Moksh Dinesh Nihalani, a Class 9 student from Dhirubhai Ambani International School, Mumbai, has won the Google India Code to Learn 2021 contest for his PRISM – smart communication project, an MIT app for people with speech and hearing disabilities. Explaining about the app, Moksh said, “Around 72 per cent of parents of children with hearing disabilities from kindergarten to Class 12 do not know sign language. About 55 per cent of them use sign language. Project Prism is an app which allows people with hearing loss to communicate easily with others and lets those without hearing disability communicate with friends and acquaintances with the disability”.

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

Some of the finalists of the competitions included:

Shayaan C Doshi, Class 6 from St Gregorios High School, Mumbai, developed an MIT app called “Secure Child’. Explaining about the project, Shayaan said, “This app was made with the sole purpose to teach children about safety. It has images and videos, creating awareness about different types of abuses, like physical, sexual, or emotional, that occur in their familiar or nearby surroundings. The app allows them to report to their parents or to the childcare centre if needed. The app also allows the user to take a photo of the person under abuse, share the contact and the location to seek quick help from the unsafe situation”.

Veer Mehta of Class 9 from Dhirubhai Ambani International School 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 tier II and III cities and 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; it not just saves the cost but also alerts at an early stage of any serious dental health problems. With smart devices being widely used in rural areas, this app would also be easily accessible”.

Yuthika Singh, a Class 10 student of JBCN International School, Mumbai, developed a “Self-chat analyses” app using Google Cloud AutoML. Explaining about the app, Yuthika said, “Around 90 per cent of teenagers aged 13-17 years use social media to connect with others and showcase their feelings to the world. Sometimes, this takes a toll on teenagers’ mental health, polarising their emotions. If these issues are left unaddressed, social media stress may cause severe emotional imbalance, from extreme happiness to extreme sadness and anxiety. This ML-based app can analyse a document to isolate the emotional categories based on the text; it can be used to understand a teenager’s emotions by capturing keywords in their social media chats, for timely help”.

Dhyey Shah, a Class 9 student from Indus International School, Pune, developed an “Identifying plant diseases using ML” app using Google Cloud AutoML. Explaining the app, Dhyey said, “Plant diseases are a critical concern worldwide, including India. They lead to the reduction of crop yield, eating away the farmer’s income. Early identification of these plant diseases is tough in rural areas, which leads to the loss of the entire crop. Due to a lack of awareness and knowledge, farmers use excessive pesticides and fertilisers, affecting the quality of the soil of the farmed land. This app will help farmers identify plant diseases based on the leaf structure”.

OMOTEC’s Robotics, ML and AI-led mentoring programmes encourage students to learn, analyse and solve real-life problems with new-age and meaningful solutions and products. The main goal is to equip students with the wherewithal to work in fields poised for growth in the future. OMOTEC had 24 participants compete at the national level, of whom five had qualified as finalists.

OMOTEC co-founder Shekhar Jain says, “OMOTEC aspires to be the MIT of India with our insightful techniques, rooted in robotics and coding, of experiential learning in mathematics, science and technology.”

The Google Code to Learn aims to strengthen the foundation for computer science among pre-university students by providing a space to code and apply computer programming for their entries.

The participating students in classes 5-10 get to 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. These are block-based coding tools that do not require prior knowledge of programming languages.

Students in classes 9-12 may use Google Cloud AutoML, which familiarises them with the concepts of machine learning (uses data to teach computers to mimic human behaviour) and artificial intelligence in an engaging manner.