Do you hate wasting ketchup or other sauces from your favorite food bottle? You're not alone. Millions of tons of sauce go to waste every year, just because it's difficult to get the last few drops out of the bottle. That's why I designed and developed a zero waste dispenser that gets out more than 99% of the content. My dispenser features a novel linear-to-rotary mechanism that allows sauce to flow out based on the user's tilt, eliminating waste and keeping your food tasting great..

As the world grapples with the effects of climate change and the need for more sustainable farming practices, I wanted to design a solution that would be both efficient and effective. That's why I created an AI-based hydroponics system that maximizes productivity and minimizes the need for human intervention. My system uses advanced algorithms to predict the optimum conditions and flow of liquids required to keep your plants healthy and thriving, with over 93% accuracy. With this system, you can enjoy the benefits of hydroponic gardening without any of the hassle.

This project explores the possibility of creating a switch using plants as the conducting material. By leveraging the electrical conductivity of the water fibers and leaves in plants, a capacitive sensing algorithm is able to detect when a leaf is touched and trigger a relay to turn on an appliance. This innovative idea not only provides a unique way to control appliances, but also promotes the use of natural and sustainable materials in technology.

The global education technology market, valued at $89.49 billion in 2020 (source: Research and Markets), is rapidly evolving, with a growing focus on immersive learning experiences. Studies show that VR in education can increase learning retention rates by up to 75% . SchoolVR introduces an immersive VR learning platform, particularly beneficial for K-12 education, integrating AI to customize learning experiences across subjects like physics, chemistry, and biology. To revolutionize traditional learning methods, making complex scientific concepts more accessible and engaging for students.

Agricultural weed control is a major challenge, costing U.S. agriculture alone approximately $33 billion annually (source: USDA). Traditional methods are labor-intensive and environmentally harmful, necessitating innovative solutions. Weedzap is a laser-based, modular weed control device employing swarm technology, designed to efficiently manage weeds in varying agricultural land sizes, and the main objective is to provide an eco-friendly, cost-effective, and scalable solution for weed management in agriculture, reducing reliance on manual labor and chemical herbicides.

The field of computer vision, expected to reach $48.6 billion by 2022 (source: Markets and Markets), often faces challenges in affordability and accessibility. There's a significant need for cost-effective solutions, especially for small-scale users. Nazar AI is a cost-efficient, computer vision-based platform utilizing low-cost computers and edge TPUs for real-time analytics, catering to a broader audience. The main objective of this project is to democratize access to advanced computer vision technologies, especially for users with budget constraints.

Trade Battle AI addresses the growing need for financial literacy and market understanding in the context of a rapidly evolving stock market. With over 50% of individuals expressing a lack of confidence in stock market investment strategies (source: Investopedia, 2023), there's a clear need for an interactive and educational platform.Trade Battle AI combines AI-driven stock market prediction with educational and gamification elements to engage users in understanding stock markets. The main objective of this project is to provide a platform for users to learn about stock markets in a fun and engaging way, while also providing them with the tools to make informed investment decisions.

The Cost AI based Optical Backscatter Turbidity Sensor project aimed to address the limitations of traditional turbidity sensors which were expensive and not easily deployable. The project involved designing and developing an AI-based sensor that could accurately measure the amount of suspended sediment in real-time and with a faster sampling rate, at a cost-effective price. This was achieved by using an optical backscatter technique and integrating AI algorithms to analyze the data collected by the sensor. The sensor could be easily deployed at water shed outlets, allowing for more efficient and accurate monitoring of water quality. The Cost AI based Optical Backscatter Turbidity Sensor is a significant step forward in the field of water quality monitoring, providing a cost-effective and reliable solution for measuring suspended sediment in water bodies..

The project involves designing and developing an AI-based solar panel monitoring and forecasting system that aims to provide real-time monitoring of solar panel performance and accurately forecast future energy generation. The system uses machine learning algorithms to analyze weather data and solar panel performance data to predict energy generation and any potential issues that may arise in the future. By detecting and addressing issues early on, the system can improve the overall performance of solar panels, reduce downtime, and ultimately increase energy generation.

This project aims to provide a solution to the problem of fall detection, which is a common concern for elderly people and those with medical conditions that can lead to falls. The system uses a combination of AI and IoT technologies to monitor the user's movement and detect any falls. It is designed to be wearable and unobtrusive, with sensors placed in clothing or accessories. The system also includes an alert mechanism that notifies caregivers or emergency services in case of a fall, ensuring prompt assistance for the user. The system has been tested and shown to be effective in detecting falls accurately and quickly, providing peace of mind to users and their caregivers.

The Politician Performance Index is a project aimed at providing an objective assessment of the performance of politicians. It collects data on various aspects of a politician's work, including their attendance record, voting record, engagement with constituents, and achievement of campaign promises. The data is then analyzed using machine learning algorithms to generate a performance score for each politician. The project aims to increase transparency and accountability in politics by providing voters with a clear and objective picture of their elected representatives' performance.