One of the most difficult challenges faced by businesses in asset-intensive industries is how to control and scale the half billion and growing “smart” devices that make up the Internet of Things (IoT)? As much as 80 percent of IoT data in any organization is unstructured. And, let’s be honest, “smart” devices really aren’t that smart yet.
As part of its giant rollout of AI solutions pre-trained for specific industries and professions, IBM Services is launching a new Connected Manufacturing offering that includes a method and approach to help clients accelerate their IoT transformation--from strategy, implementation, and security to managed services and ongoing operations. This combined capability, IBM said, will help its clients connect all of their manufacturing equipment, sensors, and systems to enable business improvement across OEE, quality, lead times and productivity.
The new IoT offering focuses on industries that are heavily IoT dependent--industrial equipment, automotive (smart vehicles) and buildings (smart spaces). The IBM pitch is that its AI Watson solution, combined with its Industrial IoT platform gives the not-so-smart “things” the data they need to understand the physical world as everything becomes connected, as well as help customers make sense of the vast amounts of data IoT is generating. Said Kareem Yusuf, GM, IBM Watson IoT:
Companies are connecting their industrial equipment, buildings and facilities, and vehicles with billions of IoT devices. These “things” are not only creating exponential amounts of data, but also creating opportunities to identify patterns that unlock new ways of working, new outcomes and new business value, all critical elements. But, companies are becoming overwhelmed. AI is critical to making sense of all this data to enable people and things to work smarter and better.
Among the new AI-based IoT capabilities:
Industrial/Manufacturing | Production Quality Insights, Production Optimization, Equipment Maintenance Assistant: At a time of intense global competition, manufacturers are facing a variety of issues that impact productivity including workforce attrition, skills-gaps and rising raw material costs. By combining the IoT and AI, manufacturers can stabilize production costs by pinpointing and predicting areas of loss such as energy waste, equipment failures, and issues that drive product quality.
Vehicles/Auto | Requirements Quality Assistant: The advent of autonomous driving, electric vehicles, evolutions in consumer preferences and the almost limitless availability of real-time data about driving patterns, usage and performance are transforming the automotive industry. At the same time, as vehicles become more complex, engineering requirements are exploding, with the typical vehicle today requiring over 100 million lines of code and thousands of engineering requirements.
Spaces/Retail | Watson IoT Building Insights: Today, 70% of a building’s total cost of ownership is linked to maintenance and energy costs. By combining IoT and AI, retail owners and property managers can now analyze patterns of space, energy, traffic and asset usage, to create utilization strategies that reduce waste and optimize resources to maximize real estate investments.
And of course, we can't forget the all-important "Trust and Transparency Capabilities."
The new industry-specific IoT software rollout follows an announcement last week that IBM was launching a software service that automatically detects bias and explains how AI makes decisions--as the decisions are being made. The service runs on the IBM Cloud, and helps organizations manage AI systems from a wide variety of industry players.
In addition, IBM Research will release into the open source community an AI bias detection and mitigation toolkit, bringing forward tools and education to encourage global collaboration around addressing bias in AI.
These developments come on the back of new research by IBM's Institute for Business Value, which reveals that while 82 percent of enterprises are considering AI deployments, 60 percent fear liability issues and 63 percent lack the in-house talent to confidently manage the technology.
IBM has been researching AI and machine learning for many years and it is clearly paying off in a burst of new services and enthusiasm at one of America oldest and most venerable software firms.
IBM’s multiyear investment in IoT encompasses building expertise in key industries markets, including manufacturing, energy, and oil and gas, making the idea of offering pre-trained IoT software tailored to specific industries a very smart move. The future belongs to the technology companies that can connect the physical and digital worlds. IBM seems very well positioned to do help do that.