Crime Record Management System

CHAPTER 1

INTRODUCTION

1.1 Overview

The Crime Record Database Management System (CRDMS) is a comprehensive and

secure web-based software solution developed to streamline and modernize the way law
enforcement agencies handle crime-related information. In an era where data accuracy,
speed, and security are vital, the CRDMS provides a centralized digital platform to manage
critical records such as First Information Reports (FIRs), victim and accused profiles,
witness statements, police officer records, and more. The primary goal is to replace
inefficient, error-prone, and time-consuming manual record-keeping practices with an
efficient, integrated digital system.

By leveraging the capabilities of modern web technologies and a robust relational

database, CRDMS ensures fast data entry, easy retrieval, and secure storage of crime-
related records. The system enhances investigative processes, improves data integrity, and
supports decision-making by providing accurate, up-to-date information to authorized
users and maintains detailed logs of user activities.

1.2 Problem Statement

In traditional police record-keeping systems, data is often stored in physical registers or

outdated software, which makes it difficult to track criminal activities, analyze crime
patterns, and maintain secure records. This manual process is time-consuming, prone to
human errors, and lacks centralized access control.

The Crime Record Database Management System seeks to solve these challenges by:
Replacing paper-based records with a digital database.
Allowing officers to register, update, and monitor FIRs through a secure portal.
Enabling real-time tracking of case status and associated individuals.
Providing an admin dashboard to manage officer activity and ensure system integrity.
Facilitating better communication, transparency, and accountability within the department.

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1.3 Objectives

Key Objectives:

Digitization of Crime Data: To shift from manual documentation to a fully digital

platform that enables real-time data capture and retrieval.

Security and Privacy: To ensure that only authorized personnel have access to sensitive
criminal records, and that all data is handled with confidentiality.

Data Centralization: To maintain all case-related records in a centralized database,

accessible from multiple authorized locations or users within an agency.

Operational Efficiency: To significantly reduce paperwork, save time during

investigations, and help agencies respond more quickly to crimes.

Scalability and Extensibility: To allow easy future enhancements like biometric

integration, mobile apps, or integration with national crime databases.

Key Features:

1. Centralized and Role-Based Access to Crime Data

The CRDMS supports hierarchical access control, where different user roles (Admin,
Officer) have specific access rights. Administrators can manage officer records, reset
credentials, and monitor system usage, while Officers can file and manage FIRs. This
ensures that sensitive data is only accessible to users with the appropriate permissions.

2. Digital Filing and Management of FIRs

Officers can digitally enter detailed FIRs including crime type, date, location, suspect
information, and a description of events. Each FIR can be linked to victims, accused
individuals, and witnesses. This digital filing process minimizes paperwork, avoids loss of
information, and provides a searchable archive of criminal cases.

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3. Secure Login System and Activity Logging

The application includes a login system with encrypted passwords and user session
tracking. Every login activity is logged with timestamps, allowing administrators to
monitor officer usage patterns and ensure accountability.

4. Structured Relational Database

The backend is powered by a normalized relational database (Oracle), which ensures that
data is stored efficiently without redundancy. Tables are interconnected using foreign keys
to maintain data integrity, and queries are optimized for fast performance and accuracy.

5. Intuitive and Responsive Web Interface

The user interface, built with HTML, CSS, JavaScript, and Bootstrap, is designed to be
user-friendly and responsive. Whether accessing from a desktop or mobile device, the
system offers easy navigation, form-based data entry, and real-time validation, making it
usable even by non-technical staff.

6. Real-Time Crime Reporting and Monitoring

The system allows law enforcement personnel to file reports and update cases in real-time,
ensuring that the most current information is available for decision-making and
investigations. Search and filter options allow users to locate specific FIRs, victims, or
accused individuals quickly.

7. Audit Trails and Data Integrity

Every action performed in the system can be tracked, including data additions, edits, and
deletions. This ensures a complete audit trail, which is essential for transparency and legal
compliance.

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1.4 Scope of Project

This system is designed for deployment within police stations or law enforcement
agencies. It is intended for use by authenticated officers and admins, and it supports the
following key features:

 Officer login and FIR submission portal.

 Admin dashboard to monitor all registered records.
 Victim and accused data linking to specific FIRs.
 Case status updates and investigation tracking.
 Secure storage using Oracle Database and backend logic via Flask.

In future iterations, the system can be extended to support analytics dashboards,

biometric or face recognition systems, and public portals for victim updates.

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Chapter 2

BACK END DESIGN

2.1 Back End Implementation using Python

The back end of the Crime Record Database Management System (CRDMS) is
implemented using Python with the Flask web framework. Flask is a lightweight, flexible,
and efficient framework ideal for building secure web applications. It handles server-side
operations such as routing, user authentication, database interactions, and form handling.

In CRDMS, Python scripts handle operations like login validation for police officers and
administrators, FIR registration, data retrieval, and record updates. All these operations
interact with the Oracle Database using the OracleDB as cx_Oracle library, ensuring
smooth communication between the front end and the database.

The system ensures data validation and implements security measures such as password
hashing and session management to prevent unauthorized access. Flask’s modular
structure allows clear separation of concerns, making the codebase organized,
maintainable, and scalable for future enhancements.

2.2 Conceptual Database Design (ER Diagram)

The Entity-Relationship (ER) model for the Crime Record Database Management System
represents the key entities involved in crime management and their relationships. The main
goal is to capture comprehensive and relational data concerning crimes, officers, victims,
accused individuals, and FIRs.
Entities:
1. Officer
 Officer_ID (PK)
 Name
 Badge_number
 Rank
 Station
 Contact

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2. Admin
 Admin_ID (PK)
 Username
 Password

3. Victim
 Victim_ID (PK)
 Name
 Age
 Gender
 Address
 Contact
4. Accused
 Accused_ID (PK)
 Name
 Age
 Gender
 Address
 Criminal_Record (Yes/No)
6. FIR
 FIR_ID (PK)
 Date_Filed
 Crime_Type
 Description
 Location
 Officer_ID (FK)
 Victim_ID (FK)
 Accused_ID (FK)
 Status (Pending/Closed)

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Relationships:
 An Officer can handle multiple FIRs.
 Each FIR is filed against one or more Accused and involves one or more
victims.
 An Admin can view, update, or delete records but does not file FIRs.

2.3 Logical Database Design

The conceptual schema is mapped to a logical schema, converting entities into relational
tables, and relationships into foreign keys.

Relational Schema:

Officer(Officer_ID, Name, Rank, Station, Contact)

Admin(Admin_ID, Username, Password)

Victim(Victim_ID, Name, Age, Gender, Address, Contact)

Accused(Accused_ID, Name, Age, Gender, Address, Criminal_Record)

FIR(FIR_ID, Date_Filed, Crime_Type, Description, Location, Officer_ID, Victim_ID,

Accused_ID, Status)

Foreign Key Constraints:

FIR.Officer_ID → Officer.Officer_ID

FIR.Victim_ID → Victim.Victim_ID

FIR.Accused_ID → Accused.Accused_ID

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ER Diagram

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Flow Chart

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ER Mapping

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2.4 Normalization

Normalization is a structured method used in database design to organize data

efficiently. It involves decomposing larger tables into smaller, interrelated tables to
remove redundancy and prevent inconsistencies during data operations such as insert,
update, or delete. The main purpose is to maintain data accuracy and integrity while
minimizing duplicate information.

Key objectives of normalization include:

 Reducing repetitive and unnecessary data.

 Ensuring that the data relationships and dependencies are properly structured
and logically maintained.

2.4.1 First Normal Form (1NF):

A table is said to be in First Normal Form when:

 Each field contains only atomic (indivisible) values.

 Every record is distinct, and there are no repeating groups or multivalued
attributes.

FIR Crime Victim Victim Officer Officer

Date Location
ID Type Name Contact ID Name

101 2025-05-01 Robbery Delhi Ramesh 9876543210 1 Inspector Raj

102 2025-05-02 Theft Mumbai Suresh 8765432109 2 Inspector Meena

Observation:
This structure follows 1NF because each field cannot be divided into multiple values, and
it is atomic.

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2.4.2 Second Normal Form (2NF):

A table is in Second Normal Form if:

 It is already in 1NF.
 All non-key attributes are fully functionally dependent on the entire primary key
(i.e., no partial dependency).

Decomposition for 2NF:

We separate entities such as victims and officers into independent tables:

FIR_ID Date Crime_Type Location Officer_ID

101 2025-05-01 Robbery Delhi 1

102 2025-05-02 Theft Mumbai 2

Victim Table

Victim_ID FIR_ID Name Contact

V01 101 Ramesh 9876543210

V02 102 Suresh 8765432109

Officer Table

Officer_ID Officer_Name

1 Inspector Raj

2 Inspector Meena

Observation:
By splitting the table, we ensure no attribute is dependent on only a part of a composite
key.

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2.4.3 Third Normal Form (3NF):

A table is in Third Normal Form when:

 It is in 2NF.
 There is no transitive dependency (i.e., non-key attributes do not depend on other
non-key attributes).

Decomposition for 3NF

Officer_ID Name Department

1 Inspector Raj Crime Branch

2 Inspector Meena Theft Squad

Department Table:

Department_ID Department_Name

D01 Crime Branch

D02 Theft Squad

Observation:
Now, officer names do not determine department names. Instead, departments are stored
separately and linked via identifiers, avoiding transitive dependencies.

Final Result:

After applying all three normal forms:

 Data is atomic and organized.

 There is no redundant storage.
 Dependencies are properly defined, reducing anomalies during operations.

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CHAPTER 3

FRONT END

3.1 Screen Layout Design

In the Crime Record Database Management System (CRDMS), HTML (HyperText

Markup Language) serves as the backbone for building the structure and layout of the user
interface. HTML is used to create the various web pages, including login screens, data
entry forms, case management dashboards, and reports. Each page is composed of HTML
elements such as headings, tables, input fields, buttons, and links, all enclosed within tags
like <html>, <body>, <form>, and <table>. The project uses Flask’s Jinja2 templating
engine to dynamically generate HTML pages, enabling seamless integration of data
retrieved from the Oracle database into the web pages. This ensures that the interface can
display updated information such as FIR details, accused or victim records, and officer
logs in a clear and organized manner.

The frontend is designed with user convenience in mind, prioritizing a straightforward and
intuitive layout that enables police officers and administrators to navigate easily between
different functionalities. Forms and data tables are organized logically to support efficient
workflows, such as filing new FIRs or updating case information. Additionally, the use of
semantic HTML5 elements enhances code readability and accessibility, contributing to a
more maintainable and scalable frontend codebase.

CSS (Cascading Style Sheets) is applied extensively throughout CRDMS to define the
visual style and enhance the usability of the system’s web pages. The project incorporates
Bootstrap, a popular CSS framework, to implement responsive design principles and
consistent styling across all pages. Bootstrap provides pre-defined classes and components
such as buttons, forms, navigation bars, and grids, which help maintain uniformity in look
and feel while reducing development time. By using Bootstrap alongside custom CSS, the
application achieves a clean, modern, and user-friendly interface that works smoothly
across different screen sizes and devices. The use of CSS ensures that the layout is well-
structured, readable, and visually appealing to users including police officers and
administrators.

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Bootstrap’s responsive grid system plays a vital role in making the application mobile-
friendly, allowing the interface to adapt seamlessly to various screen sizes ranging from
desktop monitors to tablets and smartphones. This responsiveness is crucial for users who
may need to access the system remotely or while on patrol, ensuring continuous
availability of important crime data and case management tools.

Furthermore, CSS3 animations and transitions are used subtly to improve user experience
by providing visual feedback on interactive elements such as buttons and form inputs.
These enhancements make the interface feel more dynamic and engaging without
distracting from its core functionality.

3.2 Frontend-Backend Connectivity

The integration between the frontend and backend of the CRDMS is handled by the Flask
framework, which serves as the web application’s core server. Flask manages HTTP
requests submitted through HTML forms and URLs, processing these inputs via Python
functions that interact with the Oracle database using the cx_Oracle library. After
performing operations such as creating, updating, or retrieving crime records, Flask
dynamically renders updated HTML pages by injecting database results into templates
with Jinja2 syntax. This mechanism allows for smooth, real-time data exchange and
presentation, enabling users to efficiently perform tasks such as logging FIRs, tracking
accused or victim information, and reviewing case statuses. The combination of Flask,
HTML, CSS (Bootstrap), and Oracle ensures a reliable and effective communication
channel between the user interface and the underlying database.

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Chapter 4

IMPLEMENTATION

4.1 SQLDeveloper

Oracle SQL Developer and Oracle XE (Latest Version)

For managing and interacting with the backend database, Oracle SQL Developer was used
as the primary graphical interface. It provides a user-friendly environment to run SQL
queries, manage database objects, and perform administrative tasks efficiently. The project
utilized the latest version of Oracle Database Express Edition (Oracle XE), a lightweight,
free-to-use version of Oracle's enterprise-grade database. Oracle XE is ideal for
development and deployment of smaller-scale applications, offering powerful features like
PL/SQL support, data security, and fast transaction processing, all within a simplified
setup. Integration with SQL Developer enabled smooth testing, debugging, and
optimization of SQL commands in real-time.

-- Oracle Database Schema for Crime Record Database Management System

-- Create Police Station Table

CREATE TABLE Police_Station (

station_id NUMBER PRIMARY KEY,

name VARCHAR2(100),

location VARCHAR2(150) );

-- Create Admin Table

CREATE TABLE Admin (

admin_id NUMBER PRIMARY KEY,

username VARCHAR2(50) UNIQUE NOT NULL,

password VARCHAR2(50) NOT NULL

);

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-- Create Officer Table

CREATE TABLE Officer (

officer_id NUMBER PRIMARY KEY,

username VARCHAR2(50) UNIQUE NOT NULL,

password VARCHAR2(50) NOT NULL,

name VARCHAR2(100),

rank VARCHAR2(50),

contact VARCHAR2(15),

station_id NUMBER,

badge_number VARCHAR2(20),

FOREIGN KEY (station_id) REFERENCES Police_Station(station_id)

);

-- Create Victim Table

CREATE TABLE Victim (

victim_id NUMBER PRIMARY KEY,

name VARCHAR2(100),

contact VARCHAR2(15),

added_by_officer_id NUMBER,

FOREIGN KEY (added_by_officer_id) REFERENCES Officer(officer_id)

);

-- Create Accused Table

CREATE TABLE Accused (

accused_id NUMBER PRIMARY KEY,

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name VARCHAR2(100),

status VARCHAR2(50),

added_by_officer_id NUMBER,

FOREIGN KEY (added_by_officer_id) REFERENCES Officer(officer_id)

);

-- Create Witness Table

CREATE TABLE Witness (

witness_id NUMBER PRIMARY KEY,

name VARCHAR2(100),

contact VARCHAR2(15) );

-- Create FIR Table

CREATE TABLE FIR (

fir_id NUMBER PRIMARY KEY,

officer_id NUMBER,

victim_id NUMBER,

accused_id NUMBER,

crime_type VARCHAR2(100),

description CLOB,

status VARCHAR2(50),

last_modified TIMESTAMP,

FOREIGN KEY (officer_id) REFERENCES Officer(officer_id),

FOREIGN KEY (victim_id) REFERENCES Victim(victim_id),

FOREIGN KEY (accused_id) REFERENCES Accused(accused_id) );

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-- Create FIR_Witness Table (Many-to-Many mapping between FIR and Witness)

CREATE TABLE FIR_Witness (

fir_id NUMBER,

witness_id NUMBER,

PRIMARY KEY (fir_id, witness_id),

FOREIGN KEY (fir_id) REFERENCES FIR(fir_id),

FOREIGN KEY (witness_id) REFERENCES Witness(witness_id) );

-- Create Login_Log Table to track Officer logins

CREATE TABLE Login_Log (

log_id NUMBER GENERATED ALWAYS AS IDENTITY PRIMARY KEY,

officer_id NUMBER,

login_time TIMESTAMP DEFAULT CURRENT_TIMESTAMP,

FOREIGN KEY (officer_id) REFERENCES Officer(officer_id) );

-- Create Sequences for auto-incrementing primary keys

CREATE SEQUENCE fir_seq START WITH 1 INCREMENT BY 1;

CREATE SEQUENCE victim_seq START WITH 1 INCREMENT BY 1;

CREATE SEQUENCE accused_seq START WITH 1 INCREMENT BY 1;

CREATE SEQUENCE login_history_seq START WITH 1 INCREMENT BY 1;

CREATE SEQUENCE officer_seq START WITH 1 INCREMENT BY 1;

COMMIT;

-- Trigger to auto-update last_modified timestamp on FIR insert/update

CREATE OR REPLACE TRIGGER trg_fir_set_last_modified

BEFORE INSERT OR UPDATE ON FIR

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FOR EACH ROW

BEGIN

:NEW.last_modified := SYSTIMESTAMP;

END;

-- Sample data for Police Stations

INSERT INTO Police_Station (station_id, name, location) VALUES

(1, 'Central Police Station', 'Downtown'),

(2, 'Northside Police Station', 'North District');

-- Sample data for Admins

INSERT INTO Admin (admin_id, username, password) VALUES

(101, 'admin', 'padmin123');

-- Sample data for Officers

INSERT INTO Officer (officer_id, username, password, name, rank, contact, station_id,
badge_number) VALUES

(1, 'officer_john', 'johnpass', 'John Doe', 'Inspector', '555-1234', 1, 'B123'),

(2, 'officer_jane', 'janepass', 'Jane Smith', 'Sergeant', '555-5678', 2, 'B456');

-- Sample data for Victims

INSERT INTO Victim (victim_id, name, contact, added_by_officer_id) VALUES

(1, 'Alice Brown', '555-8765', 1),

(2, 'Bob Green', '555-4321', 2);

-- Sample data for Accused

INSERT INTO Accused (accused_id, name, status, added_by_officer_id) VALUES

(1, 'Charlie Black', 'At Large', 1),

(2, 'David White', 'In Custody', 2);

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-- Sample data for Witnesses

INSERT INTO Witness (witness_id, name, contact) VALUES (1, 'Eve Blue', '555-9999'),

(2, 'Frank Red', '555-8888');

-- Sample data for FIRs

INSERT INTO FIR (fir_id, officer_id, victim_id, accused_id, crime_type, description,

status) VALUES

(1, 1, 1, 1, 'Robbery', 'Suspect robbed a convenience store.', 'Open'),

(2, 2, 2, 2, 'Assault', 'Physical altercation reported at a park.', 'Closed');

-- Sample data for FIR_Witness mapping

INSERT INTO FIR_Witness (fir_id, witness_id) VALUES(1, 1), (1, 2), (2, 2);

-- Sample data for Login_Log (officer logins)

INSERT INTO Login_Log (officer_id) VALUES (1), (2);

4.2 Flask Apllication

The Flask Application forms the backbone of the CRDMS project, acting as the bridge
between the front-end user interface and the back-end Oracle database. Flask, a
lightweight and powerful Python-based micro web framework, was chosen for its
simplicity, flexibility, and ease of integration with other tools and databases.

Key Roles of Flask in the Project:

1. Routing and URL Handling

Flask handles HTTP requests and maps URLs to Python functions using a simple
and intuitive routing system. Each module of our CRDMS (such as FIR
registration, login, victim/accused management) is tied to specific routes,
allowing the system to serve different functionalities through clean and
manageable endpoints.

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2. Database Connectivity using cx_Oracle

Flask integrates with the Oracle Database through the cx_Oracle library. This
connection allows our application to perform operations such as inserting new
FIRs, fetching login logs, updating victim or accused details, and generating
reports directly from the database.
3. Role-Based Access Control
Flask sessions and logic were used to differentiate between user roles—admin
and officer. Based on login credentials, the application redirects users to
appropriate dashboards and restricts unauthorized access to sensitive modules.
4. Form Handling and Data Validation
HTML forms for login, FIR entry, victim/accused details, and witness association
are processed by Flask’s backend. The application ensures input validation and
sanitization to prevent incorrect or malicious data entries.
5. Dynamic Content Rendering with Templates
Using Flask’s Jinja2 templating engine, we rendered dynamic content such as
FIR details, user logs, and lists of cases. This makes the web interface responsive
and data-driven.
6. RESTful API Structure (Optional/Advanced)
For scalability and future enhancements, the Flask app follows a RESTful
design, making it easy to extend for API consumption by mobile apps or other
web clients.
7. Security Features
Basic security features like password hashing, login session management, and
input validation were implemented to protect against unauthorized access and
vulnerabilities such as SQL injection.

Benefits of Using Flask:

 Lightweight and modular, ideal for academic and prototype-level projects.

 Easy to learn and code, reducing development time.
 Highly customizable, enabling integration with third-party libraries.
 Good community support and documentation.

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CHAPTER 5

SNAPSHOTS

Figure 5.1 HomePage

Figure 5.2 Admin login

Figure 5.3 Admin Dash Board

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Figure 5.4 Add Officer

Figure 5.5 Update Officer

Figure 5.6 Remove Officer

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Figure 5.7 Officer Login

Figure 5.8 Officer Dashboard

Figure 5.9 Add FIR

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Figure 5.10 Add Victim

Figure 5.11 Add Accused

Figure 5.12 Add Witness

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Fig 5.13 FIR Details

Fig 5.14 FIR Logs

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CHAPTER 6

CONCLUSION

The Crime Record Database Management System (CRDMS) is a comprehensive,

scalable, and secure solution designed to digitalize and streamline the crime reporting and
investigation process for law enforcement agencies. Through this project, we have
successfully demonstrated how modern database systems, coupled with intuitive web-
based interfaces and robust backend frameworks, can significantly enhance the efficiency,
transparency, and accuracy of crime data management.

From the conceptualization phase involving Entity-Relationship (ER) modeling and

normalization to the final implementation using Flask (Python) for the backend and Oracle
Database for storage, every component was carefully designed to reflect real-world
requirements. The system enables various stakeholders—such as administrators, officers,
and investigators—to seamlessly interact with the data related to FIRs, accused persons,
victims, witnesses, and login logs, thereby eliminating the need for inefficient manual
paperwork.

Key features like officer login tracking, witness-FIR mapping, and role-based access
control ensure data integrity and traceability, which are critical in sensitive environments
like law enforcement. Furthermore, the use of SQL triggers and constraints enforces
business logic at the database level, ensuring that data remains consistent and valid even
in complex transactional scenarios.

The CRDMS not only offers a solid backend foundation but is also easily extendable to
support future integrations such as real-time analytics, AI-based crime pattern detection,
and mobile accessibility. This ensures its long-term relevance and adaptability in a fast-
evolving technological landscape.

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Through this project, we gained practical exposure to full-stack application development,

advanced SQL programming, backend API handling, and database design principles. It
has equipped us with the essential technical competencies needed to solve real-life data
management challenges and demonstrated the importance of well-structured systems in
critical domains such as law enforcement.

In conclusion, the CRDMS serves as a powerful testament to the role of computer science
and database systems in building safer, smarter communities by enabling data-driven
policing, improving accountability, and ensuring swift justice delivery. This project not
only fulfills academic goals but also lays the groundwork for building more intelligent
public service platforms in the future.

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