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1. J D COLLEGE OF ENGINEERING AND MANEGEMENT Department of CSE-(Data Science) PRESENTING SEMINAR ON PROJECT IDEAS Group No -11 DS17 Sheetal Pandey DS27 Ankit Adpawar DS44 Piyush Sarve DS54 Suraj Vaidya

2. AI-Powered Health Monitoring System Using Wearable Devices and Real time Data Analysis INTODUCTION AI-powered health monitoring systems excel in early detection of health issues. By continuously analyzing data, these systems can identify subtle changes that may indicate the onset of a medical condition. Wearable technology enables remote monitoring of patients and personalized care. Further recommendations will be available to the patients through AI algorithms on an individual's diet and exercise habits. These tailored suggestions aim to improve overall health and reduce the risk of chronic diseases .

3. PROBLEM STATEMENT Traditional healthcare systems often rely on periodic check-ups and patient recall for disease detection and management, leading to delayed interventions and increased healthcare costs. Wearable devices offer the potential for continuous health monitoring, but extracting meaningful insights from the vast amount of data generated remains a challenge. There is a critical need for an AI-powered system that can effectively analyze real-time health data from wearable devices to enable early detection of health anomalies, personalized interventions, and improved patient outcomes

4. Objectives Data Generation: Collection and Processing: Develop a robust data collection framework to capture relevant health metrics from wearable devices. Ensure data quality, security, and privacy through appropriate measures. Develop efficient data preprocessing and cleaning techniques. AI Model Development: Design and implement AI algorithms for anomaly detection, pattern recognition, and predictive modeling. Train and optimize AI models using relevant datasets. Evaluate the performance and accuracy of developed models.

5. APPLICATION OF AN AI POWERED HEALTH MONITORING SYSTEM An AI-powered health monitoring system using wearable devices has a wide range of applications across various healthcare and wellness domains. Here are some key areas: Healthcare Chronic Disease Management: Effective monitoring of conditions like diabetes, hypertension, heart disease, and asthma. Elderly Care: Early detection of falls, cognitive decline, and other age-related health issues. Remote Patient Monitoring: Enabling continuous monitoring of patients with chronic conditions, reducing hospital readmissions. Post-operative Care: Tracking patient recovery and identifying potential complications. Mental Health: Monitoring stress, anxiety, and depression levels. A

6. Wellness and Fitness Personal Health Management: Tracking fitness goals, sleep patterns, and nutrition. Sports Performance: Analyzing athlete performance metrics to optimize training regimens. Workplace Wellness: Promoting employee well-being and preventing burnout. Research Population Health Studies: Gathering large-scale health data for epidemiological research. Drug Development: Identifying potential drug targets and monitoring treatment efficacy. Wearable Technology Research: Developing new wearable sensors and devices. Specific Use Cases

7. SCOPE OF THE PROJECT Core Functionalities Data Acquisition: Collecting various physiological data from wearable devices (e.g., heart rate, blood pressure, blood oxygen levels, temperature, sleep patterns, physical activity). Data Preprocessing: Cleaning, filtering, and transforming raw data into a suitable format for analysis. AI Model Development: Creating and training AI models for anomaly detection, pattern recognition, and predictive modeling . Insight Generation: Deriving meaningful insights and actionable recommendations from analyzed data. User Interface Development: Designing and implementing a user-friendly platform to display health metrics, trends, and recommendations .

8. System Integration Wearable Device Compatibility: Ensuring compatibility with a range of wearable devices. Data Transmission: Securely transferring data from wearable devices to the central system. Data Storage: Storing collected data in a secure and scalable manner. Integration with Healthcare Systems: Potential integration with electronic health records (EHR) for data sharing and interoperability. User Experience User Interface Design : Creating an intuitive and engaging user interface for different user segments (e.g., patients, healthcare providers, researchers). Data Privacy and Security: Implementing robust measures to protect user data and comply with relevant regulations. User Education: Providing clear instructions and guidance on using the system effectively.

9. Personal finance tracker using python and flask INTRODUCTION A personal finance tracker is a web application that helps users manage their finances by tracking income, expenses, budgets, and savings. The application aims to provide users with insights into their spending habits, allowing them to make informed financial decision

10. ABSTRACT The Personal Finance Tracker is a web-based application developed using Python and Flask that aims to help users manage their personal finances efficiently. The application provides a user-friendly platform for individuals to track their income and expenses, categorize transactions, and gain valuable insights.

11. PROBLEM STATEMENT Managing personal finances is a crucial skill that helps individuals maintain control over their spending, savings, and investments. Many people struggle with keeping track of their income, expenses, and financial goals, leading to poor financial decisions and stress. A personal finance tracker aims to simplify this process by providing users with an organized, user-friendly tool to monitor their finances.

12. OBJECTIVE To develop a web-based application that allows users to track and manage their personal finances. The application should enable users to log their income and expenses, categorize transactions, visualize their financial data, and generate reports to gain insights into their financial habits.

13. SCOPE OF THE PROJECT This scope provides a comprehensive outline of the project's goals, features, and limitations. It sets the stage for a focused development process that aims to deliver a functional and user-friendly personal finance tracker application

14. REFERENCE Flask Web Development: Developing Web Applications with Python by Miguel Grinberg Flask Framework Cookbook by Shalabh Aggarwal

15. Software Specifications Python :Core language for developing the backend using the Flask framework. HTML :For creating the structure of the web pages (e.g., forms, lists, headings). CSS :For styling the web pages to make them look appealing. JavaScript :For adding interactivity to the web pages (optional for basic functionality but useful for advanced features). SQL (optional) :If you choose to use a relational database like SQLite or PostgreSQL for data persistence.

16. Software Specifications Flask :A Python web framework for handling routing, templating, and HTTP requests. Additional Tools and LibrariesJinja2:Template engine for Python (used by Flask) to render HTML templates. Flask-WTF (optional) :For working with web forms in Flask more easily. SQLAlchemy or Flask- SQLAlchemy (optional) :For database interactions if you choose to use a relational database.

17. SENTIMENT ANALYSIS OF SOCIAL MEDIA

18. - Contents - What is Sentiment Analysis? Why is it needed? How social media sentiment is measured? Application areas of Sentiment Analysis Challenges and advantages Analysis and Outcomes Conclusion

19. WHAT IS SENTIMENT ANALYSIS? Social Sentiment refers to the emotion behind a social mention. It means monitoring social media posts and discussions, then figuring out how participants are reacting. It involves applying Natural Language Processing (NLP) to social mentions and determining whether the user is responding in a positive, negative or neutral manner.

20. HOW IS IT MEASURED? It involves checking how many negative and positive keywords are present in a chunk of conversation. If there are more positive keywords, it is considered Positive content. If there are more negative keywords, it is called Negative content. Or If it contains a mixture of negative and positive words, it’ll be called a Neutral content

21. CHALLENGES WHILE MAKING THIS PROJECT

22. Customer recommendation decision Emotion analysis in product reviews Predicting review usefulness Brand monitoring Applications