Zero Knowledge Proofs in Healthcare Data Sharing

Srinivasan Sundararajan

Recap of Healthcare Data Sharing

In my previous article (https://www.gavstech.com/healthcare-data-sharing/), I had elaborated on the challenges of Patient Master Data Management, Patient 360, and associated Patient Data Sharing. I had also outlined how our Rhodium framework is positioned to address the challenges of Patient Data Management and data sharing using a combination of multi-modal databases and Blockchain.

In this context, I have highlighted our maturity levels and the journey of Patient Data Sharing as follows:

  • Single Hospital
  • Between Hospitals part of HIE (Health Information Exchange)
  • Between Hospitals and Patients
  • Between Hospitals, Patients, and Other External Stakeholders

In each of the stages of the journey, I have highlighted various use cases. For example, in the third level of health data sharing between Hospitals and Patients, the use cases of consent management involving patients as well as monetization of personal data by patients themselves are mentioned.

In the fourth level of the journey, you must’ve read about the use case “Zero Knowledge Proofs”. In this article, I would be elaborating on:

  • What is Zero Knowledge Proof (ZKP)?
  • What is its role and importance in Healthcare Data Sharing?
  • How Blockchain Powered GAVS Rhodium Platform helps address the needs of ZKP?

Introduction to Zero Knowledge Proof

As the name suggests, Zero Knowledge Proof is about proving something without revealing the data behind that proof. Each transaction has a ‘verifier’ and a ‘prover’. In a transaction using ZKPs, the prover attempts to prove something to the verifier without revealing any other details to the verifier.

Zero Knowledge Proofs in Healthcare 

In today’s healthcare industry, a lot of time-consuming due diligence is done based on a lack of trust.

  • Insurance companies are always wary of fraudulent claims (which is anyhow a major issue), hence a lot of documentation and details are obtained and analyzed.
  • Hospitals, at the time of patient admission, need to know more about the patient, their insurance status, payment options, etc., hence they do detailed checks.
  • Pharmacists may have to verify that the Patient is indeed advised to take the medicines and give the same to the patients.
  • Patients most times also want to make sure that the diagnosis and treatment given to them are indeed proper and no wrong diagnosis is done.
  • Patients also want to ensure that doctors have legitimate licenses with no history of malpractice or any other wrongdoing.

In a healthcare scenario, either of the parties, i.e. patient, hospital, pharmacy, insurance companies, can take on the role of a verifier, and typically patients and sometimes hospitals are the provers.

While the ZKP can be applied to any of the transactions involving the above parties, currently the research in the industry is mostly focused on patient privacy rights and ZKP initiatives target more on how much or less of information a patient (prover) can share to a verifier before getting the required service based on the assertion of that proof.

Blockchain & Zero Knowledge Proof

While I am not getting into the fundamentals of Blockchain, but the readers should understand that one of the fundamental backbones of Blockchain is trust within the context of pseudo anonymity. In other words, some of the earlier uses of Blockchain, like cryptocurrency, aim to promote trust between unknown individuals without revealing any of their personal identities, yet allowing participation in a transaction.

Some of the characteristics of the Blockchain transaction that makes it conducive for Zero Knowledge Proofs are as follows:

  • Each transaction is initiated in the form of a smart contract.
  • Smart contract instance (i.e. the particular invocation of that smart contract) has an owner i.e. the public key of the account holder who creates the same, for example, a patient’s medical record can be created and owned by the patient themselves.
  • The other party can trust that transaction as long the other party knows the public key of the initiator.
  • Some of the important aspects of an approval life cycle like validation, approval, rejection, can be delegated to other stakeholders by delegating that task to the respective public key of that stakeholder.
  • For example, if a doctor needs to approve a medical condition of a patient, the same can be delegated to the doctor and only that particular doctor can approve it.
  • The anonymity of a person can be maintained, as everyone will see only the public key and other details can be hidden.
  • Some of the approval documents can be transferred using off-chain means (outside of the blockchain), such that participants of the blockchain will only see the proof of a claim but not the details behind it.
  • Further extending the data transfer with encryption of the sender’s private/public keys can lead to more advanced use cases.

Role of Blockchain Consortium

While Zero Knowledge Proofs can be implemented in any Blockchain platform including totally uncontrolled public blockchain platforms, their usage is best realized in private Blockchain consortiums. Here the identity of all participants is known, and each participant trusts the other, but the due diligence that is needed with the actual submission of proof is avoided.

Organizations that are part of similar domains and business processes form a Blockchain Network to get business benefits of their own processes. Such a Controlled Network among the known and identified organizations is known as a Consortium Blockchain.

Illustrated view of a Consortium Blockchain Involving Multiple Other Organizations, whose access rights differ. Each member controls their own access to Blockchain Network with Cryptographic Keys.

Members typically interact with the Blockchain Network by deploying Smart Contracts (i.e. Creating) as well as accessing the existing contracts.

Current Industry Research on Zero Knowledge Proof

Zero Knowledge Proof is a new but powerful concept in building trust-based networks. While basic Blockchain platform can help to bring the concept in a trust-based manner, a lot of research is being done to come up with a truly algorithmic zero knowledge proof.

A zk-SNARK (“zero-knowledge succinct non-interactive argument of knowledge”) utilizes a concept known as a “zero-knowledge proof”. Developers have already started integrating zk-SNARKs into Ethereum Blockchain platform. Zether, which was built by a group of academics and financial technology researchers including Dan Boneh from Stanford University, uses zero-knowledge proofs.

ZKP In GAVS Rhodium

As mentioned in my previous article about Patient Data Sharing, Rhodium is a futuristic framework that aims to take the Patient Data Sharing as a journey across multiple stages, and at the advanced maturity levels Zero Knowledge Proofs definitely find a place. Healthcare organizations can start experimenting and innovating on this front.

Rhodium Patient Data Sharing Journey

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Healthcare Industry today is affected by fraud and lack of trust on one side, and on the other side growing privacy concerns of the patient. In this context, the introduction of a Zero Knowledge Proofs as part of healthcare transactions will help the industry to optimize itself and move towards seamless operations.

About the Author –

Srini is the Technology Advisor for GAVS. He is currently focused on Data Management Solutions for new-age enterprises using the combination of Multi Modal databases, Blockchain, and Data Mining. The solutions aim at data sharing within enterprises as well as with external stakeholders.

Design-led Organization: Creative Thinking as a Practice!

Gogul R G

This is the first article in the series of ‘Design-led organization’ writing about creative thinking as a practice in GAVS. It is the first step for the readers to explore the world of design and creativity. So, let’s get started!

First let’s see what is design thinking is all about

There is a common misconception that design thinking is new. But when you look back, people have applied a human-centric creative process to build meaningful and effective solutions. Design has been practiced for ages to build monuments, bridges, automobiles, subway systems, etc. Design is not only limited to aesthetics, it is more of a mindset to think of a solution. Design thinking is a mindset to iteratively think about a complex problem and come up with a viable solution

Thinking outside of the box can provide an innovative solution to a sticky problem. However, thinking outside of the box can be a real challenge as we naturally develop patterns of thinking that are based on the repetitive activities and commonly accessed knowledge surround ourselves. It takes something to detach away from a situation where we’re too closely involved to be able to find better possibilities.

To illustrate how a fresh way of thinking can create unexpectedly good solutions, let’s look at a famous incident. Some years ago, an incident occurred where a truck driver had tried to pass under a low bridge. But, he failed, and the truck became firmly lodged under the bridge.

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The driver was unable to continue driving through or reverse out. The struck truck caused massive traffic problems, which resulted in emergency personnel, engineers, firefighters, and truck drivers gathering to negotiate various solutions to dislodge the truck.

Emergency workers were debating whether to dismantle parts of the truck or chip away at parts of the bridge. Each of one were looking for a solution with their respective level of expertise. A boy walking by and witnessing the intense debate looked at the truck, at the bridge, then looked at the road and said, “Why not just let the air out of the tires?” to the absolute amazement of all the specialists and experts trying to resolve the issue.

When the solution was tested, the truck could drive with ease, having suffered only the damage caused by its initial attempt to pass underneath the bridge. It symbolizes the struggles we face where often the most obvious solutions are the ones hardest to come by because of the self-imposed constraints we work within.  

“Challenging our assumptions and everyday knowledge is often difficult for us humans, as we rely on building patterns of thinking in order not to have to learn everything from scratch every time.

Let’s come back to our topic “What is Design thinking?” Tim Brown, Executive Chairman of IDEO – an international design and consulting firm quoted design thinking as below.

“Design thinking is a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.

Now let’s think about our truck example. A boy with his fresh mindset provides a simple solution to address a complex problem. Yeah! this is the sweet spot. Everyone is creative and capable of thinking like a designer, and out of the box, to come up with a solution. This way of inculcating design as a mindset for a solution is known as Design thinking.

Yes, you read it right, everyone is creative…

We forget that back in kindergarten, we were all creative. We all played and experimented with weird things without fear or shame. We didn’t know enough not to. The fear of social rejection is something we learned as we got older. And that’s why it’s possible to regain our creative abilities, even decades later. In the field of design and user experience, there are individuals to stick with a methodology a while, they will end up doing amazing things. They come up with break through ideas or suggestions and work creatively with a team to develop something truly innovative. They surprise themselves with the realization that they are a lot more creative than they had thought. That early success shakes up how they see themselves and makes them eager to do more.

We just need to rediscover what we already have: the capacity to imagine, or build upon, new to the world ideas.  But the real value of creativity doesn’t emerge until you are brave enough to act on those ideas.

Geshe Thupten Jinpa, who has been the Dalai Lama’s chief English translator for more than twenty years, shared an insight about the nature of creativity. Jinpa pointed out that there’s no word in the Tibetan language for ‘creativity’ or ‘being creative’. The closest translation is ‘natural’. In other words, if you want to be more creative, you should be more natural! So…be natural!

At your workplace, the complex problems can be easily sorted out when you find a solution using creativity with the mindset of design thinking. Creativity can be improved by following the below steps.

  1. Go for a walk.
  2. Play your favorite games.
  3. Move your eyes.
  4. Take a break and enjoy yourself.
  5. Congratulate yourself each time you do something well.
  6. Estimate time, distance, and money.
  7. Take a route you never have taken before.
  8. Look for images in mosaics, patterns, textures, clouds, stars…
  9. Try something you have never done before.
  10. Do a creative exercise.
  11. Start a collection (stamps, coins, art, stationery, anything you wish to collect)
  12. Watch Sci-Fi or fantasy films.
  13. Change the way you do things – there are no routine tasks, only routine way of doing things.
  14. Wear a color you do not like.
  15. Think about how they invented equipment or objects you use daily.
  16. Make a list of 10 things you think are impossible to do and then imagine how you could make each one possible.
  17. For every bad thing that happens to you, remember at least 3 good things that happened.
  18. Read something you have not read yet.
  19. Make friends with people on the other side of the world.
  20. When you have an idea, make a note of it, and later check to see if it happened.
  21. Connect a sport with your work.
  22. Try food you never tried before.
  23. Talk to grandparents and relatives and listen to their stories.
  24. Give an incorrect answer to a question.
  25. Find links between people, things, ideas, or facts.
  26. Ask children how to do something and observe their creativity.

Start doing the above-mentioned steps to inculcate a creative mindset and apply it in your day-to-day work. Companies like GE health care, Procter & Gamble, UBER practiced design thinking and implemented in their new product launches and for solving complex problems in their organizations. Be natural to be more creative! When you are more creative, you can apply design thinking for seeking any solution for a complex problem in your work.

This is the first article in the series of Design led Organization in GAVS. Keep watching this space for more articles on design and keep exploring the world of design-thinking!

References:

About the Author –

Gogul is a passionate UX designer with 8+ years of experience into designing experiences for digital channels like Enterprise apps, B2C, B2B apps, Mobile apps, Kiosk, Point of Sale, Endless aisle, telecom products. He is passionate about transforming complex problems into actionable solutions using design.

Center of Excellence – Security

The Security Center of Excellence was instituted to set standards in the practice and be the point of contact for technical solutions, problem solving, etc. The broad objectives of this CoE are as follows:

  • Develop and maintain technical assets that can be leveraged across GAVS.
  • Enable Quality Governance by providing support in gating of architecture and design related deliverables.
  • Enable Operational Governance by establishing cadence for tech review of projects.
  • Create domain-based SMEs within the practice.
  • Train and upskill members in the practice.
  • Improve customer satisfactory index by implementing new ideas and innovations across all engagements.
  • Create additional SOC services for market competency.
  • Automation – Detect, investigate and remediate cyberthreats with playbooks and response workflows.

COVID and the changing nature of threat landscape

For many industries, it has been challenging period ever since the COVID outbreak, more so for those in security. Clearly, the bad actors have lot of time at their disposal which is reflective in the innovative techniques being used to attack targets. The level of vigilance required in monitoring the alerts and application of threat hunting techniques is key to diagnosing problems at initial stages of compromise in the worst-case scenario.

Microsoft Cloud Solution Provider

Remote Infrastructure Monitoring Services
Source: IBM X-Force Research

For enterprises that have no clue about MDR (Managed Detection and Response), this is a good time for them to start. We have innovative, cost effective solutions – “Make Hay while the Sun shines”. Small and large corporations alike have lost business and money because of lapse in security controls and monitoring. Now is not the time to make headlines that you are the victim of a major breach.

Our team is developing a vulnerability alerting tool, which we intend to equip customers with to provide qualified bulletin alerts, i.e. alerts only on vulnerabilities that affect them. This is a first of a kind in the market. This will greatly benefit existing and new customers.

Expanding into IAM and PAM

Security practice is expanding into Identity & Access Management (IAM) and Privileged Access Management (PAM) services. With new customers being onboarded into this focus areas for products such as Sailpoint, Thycotic, Ping, Cyberark, Okta and Azure PIM, we are expanding our talent pool through recruitment and through training and certification. This should largely benefit our existing customers and prospects who intend to leverage our security practice to fulfil their cyber security needs.

Expansion of our Red Team

Our Red Team within the practice has been expanded with many talented members, including some with bug bounty bragging rights. This has enormously helped in performing intensive tests on our internal product platforms, security assessments for customers. We have also extensively invested on tools for the Red Team to help them reduce assessment times.

Certification drive

With some more analysts having certified across AZ-500, Cyberark and trained on Darktrace. GAVS’ security analysts are taking full advantage to increase their knowledge thanks to the generosity of our alliances and training sites like Pluralsight. Even the mighty Microsoft opened their learning website for free, enabling young talent to equip themselves with critical DevOps and Cloud security skills.

As part of CoE initiatives, we have;

  • Aligned our security roadmap based on industry trends and to ensure solutions tailored for customer pain points.
  • Extended our SOC practice with IAM and PAM in 2020.
  • Identified domain-based SME and product-based SME for quick support.

We are currently in the process of creating security products, GVAS and GSMA, to help customer in proactively identifying and addressing vulnerabilities and self-maturity assessment of their cybersecurity posture. We are also underway to add Operational security to our Security practice.

If you have any questions about the CoE, you may reach out to them at COE_INFOSEC@gavstech.com

CoE Team Members

  • Venkatakrishnan A
  • Shivaram J
  • Alex Nepolian Lawrence
  • Ravindran Girikrishnan
  • Aravindah Sadhasivam Subramanian
  • Vijayakumar Veerapandiyan
  • Thubati Uday
  • Ganta Venkata Sandeep
  • Sundaramoorthy S
  • Sukanya Srinivasan

Center of Excellence – Network

The Network CoE was established to focus on Network solution design, Network design, Advanced Network troubleshooting, Network consulting, Network automation, and competency development in Next Generation Network technologies. It is also involved in conducting Network and Network security assessments in the customer’s IT infrastructure environments focused on optimization and transformation.

Network and Network Security Certification drive

As part of Network CoE, we focus on upgrading the skill sets of L1, L2, L3 Network engineers so that their competency levels are high. This is achieved by Network certification drives organized by Network COE. There are many certification drives focusing on Routing, Switching, Network security, Data Center Technologies, and Network automation driven by Network CoE like CCNA, CCNP, PCNSE, CCNA Data Center and Cisco Certified DevNet Associate. There is an active participation in these certification drives, and many GAVS engineers got themselves certified.

Standard Best Practices and Standard Operating Procedures

In Network CoE, the focus is on industry best practices. Standard Operating Practices are created for various technologies within Networking and Network security and used for Network operations.  We have Standard Operating Practices for Monitoring, NOC, switching, routing, WIFI, load balancers and Network security.

Next generation Network Transformation

The Network and Network Security Industry is undergoing key changes in terms of next generation technologies,Next Generation Firewall, Software defined Networks, WIFI 6 standard. There is an added impetus to Network automation, Intent based Networking. We enable Network transformation by enabling these technologies in customer environments.

Network Automation

We are focusing on Network automation of Standard Operating practices pertaining to Network and Network Security technologies. Instead of usual script-based automation, we focus on automation through Network Programmability via standard API interfaces. This gives much finer control and increased functionality in automation.

Network Assessments and Recommendations

We undertake Network Assessments which focuses on Networking and Network security infrastructure including devices and monitoring tools. We focus on various device types like routers, switches, firewall, WIFI controllers, WIFI access points, load balancers, Layer-3 switches, collaboration devices, SD-WAN devices, MPLS devices, VPN devices, IPS devices, etc. We also focus on Network monitoring tools.  We have a GAVS tool called GAVS topology mapper which can be used to discover network topology and its serves as one of the inputs during Network assessment. We apply standard best practices and come out with findings and recommendations. The recommendations will be directed towards Network optimization and/or Network transformation.

Solutions for Pain Points

We identify customer paint points in Networking and Network security areas and address it with comprehensive solutions. A case in point is where we designed a disaster recovery solution for an enterprise network, where the main site and DR site had different subnet schemes and for the Disaster recovery solution to work the VMs in main site and DR site need to have the same IP address.

Network Maturity Model

In GAVS, we have a Network Maturity Model. We have various levels with the Model. We use the Network Maturity Model to rate Network and Network Security setup.

Network Maturity Levels
ScoreLevel
5Optimised
4Managed
3Defined
2Repeatable
1Ad hoc
Network Design

We undertake Network design of Green Field projects (New Network) or Network re-design of Brownfield projects (Existing Network).  A case in point is where we re-designed an existing data center for better resiliency.

Data Center Design

We have designed Data Centers with N+1 Redundancy based on Cisco Nexus 9K and ACI as part of Data Center move and consolidation.  We used spine and leaf architecture for high availability. We have migrated Catalyst 6000 based data center to a Data Center with Nexus 9K.

Advanced Network and Network Security Services

We undertake several Advanced Network and Network security services. We have done large scale Cisco Identity Service Engine (ISE) Hardening and upgrade. We also migrated to DMVPN for several hundreds of sites.

Advanced Network and Network SecurityTroubleshooting

There are situations when a problem will involve two or more towers, e.g., Networking, server applications etc., we get involved and crack these kinds of problems.

For example, a problem which involved DHCP Network service running in a server. The DHCP network service became slow. We systematically analysed and found out that the actual problem is the server slowness and not the DHCP Network service. In another situation, we found out that DMZ firewall was having 90% CPU utilization which led to connection drops of Applications and we fixed it by upgrading the firewall devices.

Conclusion

We continue to partner with GAVS Customer success managers to provide unique experience to customers in the Networking area.

If you have any questions about the CoE, you may reach out to them at COE_NETWORK@gavstech.com

CoE Team Members

  • Ambika Tripathi
  • Andrew Ellis
  • AvineshYokanathan
  • Deepak Narayanaswamy
  • Durai Murugan Prakash
  • Faheem koyatty
  • Ganesh Kumar J
  • Gayathri R
  • Ibrahim Silver Nooruddin
  • JettiTarakesh
  • Justin Robinson
  • Krishnakumar R
  • Nabiulla A
  • Nandhini Prabhu
  • Navaneetha Krishnan
  • Palanisamy Sakthivel
  • Prasad R
  • Rajeshkanna S
  • Ravichandran V
  • Shafi H
  • Shamini P
  • Shanmukha Ganesh
  • Sridhar
  • Srijith
  • Suresh Chander
  • Venkata Manikrishna Soma
  • Vishal Manuhar

Center of Excellence – Java

The Java CoE was established to partner with our customers and aid them in realizing business benefits through effective adoption of cutting-edge technologies; thus, enabling customer success.

Objectives

  • Be the go-to team for anything related to Java across the organization and customer engagements.
  • Build competency by conducting training and mentoring sessions, publishing blogs, whitepapers and participating in Hackathons.
  • Support presales team in creating proposals by providing industry best solutions using the latest technologies, standards & principles.
  • Contribute a certain percent of revenue growth along with the CSMs.
  • Create reusable artifacts, frameworks, solutions and best practices which can be used across organization to improve delivery quality.

Focus Areas

  1. Design Thinking: Setting up a strong foundation of “Design Thinking and Engineering Mindset” is paramount for any business. We aim to do so in the following way:
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2. Solution and Technology: Through our practice, we aim to equip GAVS with solution-oriented technology leaders who can lead us ahead through disruptive times

IT Operations Management Software

3. Customer success

  • Identify opportunities in accounts based on the collaboration with CSMs, understand customer needs, get details about the engagement, understand the focus areas and challenges.
  • Understand the immediate need of the project, provide solution to address the need.
  • Java council to help developers arrive at solutions.
  • Understand architecture in detail and provide recommendation / create awareness to use new technologies
  • Enforce a comprehensive review process to enable quality delivery.

Accomplishments

  • Formed the CoE team
  • Identified the focus Areas
  • Identified leads for every stream
  • Socialized the CoEwithin GAVS
  • Delivered effective solutions across projects to improve delivery quality
  • Conducted trainings on standards and design-oriented coding practices across GAVS
  • Publishedblogs to bring in design-oriented development practices
  • Identified the areas for creating re-usable artefacts (Libraries / Frameworks)
  • Brainstormed and finalized the design for creating Frameworks (For the identified areas)
  • Streamlined the DevOps process which can be applied in any engagement
  • Built reusable libraries, components and frameworks which can be used across GAVS
  • Automated the Code Review process
  • Organized and conducted hackathons and tech meetups
  • Discovered potential technical problems/challenges across teams and offered effective solutions, thereby enabling customer success
  • Supported the presales team in creating customized solutions for prospects

Upcoming Activities

  • Establishing tech governance and align managers / tech leads to the process
  • Setting up security standards and principles across domain
  • Buildingmore reusable libraries, components and frameworks which can be used across GAVS
  • Adopting Design Patterns / Anti-patterns
  • Enforcing a strong review process to bring in quality delivery
  • Enabling discussions with the customers
  • Setting up a customer advisory team

Contribution to Organizational Growth

As we continue our journey, we aim to support the revenue growth of our organization. Customer Success being a key goal of GAVS, we will continue to enable it by improving the quality of service delivery and building a solid foundation across all technology and process streams. We also want to contribute to the organization by developing a core competency around a strategic capability and reduce knowledge management risks.

If you have any questions about the CoE, you may reach out to them at COE_JAVA@gavstech.com

CoE Team Members

  • Lakshminarasimhan J
  • Muraleedharan Vijayakumar
  • Bipin V
  • Meenakshi Sundaram
  • Mahesh Rajakumar M
  • Ranjith Joseph Selvaraj
  • Jagathesewaren K
  • Sivakumar Krishnasamy
  • Vijay Anand Shanmughadass
  • Sathya Selvam
  • Arun Kumar Ananthanarayanan
  • John Kalvin Jesudhason

IoT Adoption during the Pandemic

Artificial Intelligence for IT Operations

Naveen KT

From lightbulbs to cities, IoT is adding a level of digital intelligence to various things around us. Internet of Things or IoT is physical devices connected to the internet, all collecting and sharing data, which can then be used for various purposes. The arrival of super-cheap computers and the ubiquity of wireless networks are behind the widespread adoption of IoT. It is possible to turn any object, from a pill to an airplane, into an IoT-enabled device. It is making devices smarter by letting them ‘sense’ and communicate, without any human involvement.

Let us look at the developments that enabled the commercialization of IoT.

History

The idea of integrating sensors and intelligence to basic objects dates to the 1980s and 1990s. But the progress was slow because the technology was not ready. Chips were too big and bulky and there was no way for an object to communicate effectively.

Processors had to be cheap and power-frugal enough to be disposed of before it finally becomes cost-effective to connect to billions of devices. The adoption of RFID tags and IPV6 was a necessary step for IoT to scale.

Kevin Ashton penned the phrase ‘Internet of Things’ in 1999. Although it took a decade for this technology to catch up with his vision. According to Ashton “The IoT integrates the interconnectedness of human culture (our things) with our digital information system(internet). That’s the IoT”.

Early suggestions for IoT include ‘Blogjects’ (object that blog and record data about themselves to the internet), Ubiquitous computing (or ‘ubicomp’), invisible computing, and pervasive computing.

How big is IoT?

AIOps in Infrastructure Management

IDC predicts that there will be 41.6 billion connected IoT devices by 2025. It also suggests industrial and automotive equipment represent the largest opportunity of connected ‘things’.

Gartner predicts that the enterprise and automotive sectors will account for 5.8 billion devices this year.

However, the COVID-19 pandemic has further enhanced the need for IoT-enabled devices to help the nations tackle the crisis.

IoT for the Government

Information about the movement of citizens is urgently required by governments to track the spread of the virus and potentially monitor their quarantine measures. Some IoT operators have solutions that could serve these purposes.

AIOps platform
  • Telia’s Division X has developed Crowd Insights which provides aggregated smartphone data to city and transport authorities of Nordic Countries. It is using the tool which will track the movement of citizens during the quarantine.
  • Vodafone provides insights on traffic congestion.
  • Telefonica developed Smart steps, which aggregates data on footfall and movement for the transport, tourism, and retail sectors.

Personal data of people will also help in tracking clusters of infection by changing the privacy regulations. For example, in Taiwan, high-risk quarantined patients were being monitored through their mobile phones to ensure compliance with quarantine rules. In South Korea, the officials track infected citizens and alert others if they come into contact with them. The government of Israel went as far as passing an emergency law to monitor the movement of infected citizens via their phones.

China is already using mass temperature scanning devices in public areas like airports. A team of researchers at UMass Amherst is testing a device that can analyze coughing sounds to identify the presence of flu-like symptoms among crowds.

IoT in Health care

COVID-19 could be the trigger to explore new solutions and be prepared for any such future pandemics, just as the SARS epidemic in 2003 which spurred the governments in South Korea and Taiwan to prepare for today’s problems.

IT operations analytics

Remote patient monitoring (RPM) and telemedicine could be helpful in managing a future pandemic. For example, patients with chronic diseases who are required to self-isolate to reduce their exposure to COVID-19 but need continuous care would benefit from RPM. Operators like Orange, Telefónica, and Vodafone already have some experience in RPM.

Connected thermometers are being used in hospitals to collect data while maintaining a social distance. Smart wearables are also helpful in preventing the spread of the virus and responding to those who might be at risk by monitoring their vital signs.

Connected thermometers are being used in hospitals to collect data while maintaining a social distance. Smart wearables are also helpful in preventing the spread of the virus and responding to those who might be at risk by monitoring their vital signs.

Telehealth is widely adopted in the US, and the authorities there are relaxing reimbursement rules and regulations to encourage the extension of specific services. These include the following.

  • Medicare, the US healthcare program for senior citizens, has temporarily expanded its telehealth service to enable remote consultations.
  • The FCC has made changes to the Rural Health Care (RHC) and E-Rate programs to support telemedicine and remote learning. Network operators will be able to provide incentives or free network upgrades that were previously not permitted, for example, for hospitals that are looking to expand their telemedicine programs.

IoT for Consumers

The IoT promises to make our environment smarter, measurable, and interactive.COVID-19 is highly contagious, and it can be transmitted from one to another even by touching the objects used by the affected person. The WHO has instructed us to disinfect and sanitize high touch objects. IoT presents us with an ingenious solution to avoid touching these surfaces altogether. Hands-free and sensor-enabled devices and solutions like smart lightbulbs, door openers, smart sinks, and others help prevent the spread of the virus.

Security aspects of IoT

Security is one of the biggest issues with the IoT. These sensors collect extremely sensitive data like what we say and do in our own homes and where we travel. Many IoT devices lack security patches, which means they are permanently at risk. Hackers are now actively targeting IoT devices such as routers and webcams because of their inherent lack of security makes them easy to compromise and pave the way to giant botnets.

Machine learning service provider
Machine learning service provider

IoT bridges the gap between the digital and the physical world which means hacking into devices can have dangerous real-world consequences. Hacking into sensors and controlling the temperature in power stations might end up in catastrophic decisions and taking control of a driverless car could also end in disaster.

Overall IoT makes the world around us smarter and more responsive by merging the digital and physical universe. IoT companies should look at ways their solutions can be repurposed to help respond to the crisis.

Enterprise IT infrastructure services
Enterprise IT infrastructure services

References:

  • https://www.analysysmason.com/Research/Content/Comments/covid19-iot-role-rdme0-rma17/
  • shorturl.at/wBFGT

Naveen is a software developer at GAVS. He teaches underprivileged children and is interested in giving back to society in as many ways as he can. He is also interested in dancing, painting, playing keyboard, and is a district-level handball player.

Discover, Monitor, Analyze & Predict COVID-19

Bargunan Somasundaram

Uber, the world’s largest taxi company, owns no vehicles. Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. Netflix, the world’s largest movie house, own no cinemas. And Airbnb, the world’s largest accommodation provider, owns no real estate. Something interesting is happening.”

– Tom Goodwin, an executive at the French media group Havas.

This new breed of companies is the fastest growing in history because they own the customer interface layer. It is the platform where all the value and profit is. “Platform business” is a more wholesome term for this model for which data is the fuel; Big Data & AI/ML technologies are the harbinger of new waves of productivity growth and innovation.

With Big data and AI/ML is making a big difference in the area of public health, let’s see how it is helping us tackle the global emergency of coronavirus formally known as COVID-19.

DISCOVERING / DETECTING

Chinese technology giant Alibaba has developed an AI system for detecting the COVID-19 in CT scans of patients’ chests with 96% accuracy against viral pneumonia cases. It only takes 20 seconds for the AI to decide, whereas humans generally take about 15 minutes to diagnose the illness as there can be upwards of 300 images to evaluate. The system was trained on images and data from 5,000 confirmed coronavirus cases and has been tested in hospitals throughout China. Per a report, at least 100 healthcare facilities are currently employing Alibaba’s AI to detect COVID-19.

Ping An Insurance (Group) Company of China, Ltd (Ping An) aims to address the issue of lack of radiologists by introducing the COVID-19 smart image-reading system. This image-reading system can read the huge volumes of CT scans in epidemic areas.

Ping An Smart Healthcare uses clinical data to train the AI model of the COVID-19 smart image-reading system. The AI analysis engine conducts a comparative analysis of multiple CT scan images of the same patient and measures the changes in lesions. It helps in tracking the development of the disease, evaluation of the treatment and in prognosis of patients. Ultimately it assists doctors to diagnose, triage and evaluate COVID-19 patients swiftly and effectively.

Ping An Smart Healthcare’s COVID-19 smart image-reading system also supports AI image-reading remotely by medical professionals outside the epidemic areas. Since its launch, the smart image-reading system has provided services to more than 1,500 medical institutions. More than 5,000 patients have received smart image-reading services for free.

The more solutions the better. At least when it comes to helping overwhelmed doctors provide better diagnoses and, thus, better outcomes.

MONITORING

  • AI based Temperature monitoring & scanning

In Beijing, China, subway passengers are being screened for symptoms of coronavirus, but not by health authorities. Instead, artificial intelligence is in-charge.

Two Chinese AI giants, Megvii and Baidu, have introduced temperature-scanning. They have implemented scanners to detect body temperature and send alerts to company workers if a person’s body temperature is high enough to constitute a fever.

Megvii’s AI system detects body temperatures for up to 15 people per second and up to 16 feet. It monitors as many as 16 checkpoints in a single station. The system integrates body detection, face detection, and dual sensing via infrared cameras and visible light. The system can accurately detect and flag high body temperature even when people are wearing masks, hats, or covering their faces with other items. Megvii’s system also sends alerts to an on-site staff member.

Baidu, one of the largest search-engine companies in China, screens subway passengers at the Qinghe station with infrared scanners. It also uses a facial-recognition system, taking photographs of passengers’ faces. If the Baidu system detects a body temperature of at least 99-degrees Fahrenheit, it sends an alert to the staff member for another screening. The technology can scan the temperatures of more than 200 people per minute.

  • AI based Social Media Monitoring

An international team is using machine learning to scour through social media posts, news reports, data from official public health channels, and information supplied by doctors for warning signs of the virus across geographies. The program is looking for social media posts that mention specific symptoms, like respiratory problems and fever, from a geographic area where doctors have reported potential cases. Natural language processing is used to parse the text posted on social media, for example, to distinguish between someone discussing the news and someone complaining about how they feel.

The approach has proven capable of spotting a coronavirus needle in a haystack of big data. This technique could help experts learn how the virus behaves. It may be possible to determine the age, gender, and location of those most at risk quicker than using official medical sources.

PREDICTING

Data from hospitals, airports, and other public locations are being used to predict disease spread and risk. Hospitals can also use the data to plan for the impact of an outbreak on their operations.

Kalman Filter

Kalman filter was pioneered by Rudolf Emil Kalman in 1960, originally designed and developed to solve the navigation problem in the Apollo Project. Since then, it has been applied to numerous cases such as guidance, navigation, and control of vehicles, computer vision’s object tracking, trajectory optimization, time series analysis in signal processing, econometrics and more.

Kalman filter is a recursive algorithm which uses time-series measurement over time, containing statistical noise and produce estimations of unknown variables.

IT Infrastructure Managed Services

For the one-day prediction Kalman filter can be used, while for the long-term forecast a linear model is used where its main features are Kalman predictors, infected rate relative to population, time-depended features, and weather history and forecasting.

The one-day Kalman prediction is very accurate and powerful while a longer period prediction is more challenging but provides a future trend. Long term prediction does not guarantee full accuracy but provides a fair estimation following the recent trend. The model should re-run daily to gain better results.

GitHub Link: https://github.com/Rank23/COVID19

ANALYZING

The Center for Systems Science and Engineering at Johns Hopkins University has developed an interactive, web-based dashboard that tracks the status of COVID-19 around the world. The resource provides a visualization of the location and number of confirmed COVID-19 cases, deaths and recoveries for all affected countries.

The primary data source for the tool is DXY, a Chinese platform that aggregates local media and government reports to provide COVID-19 cumulative case totals in near real-time at the province level in China and country level otherwise. Additional data comes from Twitter feeds, online news services and direct communication sent through the dashboard. Johns Hopkins then confirms the case numbers with regional and local health departments. This kind of Data analytics platform plays a pivotal role in addressing the coronavirus outbreak.

All data from the dashboard is also freely available in the following GitHub repository.

GitHub Link: https://bit.ly/2Wmmbp8

Mobile version: https://bit.ly/2WjyK4d

Web version: https://bit.ly/2xLyT6v

Conclusion

One of AI’s core strengths when working on identifying and limiting the effects of virus outbreaks is its incredibly insistent nature. AI systems never tire, can sift through enormous amounts of data, and identify possible correlations and causations that humans can’t.

However, there are limits to AI’s ability to both identify virus outbreaks and predict how they will spread. Perhaps the best-known example comes from the neighboring field of big data analytics. At its launch, Google Flu Trends was heralded as a great leap forward in relation to identifying and estimating the spread of the flu—until it underestimated the 2013 flu season by a whopping 140 percent and was quietly put to rest. Poor data quality was identified as one of the main reasons Google Flu Trends failed. Unreliable or faulty data can wreak havoc on the prediction power of AI.

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About the Author:

Bargunan is a Big Data Engineer and a programming enthusiast. His passion is to share his knowledge by writing his experiences about them. He believes “Gaining knowledge is the first step to wisdom and sharing it is the first step to humanity.”