Developing a device that can monitor the road and the driver respectively, Key features are lane detection and tracking, traffic estimation, collision warning, SOS messages, Drowsiness detection and activity detection { Smoking / Drinking }.
Developed a change Robot using face-recognition and OpenCV which recognizes the person and using pyttsx3 library it greets the person with a handshake and checks the temperature.
Developed a ROCK PAPER SCISSOR GAME using cvzone and OpenCV
Developed a gesture-based model for controlling the mouse virtually using media-pipe and OpenCV
Developing a rover that keeps an eye on the crops, detects unhealthy crops, alerts the farmer to potential solutions, connects them to the closest test facilities, and periodically checks the crop growth for anomalies.
Published in IPR - Intellectual Property India, 2023
Filed a patent on AI FARM ROVER - Published - Got Commercialised [ HEXAIND TECHNOLOGIES AND SERVICES LLP ]
Published in IPR - Intellectual Property India, 2023
Filed a patent on IOT BASED INTELLIGENT VEHICLE SAFETY SYSTEM - Published
Published in IPR - Intellectual Property India, 2023
Filed a patent on IOT-SENSOR-BASED PLANT DISEASE DIAGNOSIS - Published
Published in IPR - Intellectual Property India, 2023
Filed a patent on PREDICTION OF BIRDS AND ANALYSIS OF ENDANGERED BIRD SPECIES - Published
Published in IPR - Intellectual Property India, 2023
Filed a patent on DRIVER ASSISTANT SYSTEM - Published
Published in IEEE 14th International conference on computer communication and informatics (ICCCI), 2024
The research paper focuses on the development of an interactive robot system that utilizes IoT technology and classification algorithms for various functionalities such as attendance marking, face recognition, and temperature monitoring
Published:
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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Built a greeting robot by combining OpenCV and facial recognition tools, putting SVMs to use, and adding IOT devices like temperature sensors, servo motors, Raspberry Pis, and Pi cameras.
Deciding the image criteria, photos are gathered, labeled with the help of the LabelImg tool, and then stored on Amazon S3. Product data is gathered and stored in MongoDB concurrently.
The project aimed to enhance runway safety by detecting Foreign Object Debris (FOD) on airstrips, which can pose significant risks to aircraft during takeoff and landing. The FOD detection vehicle was designed to autonomously patrol the runway, capturing high-resolution images and processing them in real-time to identify potential hazards.