blood bank in distributed data system

1. Distributed Blood Bank
Management System Database

2. Before I start my discussion
Let us know
What is Blood Bank?
2

3. What is Blood Bank?
• A blood bank is a cache or bank
of blood or blood components, gathered as a
result of blood donation or collection, stored
and preserved for later use in blood
transfusion.
• The term "blood bank" typically refers to a
division of a hospital where the storage of
blood product occurs and where proper
testing is performed.
3

4. Basic Project Overview
• In this project we are trying to implement
a distributed database from a centralized
database of Blood Bank Management
System.
• Here, we have designed a distributed
database system for Blood Bank
Management from a centralized database
system.
• Which will increase the system
performance, reliability and throughput.
4

5. Methodology
I have incorporated several methodologies for
creating this system, which is shown in next
slide
5

6. Methodology (Cont.)
6
Existing
System
Review i.e.
Centralized DB
Data
distribution
based on
horizontal
fragmentation
Getting Query
Statistics
Vertical
Fragmentation
based on
Query
statistics
Figure: Developing Methodology

7. Existing Centralized Database ERD
7

8. Sample Tables with Dates
8
Figure: Branch Table

9. Sample Tables with Dates (Cont.)
9
Figure: Donor Table

10. Distribution among sites
10
Site Name Site area
Blood Bank Chwakbazar Chwakbazar
Blood Bank CMCH Prabortok Circle
Blood Bank Bahaddarhat Chandgaon
Blood Bank Anderkilla Anderkilla
Blood Bank Agrabad Agrabad
Blood Bank New Market New Market
Blood Bank CEPZ CEPZ
Blood Bank Halishohor Halishohor

11. Distribution among sites (Cont.)
11
Chwakbazar
Halishohor
CEPZ
New
Market
Agrabad
Anderkilla
Chandgaon
Prabortok
Circle
Fig: Distributed Sites are connected with each Other where each of them has their
own data

12. Data Distribution techniques (Cont.)
• The result of previous shown query is given
below:
• By this way we have also selected our other
table values.
12

13. Query Statistics Collection
• We have assumed some queries. Based upon
that we’ll make decision for vertical
fragmentation.
• Suppose we have some applications in our site
which generate quires in following areas:
• Donor
– Find d_name,blood_group,phone via sub_area
– Update donor details
– Etc
13

14. Vertical Fragmentation based on
Query statistics
• We have fragmented the database vertically based on
the query written above.
• Fragments of Donor
– Donor_fragment1(d_id,d_name,address,blood_group,pho
ne)
– Donor_fragment1(d_id,br_id,area,sub_area,national_id,e
mail)
• Fragments of Blood_request
– Bloodrequest_frg1(name,address,hospital,blood_gruop,bl
ood_amount,phone)
– Bloodrequest_frg2(id,name,delivery_confirmation,email)
14

15. Average Response Time at
Centralized Database & Distributed
Database
15
0
5
10
15
20
25
30
Centralized
Distributed
Figure: Average Response Time at Centralized Database &
Distributed Database

16. System basic with graphical view
• Required Tools
Here we used Microsoft
office Access to create
the database and Microsoft
Visual Studio .NET
to design the interfaces.

17. Overview of Graphical
Presentation
• Donor Details
• Blood Collection
• Screening
• Component preparation
• Blood storage
• Blood request
• Compatibility
• Blood issue
• Monthly statistics

18. Compatibility Testing
 Before a transfusion, compatibility testing
between donor’s and patient’s blood must be
done. Firstly they perform testing to determine
the blood type of patients and perform cross
matching test to identify compatible blood
components for blood transfusions.

19. Compatibility testing interface

20. Blood issued
 They issue the components to the patient
according the compatibility report.
 To other hospitals they issue RBC only.

21. Blood issue interface

22. Monthly Statistics Analysis
 The following Statistical Analysis are
maintained by the Hospital Blood Bank.
a. Blood Collection
b. Blood Collection Of Summary
c. Collection Of Blood Group
d. Analysis Of RCC

23. Monthly statistics analysis
interface

24. Conclusion
 As the donor’s data is saved in the system we
can reject those who have HIV or any other
infections.
 As we have the contact number of the donor
we can contact donor whenever necessary
comes.
 Since we have the expiry date of the packs we
can have a proper storage management
system.