Just imagine a smartphone app that can ‘listen’ to distress calls and automatically trigger an alert to your home or the police. This is what Rakshak, a new Android app developed by innovators from Delhi-based Bharti Vidyapeeth College of Engineering, does. It is designed to detect speech patterns via a phone’s microphone and generate an SOS. Audio snippets with speech commands requesting help or saying “stop” in distressed tones can be detected by the app and a message is automatically sent to the emergency contact specified by the user, along with the location of the user.
The innovation won the first prize in a national contest organised in India by the US-based Marconi Society under its Celestini Program. The winning team of Piyush Agrawal, Subham Banga, Aniket Sharma and Ujjwal Upadhyay presented their work at a function held at Indian Institute of Technology, Delhi on Monday.
For developing the app, the team started with publicly available speech command datasets, and added speech commands specific to the scenario of women’s safety. They also collected additional speech data through crowd-sourcing. This enabled them to detect emotion, background noise, and Indian accents in the audio with improved precision. At present, the app can handle two languages – Hindi and English.
The app can ‘listen’ when it is on and track keywords like ‘help’ or ‘bachao‘. It uses the machine learning algorithm to judge emotional state from sound, pitch, etc. and triggers an automatic alarm. There is a 30-second delay in case the owner wants to cancel a false alarm. The developers claim that the app can differentiate a real cry for help from a casual conversation with similar words.
The team winning the second prize – also from Bharti Vidyapeeth College of Engineering – developed an app for air quality measurement. Its members – Harshita Diddee, Shivam Grover, Shivani Jindal, and Divyanshu Sharma – have developed an app called VisionAir which uses photos of the horizon to estimate air quality. It builds on the work done by last year’s prize winners, which showed that machine learning models can be built to estimate air quality by extracting image features like haziness and combining them with meteorological and past air quality data.
“The program is a unique and impactful way to help us create the next generation of technical innovators,” said Professor Brejesh Lall, head of Bharti School of Telecom Technology and Management and Celestini Program partner at IIT-Delhi. “Students become deeply engaged when they are defining important problems that technology can solve and creating proof-of-concept applications that will make a difference in the world.” The winning team gets a cash prize of US$1,500 and the second-place team receives US$500.
The author, Dinesh Sharma, is Managing Editor at India Science Wire.