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The Future of Data Integrity

IoT – Economic Impact and Use Cases

October 29, 2019

Digitalization and Compliance

The generic process underlying most IIoT application is the collection of data which is then processed shared, and used for further action, creating requests, sending, giving assignments, create a repository or giving strategical or operational insights, and more.

This simple underlying process enabling efficient automation and effective sharing of necessary information has made a profound impact on many industries, from healthcare over logistics to energy and utilities.

Last blog post we have shared the Tech-stack of IoT. Read here about the economic impact and use cases in IoT.

Supply Cain | Cold Chain

IoT us often used in supply chains, certain chains require a lot of attention due to the sensitivity of the products supplied, such as cold chains for pharmaceuticals or other perishable goods. IoT solutions for cold chains are used to decrease product failure and increase trust in the products delivered, since they can provide a complete picture of the conditions under which sensitive foods have been transported and stored, creating real-time visibility.

This is why it is key for all if participating parties to have some way of verifying whether the data is in its original state or not. Further, this is of great importance as regulators made suppliers proof that their chain has adhered to regulations.

Remote Patient Monitoring

The healthcare sector has found many incredible applications for IoT. Especially regarding patient care, the health sector has made huge strides forward with solutions like remote patient monitoring. Treatments for chronic diseases in particular are and will profit immensely from IoT applications, one of them would be in regards to diabetes patients.

Diabetes for instance has become a “global epidemic” with over 475 million people suffering worldwide. Further, the number is growing and is expected to rise to about 642 million by 2040. A large telecommunications provider, for example, has teamed up with an IoT sensor company specialized in diabetes IoT devices with an attached management and data exchange platform to provide increased service to patients, especially less mobile or remotely living individuals. (Vodafone, 2019) (Diabetes.co.uk, 2019)

Solution providers need to be not only responsible but compliant with health and personal data regulations, this implies that data is not only safe but unchanged. If patient data is tampered with, there are lives at risk. This means that every piece of data needs to provide some sort of mechanism to check for its integrity to be compliant.

Transactive Energy

The utility sector has increasingly opened up towards IoT applications for consumers. Energy – as a sub-segment of utilities – has seen many incredible innovations.

Within a transactive microgrid, “prosumers” (individuals that are consumers and produces at the same time (Prof. Dr. Markgraf, 2019), consumers with energy generation and storage capabilites supplying to the energy grid) can trade energy with each other thereby smoothing the load on the main grid using local supply. In the past providing security, safety, and privacy in a transactive energy system was often facilitated by finding an entity of trust to enable effective business.

What all IoT applications have in common is the processing and use of mission-critical information, which in turn brings back the question of how organizations manage to stay in control and remain compliant regarding the use of data?  Not only that but how can organizations make sure that their information is trustworthy to other parties?

For the last question, the answer seems obvious: find an entity of trust to facilitate business. This, however, has several drawbacks; first it takes time to agree upon a common source of trust, the process of finding one might take time and effort, every additional partner needs to agree on this source of trust, different markets might not accept the middle-man, and lastly employing the services of a ‘trust-giving’ middle-man is often costly and slow –  hindering business.

What all of the IoT data-based business processes need is independently verifyable trust created though an immutable mathematical process that can run in parallel to the actual business processes. This would present the opportunity to every party in a chain of production to verify underlying data and information themselves when required without slowing down the process unnecessarily.

Summary

The Internet of Things is and will be a revolutionary force in many industries across the globe and will change lives for the better. In the next decade the amount of devices that are connected and able to communicate with each other independently will rise exponentially, constrained mostly by the scarcity of resources and pushed by increasing efficiency, effectiveness and decrease costs of most if not all affected industries.

With the incredible growth of IoT devices and network(s), there will also be a massive increase in the amount of data produced and processed for analytics, data exchanges, and further actions.

All the positive attributes of collecting and processing huge amounts of data have been made apparent throughout this paper. However, on the other side, organizations now have to manage, maintain and secure the massive amounts of data, especially regarding existing and upcoming data protection and management regulations such as GDPR, CCPA, HIPAA or SOX. With evolving industries, so to will regulation evolve further and increase pressure on companies to fervently and pro-actively seek out solutions to be prepared. In this new world, traditional security methods will not be enough — distributed technologies, based on mathematical principles, will likely play a vital role in proving data provenance, data integrity, and data security.

Read the whole white paper about “The Internet of Things – Digitalization and Compliance” here.