Researchers at the Indian Institute of Technology, Mandi have developed LakshmanRekha, an Artificial Intelligence – biometric driven Home Quarantine Management Application (HQMA) for COVID patients. The application uses a combination of biometric verification, geofencing, and artificial intelligence, to continuously monitor and accurately detect the identity of a home quarantined person. In addition to the quarantine management, this application can also serve as an unbreachable mobile phone platform for normal (non-COVID) mobile users, situations like under curfew, or any national emergency, for identifying the violators or lawbreakers.
In existing quarantine management mobile applications, individuals under self-isolation are forced to share their instantaneous position routinely via geofencing technology or they are required to upload a face selfie every hour or ten times a day. But these geofencing applications fail to ensure the user identity throughout the time because individuals can leave cell phones in isolation zones and move in/ out, leading to disobey the self-isolation rules. Similarly, the idea of uploading a face selfie every hour cannot ensure the patient’s stay in a geofenced area as they can also try to fool the system by using a photo containing its registered face.
To mitigate these risks, LakshmanRekha matches the quarantine location of the individual with the location from where they have uploaded the biometric data. Along with this, using AI, the application continually computes an authentication score that can measure how certain it is, that the quarantined user is also the one using the mobile. If the application detects any action indicating that the user identity has been changed, it will directly notify the authorities for necessary action.
The results of the research work that was funded by the Department of Science and Technology, have recently been published in the IEEE Consumer Electronics Magazine. The paper has been authored by the lead scientist on this research Dr Aditya Nigam, Assistant Professor, School of Computing & Electrical Engineering, IIT Mandi, and co-investigators on the study were Dr Arnav Bhavsar, Associate Professors, School of Computing & Electrical Engineering, along with research scholars, Daksh Thapar and Piyush Goyal of IIT Mandi, with Dr Gaurav Jaiswal from IIT Delhi and Dr Kamlesh Tiwari and Rohit Bhardwaj of BITS Pilani, Rajasthan.
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