Class 9 student’s app wins Google Code to Learn 2021

Moksh Dinesh Nihalani, a class 9 student at Dhirubhai Ambani International School, Mumbai, has won the Google India Code to Learn 2021 competition for his smart communication project PRISM, an MIT app for people with speech disabilities. speech and hearing. Explaining about the app, Moksh said, “Around 72% of parents of hearing impaired children from kindergarten to grade 12 do not know sign language. About 55% of them use sign language. Project Prism is an application that allows people with hearing loss to easily communicate with others and allows those who do not have a hearing impairment to communicate with friends and acquaintances with a disability”.

Besides Moksh, many OMOTEC students were finalists and had developed apps that can be used for real-life cases.

Some of the competition finalists included:

Shayaan C Doshi, class 6 from St Gregorios High School, Mumbai, has developed an MIT application called “Secure Child”. Explaining the project, Shayaan said, “This app was made for the sole purpose of teaching children about safety. It contains images and videos, raising awareness of different types of abuse, such as physical, sexual or emotional, that occur in their familiar or close environment. The application allows them to introduce themselves to their parents or to the crèche if necessary. The app also allows the user to take a photo of the abused person, share the contact and location to seek quick help of the dangerous situation”.

Veer Mehta from Class 9 of Dhirubhai Ambani International School has developed a project “Dental Hygiene and Cavity Identifier using Google Cloud AutoML”. Explaining the project, Veer said, “Majority of Indians are either ignorant or unable to afford dental care, especially in cities and Tier II and III rural areas. Dental care is also expensive for many low-income families. This app identifies a host of dental issues with just a photo of the user’s mouth; this not only saves cost but also alerts you to any serious dental health issues at an early stage. Since smart devices are widely used in rural areas, this app would also be easily accessible.”

Yuthika Singh, a class 10 student at JBCN International School, Mumbai, has developed an “Auto-Chat Analytics” application using Google Cloud AutoML. Explaining the app, Yuthika said, “About 90% of teens aged 13-17 use social media to connect with others and show their feelings to the world. their emotions. If these issues are not addressed, social media stress can cause severe emotional imbalance, ranging from extreme happiness to extreme sadness and anxiety. This ML-based application can analyze a document to isolate categories emotions based on the text; it can be used to understand a teenager’s emotions by capturing key words in their social media discussions, for timely help”.

Dhyey Shah, a class 9 student from Indus International School, Pune, has developed an application “Plant Disease Identification Using ML” using Google Cloud AutoML. Explaining the app, Dhyey said, “Plant diseases are a major concern all over the world, including in India. They lead to reduction in crop yield, eating away at the farmer’s income. Early identification of these plant diseases is difficult in rural areas, resulting in the loss of the entire crop. Due to a lack of awareness and knowledge, farmers use excessive pesticides and fertilizers, affecting the soil quality of cultivated land. This app will help farmers identify plant diseases based on leaf structure.”

OMOTEC’s robotics, ML, and AI-led mentorship programs encourage students to learn, analyze, and solve real-world problems with new and meaningful solutions and products. The primary goal is to empower students to work in fields poised for growth in the future. OMOTEC had 24 entrants competing nationally, five of whom qualified as finalists.

OMOTEC Co-Founder Shekhar Jain said, “OMOTEC aspires to be India’s MIT with our insightful, robotics and coding-based, experiential learning techniques in math, science and technology.”

The Google Code to Learn aims to strengthen the basics of computer science in pre-college students by providing a space to code and apply computer programming for their entries.

Participating students in grades 5-10 can create projects using Scratch (to create stories, games, and animations), a stepping stone to the world of computer programming, or MIT’s open-source tool for creating Android apps . They are block-based coding tools that do not require any prior knowledge of programming languages.

Students in grades 9 through 12 can use Google Cloud AutoML, which introduces them to the concepts of machine learning (uses data to teach computers to mimic human behavior) and artificial intelligence in an engaging way.

Lance B. Holton