Webscraping project and Fire detection system project

1. TEAM
MEMBERS
Stanley Saji George (63)
Sajith Sajeev (54)
K Karthikeyan
(10)
Ken Jose
(14)
GUIDE’S
NAME
Er. Lini Ickappan
TEAM NO: 7

2. WEBSCRAPING
USING BEAUTIFUL
SOUP

3. WEBSCRAPING USING BEAUTIFUL SOUP
A Process of extracting data from
websites using automated tools or
software
Data collection: extract large
amounts of data from multiple
websites quickly and easily.
Competitive analysis: help
businesses gather information about
their competitors, such as pricing,
product offerings, and marketing
strategies.

4. WEBSCRAPING USING BEAUTIFUL SOUP
Lead generation: help businesses
collect contact information from
potential customers, such as email
addresses or phone numbers.
Content creation: used to gather
information for creating content, such
as news articles, blog posts, or social
media updates.
Market research: used to gather data
on consumer behavior, such as
product preferences, shopping habits,
and social media activity.

5. WEBSCRAPING IDEA ALREADY EXISTS ?
YES
DOES
CHANGES WE PLAN TO IMPLEMENT
• Respect the websites ToS
• Use ethical Webscraping techniques
• A User-Friendly GUI
• AI to enhance the webscraping process
• Using a distributed webscraping system

6. WEBSCRAPING DRAWBACKS
Limited browser support
Limited performance
Legality concerns
HTML inconsistencies
Data accuracy

7. WEBSCRAPING REQUIREMENTS
HARDWARE

8. WEBSCRAPING
USING BEAUTIFUL SOUP
REQUIREMENTS
SOFTWARE
• Beautiful soup
• PyCharm
• Visual Studio Code
• Sublime Text
• Requests library
• Pandas for data
manipulation or
• Selenium for web
automation
• A code editor or development environment

9. FIRE DETECTION
SYSTEM
USING AI & ML

10. FIRE DETECTION SYSTEM USING AI & ML
 To detect the presence of fire
 A combination of image processing and machine learning
techniques
 The system uses a camera to capture real-time images
and applies computer vision algorithms to detect fire-
related objects and patterns.
 The system is trained using a dataset of images to identify
potential fire hazards accurately.
 The proposed system can provide an early warning

11. FIRE DETECTION SYSTEM
IDEA ALREADY EXIST ?
DOES
YES
 Existing systems use AI algorithms
to analyze various types of data
 Images from cameras,
 temperature readings from sensors,
and
 smoke particle measurements,
 to detect fires in their early stages.

12. FIRE DETECTION SYSTEM
DRAWBACKS
 False alarms
 Limited coverage
 Delayed response
 Maintenance issues
Our AI-based fire detection systems use more
sophisticated algorithms and data sources to detect
fires quickly and accurately.

13. FIRE DETECTION SYSTEM
SOFTWARE
REQUIREMENTS
HARDWARE
OS
ML Libraries
DBMS
Real-time DPS
Sensors
Cameras
Networking
Equipments
Storage

14. THANK
YOU