Saturday , September 18 2021

Is AI more important than Big Data for IoT Implementation?

The development of the internet of things has revolutionized the heavy industry, online shopping, localized data collection and virtually every other aspect of modern life and business. However, innovators are still struggling over the future of the IoT, and how they’ll get there. While many see big data as the driving engine behind the IoT, savvy investors and entrepreneurs have shown that artificial intelligence is the real power of the interconnectivity phenomenon.

Today’s AI is increasingly capable of operating as a prediction engine, being used to foresee and exploit forthcoming market trends more so than being used as robotic labor.

As the quality of AI’s predictions continues to grow, companies in virtually every industry will come to rely on its accurate forecast more so than on big data analytics. While investments in big data will serve companies for decades to come, the potential of big data can only truly be realized when it’s paired with advanced AI capable of putting it to good use.

IoT sensors are rapidly coming to be embedded in virtually every modern structure and home, meaning localized data collection is more optimized now than ever before. As the volume of data collected grows, only AI with deep machine learning capabilities will be able to crunch it effectively.

By relying on advanced AI to spur further development in the IoT, companies and individual innovators will be able to better predict the outcomes of business decisions before they’re even made. AI will helpfully point out the common pitfalls made by startups trying to create IoT applications and will help successful startups optimize their performance once they get off the ground.

AI is quickly coming to automate even the most complex and fragile of operations, such as mining ventures. As the IoT grows and more connected devices are used in tandem with one another, machine learning capable of keeping up with the dizzying amounts of data will be necessary for future business endeavors to succeed.

Besides that, for enterprise software, operational efficiency trumps superfluous features. When it comes to optimising these applications, particularly for the Internet of Things (IoT), enterprises need to focus their efforts on the basics of business optimization rather than insight driven innovation. A recent GlobalData survey of 1,000 IoT professionals revealed a heavy reliance on traditional business intelligence (BI) software. And, 40 percent of those surveyed ranked business intelligence platforms well above all other means of analyzing data.

Unfortunately, with the broad market trend toward the democratization of data now well-established, such do-it-all BI software platforms have already given way to numerous smaller, more discrete ways of deriving value from enterprise data. Business intelligence software is reactionary and static. Its users rely heavily upon basic reporting mechanisms that, in turn, rely heavily on laborious queries and reports, which is a very costly venture to both build and maintain.

Artificial Intelligence (AI), however, can do far more than inform. It can immediately prove the value of IoT as a means of optimizing existing business processes. With even the simplest AI machine learning (ML) framework and model at the ready, for example, IoT practitioners can solve two pressing problems: detecting anomalies and predicting desired outcomes.

The problem lies within the idea of centralization. Centralization is part and parcel of traditional BI analysis and reporting and traditional ideas like predictive modeling. Where AI is most valuable at the edge. IoT deployments need to employ tools like ML, not centrally, but at the edge, close to the device itself. And like today’s enterprise software, those analytics endeavors should be brief and to the point, and focused on solving specific challenges.

As a new generation of AI explicitly designed to work alongside humans is born, current ways of doing business or predicting future trends will come to be entirely revolutionized. Tapping into the potential of AI won’t be easy, but doing so will be far more profitable for the IoT’s future than relying on big data alone. As programmed intelligence grows to new and greater heights, its ability to optimize the IoT will only be enhanced.

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