Eesha Tariq@eesha_tariq899

Wave Tracker simplifies mobile network analysis and optimization with a range of powerful features: → Easy Network Analysis: Helps users understand and improve mobile network performance. → Target Audience: Ideal for telecom professionals, engineers, and general users curious about network performance. → Input Data: Users can input MCC, MNC, Cell ID, LAC codes, or location data for area coverage analysis. → Data Fetching: Utilizes OpenCellID API to retrieve tower signal strength, location, and other key details. → Speed Predictions: Estimates internet speeds based on tower data and signal strength. → AI-Powered Insights: Offers suggestions for network optimization, such as tower selection and reducing interference. → Interactive Visualization: Displays network performance through dynamic charts for better clarity and actionable insights. In conclusion, Wave Tracker provides a comprehensive and intuitive solution for users to analyze and optimize their mobile network performance. By combining real-time data with AI-driven insights, it empowers individuals and professionals alike to make informed decisions and improve connectivity. Whether you're troubleshooting network issues or enhancing coverage in rural areas, Wave Tracker is the go-to tool for smarter, more efficient network management.

The Smart Space Habitat Manager is a cutting-edge AI-driven solution designed to autonomously manage life-support systems in space habitats like the International Space Station (ISS), lunar bases, and Mars colonies. This system integrates real-time astronaut health monitoring, machine learning-based predictive maintenance, and statistical anomaly detection to prevent failures before they occur. By leveraging Random Forest regression models for failure prediction and statistical analysis for anomaly detection, it ensures a safe, self-sustaining environment without constant human intervention. Live sensor data tracking oxygen levels, temperature, CO₂ concentration, humidity, and power usage provides instant alerts for potential risks, enabling proactive decision-making. With its automated monitoring, predictive AI models, and real-time anomaly detection, this project represents a crucial step toward the future of sustainable space exploration, ensuring that astronauts remain safe while humanity expands beyond Earth

Overview HireGenius AI is an AI-powered job application assistant that automates job scraping, resume matching, and email generation. It is designed to streamline the hiring process for recruitment teams in leading companies like Infosys, TCS, and Accenture, helping them attract top engineering talent from industry leaders such as Google, Microsoft, and Amazon. Features ✨ Job Posting Scraper 📌: Extracts job descriptions from various job portals. Resume Matching 📊: Uses AI to analyze and compare resumes with job requirements. Automated Email Generation ✉️: Generates professional application emails tailored to job postings. Visualization 📈: Provides insights on job-resume match percentage with graphical representation. Open Source & Extensible 🛠: Fully customizable and open for contributions.

GraniteFit is a cutting-edge AI-powered platform that revolutionizes health tracking and workplace automation using IBM’s Granite AI. It integrates advanced AI-driven analytics, natural language processing (NLP), and predictive modeling to enhance productivity and well-being. Designed to cater to both corporate professionals and healthcare providers, GraniteFit offers a seamless experience by automating reminders, scheduling tasks, and improving personal and workplace efficiency. This AI-driven assistant not only simplifies daily tasks but also ensures a healthier lifestyle by sending personalized reminders for medication, hydration, physical activity, and work-related tasks. The system can intelligently analyze user behavior, predict needs, and provide real-time insights to optimize workflow and personal health. Leveraging IBM Granite AI, it ensures a highly scalable, secure, and adaptive AI model that evolves based on user interactions.