Deeraj C’s research while affiliated with Alpha College of Engineering Bangalore and other places

Code Verse features a revolutionary online code editor that aims to revolutionize your coding experience by providing a seamless interface between different programming languages. This innovative platform supports developers working with languages such as JavaScript, Python, Java, php etc. facilitating a versatile programming environment that adapts to the diverse needs of users. Code verse's user-friendly interface removes the traditional barriers associated with language-specific editors and allows developers to seamlessly switch between languages within the same platform.

This adaptive system offers a comprehensive solution to enhance vehicle performance and safety in diverse driving conditions, providing drivers with actionable insights and real-time adjustments to optimize their driving experience. By leveraging cutting-edge technologies, including adaptive lighting and accelerometer-based control, the system empowers drivers to navigate challenging terrain with confidence and precision, ultimately improving overall vehicle safety and efficiency

QuantumClean SparkSwift is an innovative IoT-based project focuses in the development automatic vaccum cleaner. Leveraging the IoT technology, the system allows users to remotely control and monitor the vaccum cleaner through a mobile application. The device employs sensors for obstacle detection and obstacle avoidance and mapping, ensuring efficient cleaning. The integration of smart features such as obstacle detection, obstacle avoidance, mapping, Bluetooth control, voice command controlling enhances user convenience, making it a practical and innovative solution for automated home cleaning

This project customs innovative machine learnings methods to forecast brain strokes to MRI data. Leveraging high- resolution MRI scans, the model seeks to detect subtle changes indicative of stroke risk. By analyzing features like lesion location and intensity variations, it aims to capture the complex factors contributing to stroke occurrence. Additionally, the model aims to classify stroke subtypes, such as ischemic and hemorrhagic strokes, using multi-modal MRI data for personalized treatment strategies. Validation will be performed on diverse patient datasets, assessing sensitivity, specificity, and AUC- ROC. The outcome targets the advancements of a a therapeutically useful instrument for earley stroke prediction, enabling proactive intervention and improved patient outcomes. By integrating MRI and machine learning, this project aims to advance stroke diagnosis and treatment, reducing the burden on healthcare systems globally

Waste segregation is a crucial step in Waste Management System to promote recycling, reduce environmental pollution, and conserve resources. In recent years, the integration in Internet of Things. Technology has emerged as a promising approach to enhance waste segregation processes. This paper presents a comprehensive overview of waste segregation using (IoT). Smart bins with many sensors, including moisture, infrared, and ultrasonic ones, connectivity elements like power supply and battery, make up the Internet of Things-based trash segregation system. Moreover, the system utilizes actuators to automate processes like lid opening/closing and waste compaction, improving efficiency and hygiene.