For Enterprises Across Businesses

The Internet of Things is getting smarter. Companies are incorporating artificial intelligence--in particular, machine learning--to their IoT applications. The key is finding insights in data.

Brand new products and a rising tide of enterprise deployments, artificial intelligence is creating a splash in the Internet of Things (IoT). Companies crafting an IoT strategy, evaluating a possible new IoT project, or attempting to acquire more value from a current IoT deployment may want to explore a role for AI.

Artificial intelligence plays a Growing role in IoT applications and deployments. Both acquisitions and investments in startups that unite AI and IoT have risen over the last two years. Significant vendors of IoT platform software now offer integrated AI capabilities like machine learning-based analytics.

The value of AI in this context is Machine learning, an AI technology, brings the ability to automatically identify patterns and detect anomalies in the data that smart sensors and devices create --information like temperature, pressure, humidity, air quality, vibration, and sound.

Other AI technologies like speech Recognition and computer vision can help extract insight from information that used to require individual review.

AI software for IoT enable Companies to avoid unplanned downtime, increase operating efficiency, spawn new services and products, and improve risk management.

Numerous sectors--industrial Fabricating or offshore oil and gas, to name two--unplanned downtime caused by equipment breakdown can cost big money.

Predictive maintenance--using Analytics to predict equipment failure beforehand in order to schedule orderly maintenance processes --can mitigate the harmful economics of unplanned downtime. Machine learning makes it possible to recognize patterns in the continuous streams of data from today's machines to predict equipment failure.

AI-powered IoT can also help improve operational efficiency. As machine learning may predict equipment failure; it may predict operating conditions and identify parameters to be adjusted on the fly to keep perfect outcomes, by crunching continuous streams of data to detect patterns invisible to the human eye and not clear on simple gauges.

Counterintuitive insights: A shipping fleet operator's machine learning tools ascertained that cleaning their ships' hulls more often--a costly, downtime-causing process--actually increased the fleet's overall profitability. The mathematics went against transport industry instincts: Hulls kept smooth through regular cleaning improve fuel efficiency enough to vastly outweigh the higher cleaning costs.

Directly create new services and products. Natural language processing is getting better and better at allowing people speak with machines, rather than requiring an individual operator. AI-controlled drones and robots--which can go where humans can't--bring all-new chances for monitoring and review that, simply did not exist before.
Vehicles is being reinvented through AI, which can track every quantifiable data point in a fleet of airplanes, trains, trucks or automobiles to find more efficient routing and scheduling, and reduce unplanned downtime.

A number of applications pairing IoT With AI are helping organizations better understand and predict an assortment of risks in addition to automate for quick response, enabling them to better manage worker safety, financial loss, and cyber threats.

Programs already in use include Detecting fraudulent behavior at bank ATMs, calling auto driver insurance premiums based on their driving patterns, identifying potentially hazardous anxiety conditions for factory workers, and monitoring law enforcement surveillance data to identify likely crime scenes ahead of time.

For enterprises across Businesses, AI is a natural match to IoT deployments, allowing better offerings and operations to give a competitive edge in business performance.

Bundled or vertical IoT solutions make the most of AI technologies, more value from IoT deployments which were not designed with the use of AI in mind. IoT deployments generate huge, continuous streams of data, which machine Learning excels at analyzing to identify patterns that lead to greater value. For both computation and storage Dxchain delivers a robust solution.

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