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The new face of big data: AI, IoT and blockchain

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The Internet of Things

The IoT typifies big data’s most demonstrable characteristics with its continuous generation of unstructured streaming, event-based data from a multitude of decentralized sources. Historically, the technology has buttressed the Industrial Internet in the form of equipment asset monitoring and predictive analytics for maintenance. Gartner has predicted, “By 2022, IoT will save consumers and businesses $1 trillion a year in maintenance, services and consumables.”

However, more recent advances in the IoT and the influence of AI have successfully extended its scope to include other verticals. IDC’s 2017 predictions indicate that “by 2019, 40 percent of digital transformation initiatives and 100 percent of IoT initiatives will be supported by AI capabilities. Top three AI use cases in terms of spending ... are: medical diagnostics and treatment, quality management in manufacturing and automated service agents in retail.”

The telecommunications industry has also been widely impacted by the IoT. In fact, the growing relationship between big data and the IoT is characterized by Jack Norris, MapR  senior VP of data and applications, who says, “If you kind of define IoT fairly broadly, then a lot of big data is generated one event at a time whether that’s a log file, a social media interaction or a customer transaction.”

Regardless of the source data, the cardinal concern with monetizing the IoT pertains to analytics and security. A common approach to the former is to employ a decentralized model in which devices at the cloud’s edge perform basic analytics and transmit the results—instead of the raw data—to centralized locations for more complex analytics. This process is enhanced by AI capabilities that may involve pattern recognition. An alternative approach involves what Gartner calls a digital twin, which “captures near real-time data feeds from its sensor-enhanced real-world twin ... and uses this to update its simulation to reflect the physical state of the twin.”

The need to perfect the time series analytics required for effective IoT deployments is also driven by the healthcare industry and the market for wearables. Wearables provide metrics for patients analogous to the predictive capabilities of the maintenance and equipment asset monitoring germane to the industrialized sector. Waqaas Al-Siddiq, co-founder and CEO of Biotricity, a startup that specializes in wearables in accordance with FDA (fda.gov) regulations, discussed the importance of AI’s impact on that manifestation of big data. “Right now we have mathematical algorithms that are used in the [endpoint] device to detect mathematical anomalies,” he says. “They’re very range-specific. The idea is to use deep learning to try and understand how these algorithms can be manipulated from one individual to another to personalize them.”

Blockchain

The more pressing concern associated with the IoT is security, which has intensified since the Dyn cyber attack in which endpoint devices were used to both perpetuate attacks and penetrate the security of centralized datacenters. The decentralized, disparate nature of the individual gadgets encompassing the IoT (external to enterprise firewalls) makes security an inherent weakness. This reality is compounded by the fact that most of those simplified mobile devices lack the sophistication required for substantial security fortification. A synopsis of a Gartner webinar about the Top 10 IoT Technologies for 2017 and 2018 states, “Security technologies will be required to protect IoT devices and platforms from both information attacks and physical tampering, to encrypt their communications, and to address new challenges such as impersonating ‘things’ or denial-of-sleep attacks.”

Blockchain technologies could possibly provide the basis for IoT security. Gartner Glossary defines blockchain as a “distributed ledger in which value exchange transactions ... are sequentially grouped into blocks. Each block is chained to the previous block and immutably recorded across a peer-to-peer network, using cryptographic trust and assurance mechanisms.”

Blockchain’s relevance to IoT and enterprise security largely lies in its unalterable nature and expedience, underscored by its encryption capabilities. Highlights from Forrester’s 2017 Predictions for the IoT indicate “the cloud will be trusted and by 2020, it will be where trusted and secured IT lives, enhanced by blockchain-based security.”

Spearheaded by the widespread adoption of BitCoin (bitcoin.org), blockchain technologies are gaining credence throughout the finance and healthcare spaces. The rapid nature of the secure transactions they facilitate could potentially reduce costs for transactional data systems while hastening dependent business processes.

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