The team of four Marwadi University (MU) students—Komal Bhagchandani and Disha Sanghavi of B.Sc. (IT), Neha Suva from MCA and Ananya S from M.Sc. (Cyber Security), who were declared as the runners up in the All India Hackathon organized by Indian Institute of Information Technology (IIIT) Allahabad have developed an app called FirstTalk. Their app bridges the communication gap between hearing and speech impaired individuals using Machine Learning (ML) and Android Studio technologies.The team was mentored by the Faculty of Computer Applications (FoCA) under the mentorship of Dr.Raviraj Vaghela.
More than 52 teams participated from various educational institutions and 22 teams qualified in the first round and just eight in the second round.
“First Talk was developed by our Faculty students within 3 days, solving real world challenges using technologies that were unimaginable a few years ago. At MU, we encourage the integration of latest tech developments into our learning modules, so our students keep up with the changing times,” says MU FoCA Dean Dr.Sridaran Rajagopal. He added in all, competitive participation in the Information and Communication Technology (ICT) domain which is one of the focus study areas at MU, with students being able to choose from a pool of software programming, electronics hardware, network and security, communication systems and data science — further helps refine a students’ career opportunities in Software Development, Machine Learning, Android/iOS Application, Robotics, Sensors & IoT, Data Analytics, Embedded Software, Wireless Technologies, Network & Security and VLSI Chip Design.
New-age technologies like Machine Learning and Android Studio are not only presenting immense learning and career opportunities for students but carry potent solutions for a better quality of human life. Useful across sectors such as telecommunications, medicine, BFSI (banking, financial services and insurance) and energy, ML enables a computer to learn on its own using artificial intelligence and mathematical data models.