“When you want something, all the universe conspires in helping you to achieve it”– Paulo Coelho.

Be it a dream or a wish, when you are determined to pursue what the mind really wants, SRM University-AP helps you reach that goal. Ms Pragya Gupta and Ms Swikriti Khadke joined SRM AP with vibrant dreams, and in their third year, they have attained the prestigious Mitacs Globalink Research Internship. The students from the Department of Computer Science and Engineering will spend three months in Canadian universities as a part of this fully-funded research internship. Ms Swikriti will intern at Université du Québec en Outaouais – Gatineau on the research project titled “Systematic PV farm power losses calculation and modelling using computational intelligence techniques”. Ms Pragya will be going to Athabasca University – Edmonton as a research intern to work on the project titled “Blockchains for Data Storage and Mining in Learning Analytics”.

About Mitacs Globalink Research Internship

Mitacs Globalink Research Internship is a highly competitive programme that pairs top-ranked international students having specific research expertise from 15 countries worldwide with faculty at top Canadian academic institutions. This is a twelve (12) week research project of mutual interest between May and October 2022. The Canadian host faculty project leader makes selections by verifying the student’s background and skills in the research area and the unique contribution they will be made to the research during the stay. As a fully-funded programme, Mitacs and AICTE will administer the grant. Students can choose from about 14k+ projects in disciplines like Engineering, Life Sciences, Mathematics, Natural Sciences, Social Sciences, and the Humanities.

Mitacs will be responsible for providing the following to the students:

1. An airfare stipend of Can$1,500;
2. A stipend of Can$175 to contribute to the cost of transportation from the Canadian airport to accommodation unless otherwise arranged by your host institution
3. A stipend of Can$200 per week for living expenses
4. Ensure that students receive Canadian medical insurance.
5. A daily allowance of Can$45 for housing for the duration of the research internship.
6. A stipend of Can$300 for any student fees charged by the Canadian host institution
7. Reimbursement of immigration permit application fees (as required to participate in the research internship — up to a maximum of Can$240)
8. A stipend of Can$500 for any COVID-19-related expenses (e.g., COVID test, quarantine, expenses incurred during isolation, etc.)

The journey, in Pragya and Swikriti’s words:

The journey from applying for MITACS to getting selected as one of the GRI interns in one of the top-ranked universities in Canada was no less than a dream come true. The registration process included filling out an application form which was the most important step and a complicated one. This was also an elimination stage for many because writing down all our details in a limited number of words was quite difficult and challenging. After submitting the application form, the details about the Matching round were intimated in November. We received emails for the interview round from the professor himself. It was a technical interview that comprised of questions regarding our work experience, knowledge about the technology we will be contributing to the project during the internship, and personal details. The interview lasted for 30-45 mins, after which the professor assigned us some tasks to assess our knowledge regarding the topic. After completing and submitting the task, around Mid December, we received a congratulatory mail regarding our selection for MITACS GRI 2022, which will commence from May 2022 and continue for the next three months.

The Globalink Graduate Fellowship offers former Globalink research interns:

■ Direct financial support from Mitacs
■ Recognition as Globalink alumni
■ The opportunity to work with Canada’s research supervisors during your graduate studies
■ Additional exposure to the Canadian research and innovation landscape and increased Canadian experience.

A note of gratitude

“We would like to thank SRM University-AP, Andhra Pradesh, for helping us build our skills and supporting us throughout the process. Our university management has always been kind and helpful to its students to explore new opportunities and create new relations. We would like to extend our gratitude to our mentors, Dr Goutam Kumar Dalapati and Dr Anil K Suresh, for their continuous support, guidance, and motivation. Last but not least, our parents have been our support system throughout our journey”.

The healthcare system across the globe has been under colossal pressure since the emergence of novel coronavirus pandemic. The pandemic has also unveiled some of the greatest gaps in the existing healthcare systems. The research paper authored by Dr Ashok Kumar Pradhan and his PhD student E Bhaskara Santhosh, Department of Computer Science and Engineering, proposing a blockchain-based pandemic detection model was recognised by WHO and the paper was listed in COVID-19 Global literature on coronavirus disease. The paper titled “iBlock: An Intelligent Decentralised Blockchain-based Pandemic Detection and Assisting System” was published in collaboration with Saraju Mohanty, University of North Texas and Dr Venkata Ramana Badarla, Associate Professor, IIT Tirupati. The authors have expressed their deepest gratitude to Science and Engineering Research Board (SERB) for Grant number TAR/2019/000286 and SRM University-AP for supporting this work.

Abstract of the Research

The recent COVID-19 outbreak highlighted the requirement for a more sophisticated healthcare system and real-time data analytics in the pandemic mitigation process. Moreover, real-time data plays a crucial role in detection and alerting process. Combining smart healthcare systems with accurate real-time information about medical service availability, vaccination, and how the pandemic is spreading can directly affect the quality of life and economy. The existing architecture models become inadequate in handling the pandemic mitigation process in a real-time dataset. This is because, the present models are server-centric and controlled by a single party, hence to manage confidentiality, integrity, and availability (CIA) of dataset is a challenging task. Therefore, a decentralised user-centric model is essential, where the CIA of user data can be assured. In this paper, we have suggested a decentralized blockchain-based pandemic detection and assistance system named as (iBlock) that uses robust technologies like hybrid computing and IPFS to support system functionality. Moreover, a pseudo-anonymous personal identity is suggested using H-PCS and cryptography for anonymous data sharing. The distributed data management module guarantees data CIA, security, and privacy using cryptography mechanisms. Furthermore, it delivers useful intelligent information in the form of suggestions and alerts to assist the users. Finally, the iBlock reduces stress on healthcare infrastructure and workers by providing accurate predictions and early warnings using AI/ML technology.

Contributions of the Research

i) Proposes a novel architecture model for pandemic detection and alertness using a blockchain called as “iBlock”. It supports sharing of real-time data utilization.
ii) The proposed system introduces suitable privacy and security mechanisms to cover system-level data privacy and security.
iii) It also suggests a logical combination of blockchain and AI/ML on hybrid computing to support global level requirements during pandemic mitigation and alerting the systems.

Social Implications

The proposed system helps in the early detection of Covid-19 and encourages people to use their health data anonymously in pandemic detection and mitigation process. Moreover, iBlock maintains all crucial data on blockchain for future sustainable healthcare solutions. The majority of pandemic detection and alerting systems are limited to prediction, however iBlock further simplifies the area-labelling to cover area wise mitigation mechanisms. The classification of areas helps the government and healthcare organizations to plan sustainable preventive measures in a real-time scenario. It also helps in prediction of new cases and death rates with the aid of a dedicated AI/ML detection engine module. To motivate the people to share legitimate data, the proposed model even suggests a reward mechanism to influence the participants.

The research investigates the advanced possibilities in smart healthcare architecture to bring down the time and effort for pandemic mitigation activities. Read to know more.

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