WAQAS ALI@WAQAS

Disease identify and mapping are artificial intelligence use camera to capture and give report output from disease symptoms it's like our doctor watching our health as private healthcare, and give us good response to our disease. It's taking much time to our doctor for take information from patients, it's more useful make this AI trainable for our doctor and the fast respon and massif data collecting make our doctor job's less busy and they can take attention to our health development time by time Starts from now. But in this prototype I'm use a small case with Small data but not in real time condition.

We're Team TerraSentinels part of MindsDB hackathon , on a mission to revolutionize land use monitoring with AI and geospatial data! Our project: Intelligent Land Use Monitoring Agent, aims to detect unauthorized land use, deforestation, and urban expansion in real-time by analyzing satellite images and large-scale geospatial datasets. We plan to use tech like MindsDB, Google Earth Engine, and TensorFlow, all wrapped in a sleek web interface with Flask. If you're passionate about AI, geospatial data, or just love tackling big challenges with a positive, can-do attitude, we’d love to have you on board!

Granite Gurus Many Eyes is an extension of three previous Hackathons: Build Your AI Startup, Codestral, and Edge Runners. This Hackathon introduced two powerful principles: (1) Uniqueness and (2) Many Eyes, both of which were crucial in advancing the exploration of Multidimensional (MD) space. These principles were effectively demonstrated through a custom search engine built on top of IBM Granite, highlighting their transformative potential. The Principle of Uniqueness asserts that spatial points can be arranged in any configuration as long as the number of points remains constant and each point is unique. This principle underpins the 2D Infinite Plane, which aids in visualizing interactions in higher dimensions and emphasizes representing numeric values as symbols rather than numbers to reduce computational costs. The Principle of Many Eyes posits that knowing one aspect of a system allows for understanding the entire system, thanks to the symmetries in MD-space. Unlike traditional programming, where functions have a single input and output, MD-systems can yield multiple outputs from a single input by leveraging these symmetries. This was illustrated in our use of IBM Granite for pattern search, which returned multiple results due to MD-space symmetries, and then predicted the next pattern, showcasing the system's adaptability. Integrating IBM Granite with the 2D Infinite Mathematical solution creates a powerful combination that enhances search engine performance by reducing computational overhead, improving accuracy, and accelerating processing times. This approach not only offers a superior user experience but also aligns with sustainability and cost-saving goals, positioning the search engine as a leader in the AI-driven market. By optimizing resources and delivering faster, more accurate results, this project demonstrates the potential to revolutionize search technology, making it a valuable asset for businesses aiming to lead in the AI space.