DBMS PPT(CRIME DATABASE).pptx Database s

DBMS project ppt

1. DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING DBMS MINI PROJECT PRESENTATION ON CRIME DATABASE MANAGENENT SYSTEM -Submitted By: (5 TH SEM AIML) Prajwal Mathapati(3GN21AI037) Prithviraj Kalyan(3GN21AI040) Rahul Reddy(3GN21AI041) Sachin V Bacha(3GN21AI044)

2. 3.System Requirements CONTENT 1.Introduction 2.Entity-Relationship Diagram (ERD) 4.Implementation 5.Conclusion and Future Scope

3. INTRODUCTION: Crime Database Management System Crime data plays a crucial role in law enforcement and crime prevention strategies. Efficient management and analysis of this data are essential for investigators and authorities. In this presentation, we'll unveil our crime database management system, a mini-project built using DB2 as the backend database and Python for the frontend. We'll explore how this system empowers law enforcement personnel with efficient data management and retrieval capabilities. Its streamlined approach to data insertion and retrieval aims to enhance operational efficiency and support informed decision-making in the realm of criminal justice.

4. Entity-Relationship Diagram (ERD):

5. Entity-Relationship Diagram (ERD): Our Crime Database utilizes an Entity-Relationship Diagram (ERD) to model the relationships between different data entities: Crime Entity: Stores details about crime incidents (date, time, location, type of crime). Victim Entity (Optional): Captures information about victims (name, demographics, contact details). Suspect Entity (Optional): Stores information about suspects (name, demographics, contact details). Location Entity: Stores details about crime locations (address, coordinates). Relationships: -A Crime can have zero or one Victim. -A Crime can have zero or one Suspect. -A Crime always occurs at a Location.

6. SYSTEM REQUIREMENTS: Hardware requirements : Any modern updated Operating System (preferably 64-bit architecture) Minimum of 4 GB Ram The Disk space mainly depends on the size of data we will be dealing with ,but minimum of 1GB is sufficient. Technologies Used : Python (version-3.11.0) Db2(version-3.1.0) Streamlit Pandas

7. Why DB2? DB2, a robust DBMS by IBM, was chosen for its: Scalability: Ability to handle massive datasets of crime incidents efficiently. Security: Built-in features to safeguard sensitive crime data, ensuring data privacy and integrity. Reliability: Proven track record of uptime and data integrity for crucial crime information. In this project, DB2 is likely used as the backend database to store and manage the data.

8. The Python Advantage: Python, a versatile programming language, provided the foundation for the project's frontend: Readability: Clear and concise syntax for easy development and maintenance of the user interface. Extensive Libraries: Streamlit for creating interactive web apps, DB2 for database interactions, Pandas for data manipulation and visualization. Cross-Platform Compatibility: Runs seamlessly on various operating systems, making the application accessible. In this project, Python is likely used for various tasks such as backend development, scripting, and data manipulation.

9. Streamlit in Action: Streamlit simplifies web app creation for the Crime Database: User-Friendly Interface: Effortless development of interactive dashboards for crime data visualization (e.g., location heatmaps, crime type charts). Real-Time Updates: Data reflects changes instantaneously, ensuring users have the latest information. Streamlined Deployment: Easy sharing of the web app for wider access by authorized personnel. - In this project, Streamlit is likely used to create a user interface (UI) for interacting with the DBMS, providing features such as data visualization, querying the database, and displaying results.

10. Unleashing the Power of DB2 with Python: Python's DB2 library bridges the gap between code and the DB2 database: Seamless Interactions: Python code interacts effortlessly with the DB2 database for CRUD (Create, Read, Update, Delete) operations on crime data. SQL Execution: Allows execution of SQL queries for efficient retrieval and manipulation of crime data. Data Integration: Facilitates seamless integration of crime data from DB2 into the Python environment for analysis and visualization.

11. IMPLEMENTATION:   Setting Up the Environment: -Install the chosen DBMS on the development environment. -Set up any necessary tools or libraries required for development. Create Database and Tables: -Write SQL scripts to create the database and necessary tables based on the designed schema. Implement Data Manipulation Logic: -Write SQL queries to insert, update, delete, and retrieve data from the tables. -Implement any necessary constraints or triggers. Implement Application Logic: - Develop the application logic to interact with the database. - This may involve writing server-side scripts to connect the database, APIs, or client-side code depending on the project requirements.

12. TESTING: HERE IS OUR APPLICATION LINK: https://crime-database.streamlit.app/ Data Insertion page for the application  

13. TESTING: HERE IS OUR APPLICATION LINK: https://crime-database.streamlit.app/ Data Retrieval page for the application  

14. CONCLUSION AND FUTURE SCOPE: Conclusions Simplicity is never simple. As we have seen in this project, the provided database schema offers a fundamental framework for managing information related to criminal incidents and the individuals involved. It efficiently captures data regarding persons, incidents, and their relationships through participation and potential matches. However, to fully support comprehensive criminal investigations, additional entities and attributes should be considered. The project can be updated in the near future as and when the requirement for the same arises, as it is very flexible in terms of expansion. With the proposed software for database Space Manager ready and fully functional, the client is now able to manage and hence run the entire work in a much better, more accurate, and error-free manner.

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