IN - Health Informatics (HI) Center of Research and Innovation.

Based on the Intelligent Platform (IN) System Platform by : Mr. Prem Pungaliya, Arsha Consultants LLC (USA)

IN-HI Platform Vision

Basic Intent: Individual level management of risk of infectious diseases.:

Every ordinary person is empowered to control, contribute and/or demand timely information to enhance health-related situational awareness and actionable assessment. This IN system defines an affordable AI-enabled distributed sensing-supercomputing system to real and practical level of our daily ordinary lives.

Early detection, assessment and warning of (bio) threats – whether nature-made or man-made - to human life. Application of advanced information technologies, procedures, timely environmental monitoring, and citizen participation to promote active awareness of healthy well being and to save lives!! The timeline of from the time of incubation of a pathogen to detection and action is unacceptably long and costly in terms of human suffering as well as impact in economic terms. The IN intends to be revolutionary in terms of early, timely detection and warning as well as enforcement of necessary actions to make a difference.

A programmable Neighborhood is intended. Infectious diseases’ related problems are the targets based on a set of innovative “systems technologies” to enable intelligent, model-based Personalized

Epidemiology: The vision based on 5G-enabled distributed sensing/deep learning. The capturing of the “person-centric cyber-physical context” is the focus of our proposed model-based data collection.

The proposal will also address integration and information fusion challenges at different levels: Environmental, Social as well as Computational. Individual level relevant assessment of risks of communicable diseases can be done by applying the person-centric context to operationalization of the larger population level models. A wide variety of “Macro-level” epidemiological models for infectious diseases are available from many reputable institutions world-wide. Operationalization of these models has been a difficult challenge in terms of their performance and the ability to predict.

The Technology-enabled Opportunity:

The IN can continuously learn and update “Person’s Susceptibility and Sensitivity” 24/7 to make actionable-knowledge available before, during or after any disease outbreaks. It is feasible to realize a private and secure programmable “Cloud On The Ground” System in a typical neighborhood with affordable sensing and computing devices. The smartphone, wearable devices as well as devices embeddable in a person’s environment allow capturing of highly relevant to person’s awareness of his/her bio-medical conditions.

An active, dynamic multi-mode surveying tool will be developed to allow collection of human-based sensing data. A variety of of affordable devices , e.g. Foldscope, have become available to capture environmental data a person is embedded in. Crowdsourcing of such contexts, e.g. vectors’ breeding and feeding

Emerging nano-scale informatics is expected to further revolutionize healthcare in general and medical field in particular.

Strategy:

A practical “crowd-sourced” Intelligent Collection System will allow knowledge to be individualized or localized. The operationalization of the wide variety of emerging digital epidemiological models will improve our ability to manage and control disease detection and spread processes

It is envisioned that the system will be deployed step-by-step, neighborhood by neighborhood to be adopted by a wide range of users to cooperate and collaborate to achieve quantitative, timely, shared awareness of susceptibility and spread of infectious diseases.

Conclusion:

Innovative approaches to “Crowdsourced, Intelligent Model-Based Data Collection” is needed. The epidemiological models will benefit greatly from timely, relevant quantitative data we planned to collect, and the distributed sensing-supercomputing resources planned to be deployed in neighborhoods, i.e.. “cloud on the ground” on the edge of the Internet and near the users. Such epidemiological models continue to be developed by leading researchers around the world. They demand timely data and supercomputing resources. .

Contact Information:

Prof. Kailas Patil,
Email : kailas [DOT] patil [AT] vupune [DOT] ac [DOT] in

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