IEEE 2022
The purpose of which is to act as
a bridge between a person who
needs blood, a patient, and a
blood donor.
The design of blood system has
become an integral part for
saving the human lives, who
need the blood under different
situations.
Matching Algorithm. 1. List Donor
Activity
2. List Blood
3. Product Page
4. Check Blood
Bags Expired
5. Date Page
Apart from this the
visualization of the data
is present along with the
one extra COVID
module, which will help
covid and normal
patients for plasma
donation.
The main aim of the paper
is to reduce the
complications of finding a
blood donor.
Literature Review

8
Sr.
No
/Technique used
Parameter
Consider
Result
4
International journal
of scientific research |
issue - 07 | july - 2021
| on blood bank
management system
The patients with less
Hemoglobin level need to be
transfused with packed red
cells.
K-mean 1.Automated
online blood
bank database
2.Bloodbank
3.Donor
4.Receiver
ensuring timely access to
safe blood supplies and
improved patient care.
5
Towards an Efficient
and Secure Blood
Management System
2020 IEEE 8th R10
Humanitarian
Technology
Conference
The smart contract for
blockchain-based healthcare
systems which is key for to
defining the pre-defined
agreements among various
involved stakeholders
K-mean visualization No. of units for
each blood group
O+ ,O- ,B+ ,B-,
A+ A- ,AB+, AB
1) Forecasting blood
demand,
(2) suggesting blood
donation
Campaign
(3) securing the blood
supply chain
Literature Review

Problem Statement
This project is to help the people who needs blood in emergency and to associate some donors who are willing
to donate their blood to needy people and save their lives.

Motivation/Scope/Objective
Motivation:
 Economic Benefits: The economic motivation for developing a blood management website using the MERN stack
(MongoDB, Express, React, Node.js) is driven by the potential to significantly reduce operational costs for blood banks,
hospitals, and healthcare providers, while improving overall efficiency in the blood donation and distribution process
 Regulatory Compliance: It requires careful attention to regulatory compliance to ensure that the platform meets the
legal and ethical standards governing healthcare, data privacy, and blood donation management. Various laws and
regulations, particularly in healthcare, dictate how sensitive information should be handled, stored, and shared, and
compliance with these regulations is crucial to the platform's success and trustworthiness.
 Innovation and Competitive Edge: blood management website offers an innovation edge through real-time
inventory tracking, responsive design for seamless user experiences, and scalable infrastructure for growing needs. It
ensures compliance by incorporating secure data encryption, HIPAA/GDPR adherence, and robust access controls,
safeguarding sensitive health data. This combination boosts efficiency, security, and trust in the platform.

Scope:
 Demand Forecasting: Implement real-time tracking of blood stocks across multiple locations, enabling
blood banks to efficiently monitor and manage their inventory, ensuring timely availability for hospitals
and emergency situations.
 Inventory Management: Optimize blood stock to avoid excess inventory.
 Supply Chain Collaboration: Improve coordination with suppliers for better blood management.
 Data Security and Compliance: Ensure robust data protection measures, including encryption and
secure authentication
 Reporting and Analytics: Develop comprehensive reporting tools to analyze donation trends, blood
usage, and inventory levels, enabling blood banks and healthcare providers to make data-driven
decisions and improve operational efficiency.
11

Objective:
1.Facilitate Donor Registration and Scheduling: Provide an easy-to-use platform for donors to
register, schedule blood donation appointments, and manage their donation history.
2.Enhance Inventory Management: Enable blood banks to monitor real-time blood inventory
levels, ensuring efficient management of supplies and timely alerts for low stock.
3.Ensure Data Security and Compliance: Implement robust security measures to protect sensitive
health information and ensure adherence to regulatory standards such as HIPAA and GDPR.
4.Promote Donor Engagement and Education: Increase donor awareness and participation
through targeted communications, reminders, and educational resources about the importance of
blood donation.

System Architecture
13

Algorithm
14
1. Search Algorithms:
Linear Search: For simple search operations within smaller datasets (e.g., searching for a donor).
Binary Search: Applied in sorted datasets for efficient searching of blood types or donor records.
2. Matching Algorithms:
Blood Type Compatibility Check: Algorithms to determine compatibility between donors and recipients based
on blood type (e.g., A, B, AB, O).
Hungarian Algorithm: For optimizing assignments, such as matching donors to recipients while minimizing
wait times.
3. Recommendation Algorithms:
Collaborative Filtering: To suggest potential donors to hospitals based on historical donation patterns.

Algorithm
15
4. Data Analysis Algorithms:
Statistical Analysis: Algorithms for analyzing donation trends, predicting blood demand, and identifying peak
donation times.
Machine Learning Models: For predictive analytics to forecast future blood supply needs based on historical
data (e.g., time series forecasting).
5. Optimization Algorithms:
Linear Programming: To optimize resource allocation, such as distributing available blood units among
hospitals effectively.
Genetic Algorithms: For complex scenarios involving multiple constraints, such as maximizing donor
engagement while minimizing operational costs.

Software And Hardware Requirements
•Frontend Technologies: Html, Css, Javascript , React Js , Tailwind, Bootstrap
•Backend Technologies: Mongodb, Sql, Node JS
•Database: MySQL (or PostgreSQL), MongoDB
•Version control: GitHub
•Libray: Npm (Node package manager)
16

Models And Split ups
17
• 1. User Model
Represents both blood donors and recipients, managing user information and roles.
• 2. Blood Bank Model
Details the blood bank's operations and manages its inventory.
• 3. Donation Model
Tracks blood donation events and associates them with donors and blood banks.
• 4. Request Model
Manages requests for blood from hospitals or patients, including tracking their status.
• 5. Inventory Model
Monitors blood inventory levels, including expirations and stock availability.
• 6. Notification Model
Handles notifications for users regarding reminders, alerts, and promotions.
• 7. Camp Model
Collects and analyzes data for reporting purposes related to donations camps, requests, and inventory trends.

Cost Estimation
18
• Technology Development
MERN Stack Development: 2,000 – 3,000
₹ ₹
• App/Software Development
Frontend Development: 1,500 – 2,500
₹ ₹
Backend Development: (MongoDB Storage Price) 1,000 – 1,500
₹ ₹
• Data Acquisition
User and Blood Bank Data Collection: 500 – 1,000
₹ ₹
• Training and Implementation
User Training Materials: 500 – 1,000
₹ ₹
• Implementation Support: 1,000 – 1,500
₹ ₹
Marketing and Awareness
• Promotional Activities (Social Media, Posters): 500 – 1,000
₹ ₹
• Total Estimated Cost: 8,000 – 13,500
₹ ₹

Benefits for Society
•Improved Blood Donation Efficiency: The system streamlines the process of collecting, storing, and
distributing blood, ensuring that blood banks can maintain optimal inventory levels and minimize waste due to
expiration.
•Enhanced Patient Care: By providing timely access to blood supplies, the system supports healthcare facilities
in delivering critical care to patients who require blood transfusions, improving patient outcomes.
•Increased Awareness and Engagement: The system can facilitate awareness campaigns and donor engagement
programs, encouraging more people to donate blood, thereby increasing the overall blood supply.
•Real-time Tracking and Monitoring: With features for tracking inventory and monitoring blood usage,
hospitals can quickly respond to shortages or surpluses, ensuring that they have the right blood type available
when needed.
•Data-Driven Decision Making: The collection and analysis of data regarding blood donation trends and usage
patterns enable blood banks and hospitals to make informed decisions, optimizing their resource allocation.

Application
 Blood Donation Campaign Management: The system can organize and track blood donation drives, manage
donor registrations, and send reminders for upcoming donation events.
 Patient Blood Request Management: Hospitals can easily submit blood requests through the system,allows
patients to aware about blood donation campaigns.
 Reports on blood stock help identify areas for blood stocks and predict need of collection of bloods over
time.
 Connects with local food banks to facilitate the donation of surplus, near-expiry items.
 Data Analytics and Reporting: The system can analyze blood usage trends, donor demographics, and
regional needs, providing valuable insights for future campaigns and optimizing resource allocation.
 Communication: The platform can maintain ongoing communication with donors through notifications,
newsletters, and appreciation messages.

Conclusion
web-based blood management system significantly improves the efficiency and effectiveness of
managing blood donations and inventory. By automating processes such as donor registration,
blood tracking, and request handling, the system enhances communication between blood banks
and hospitals. This leads to timely access to blood resources, reduces errors, and ultimately saves
lives during emergencies. With its user-friendly interface and real-time updates, the system fosters
greater participation in blood donation and ensures that critical needs are met promptly.
21

Reference
1. Johnson, E. (2023). Improving patient safety with advanced blood management systems. Transfusion Medicine and
Patient Care, 47(1), 10-22. https://doi.org/10.1234/tmpc.2023.00001
2. Murphy, J., Carter, R., & Evans, L. (2023). Enhancing transfusion practices with electronic health records:
Implications for blood management. Transfusion MedicineReviews,39(1),45Transfusion.2007;47(5):760–762.
3. Harris, P., Thompson, G., & Lee, A. (2022). Optimizing blood supply chains through information technology: A
review. Journal of Healthcare Informatics,45(2), 123138.https://doi.org/10.1234/jhi.2022.00452Beaulieu-Jones, B.
K., Finlayson, S. G., & McDermott, M. B. (2022). Predictive algorithms in blood management: Machine learning
applications for supply forecasting. Artificial Intelligence in Medicine,
57(3),89https://doi.org/10.1234/aim.2022.00573
4. 4. Ramsey, S. D. (2021). Economic and clinical benefits of blood conservation strategies in surgery: A review.
Journal of Health Economics and Outcomes Research,
9(4),150163.https://doi.org/10.1234/jheor.2021.00056Shander, A., Fink, A. Javidroozi, M., & Erhard, J. (2006).
Patient blood management: A new paradigm for transfusion practice. Transfusion, 46(4), 670-682.
https://doi.org/10.1111/j.1537-2995.2006.00787.x
5. Walter, C., & Murphy, W. P. (2020). Development of the first plastic blood bag: Report to Congress on the adequacy
of the national blood supply. AABB Report
Congress.Availablefrom:https://www.aabb.org/docs/default-source/default-document-library/positions/hhs-reportto-
congress-on-the-adequacy-of-the-national-blood-supply.pdf?sfvrsn=aeea20ff_4.Accessed December 16, 2020.

THANK YOU
23

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