Controlling and scaling massive Internet of Things (IoT) installations is difficult, especially in asset-rich organisations, such as industrial and manufacturing companies.
More, with each connected thing being a data point that could tell both operators and business leaders how the organisation is running – and predict how it will run in the future – managing the mass of unstructured data that comes from sensors and other connected devices is itself a massive challenge.
That’s where artificial intelligence comes in, according to IBM.
The cognitive services giant has launched a range of new AI-enabled IoT offerings this week, to help organisations accelerate their IoT programmes from ‘soup to nuts’ – from strategy, implementation, and security, to managed services and daily operations, according to the company.
Agriculture, customer service, human resources, supply chain, manufacturing, building management, automotive, marketing, and advertising are the sectors addressed by the new suite of Watson tools.
The data point
“As data flows continue to increase, people are overwhelmed by the amount of information we have to act on every day, but luckily the information explosion coincides with another key technological advance: artificial intelligence,” said David Kenny, senior VP, IBM Cognitive Solutions.
“AI is the tool professionals need to take advantage of the data that’s now at our fingertips and tailoring general AI for specific industries and professions is a critical way to enable everyone to reach new potential in their daily jobs.”
IBM is combining its Watson AI – the question-answering system that has become a cloud-based, natural-language AI platform and mobile digital assistant – with its IoT portfolio to launch a range of ‘pre-trained’ IoT services.
From AI to table
First, IBM is making the Watson Decision Platform for Agriculture available globally, a solution that the company says works from “AI to table”.
The new platform gathers data from multiple sources – such as the weather, IoT-enabled tractors and irrigators, satellite imagery, and more – to provide a single, overarching, predictive view of farm data in a single app.
“For the individual grower, this means support for making more informed decisions to help improve yield,” said IBM. “For example, using AI-enabled visual recognition capabilities, growers can identify certain types and severity levels of pest and disease damage and determine where to spray pesticides. Or a grower can forecast water usage, thereby reducing waste and helping to save money.”
Alongside Watson Assistant releases for Salesforce, marketing, advertising, and HR applications, IBM is also releasing new Watson toolsets for industrial IoT (IIoT) applications.
According to Kareem Yusuf, general manager of IBM Watson for the 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 opportunities to identify patterns that unlock new ways of working, new outcomes and new business value, all critical elements.”
As a result, those organisations are being overwhelmed by the challenge, and left drowning in data lakes clogged with millions of devices, which is where IBM believes Watson can help.
Among the new IoT capabilities, Connected Manufacturing sees Watson becoming a maintenance assistant in industrial deployments and manufacturing, combining its insight capabilities with the IoT to offer predictive maintenance and energy management skills.
Watson can also become a quality control assistant in the worlds of connected mobility and transport, said IBM, looking at real-time data about driving patterns, usage, and performance.
Meanwhile in the smart spaces and retail environments, IBM is offering Watson IoT Building Insights, to help managers analyse their space, energy, and asset usage.
It is also releasing Watson Supply Chain Insights to help decision-makers manage their smart, connected logistics and transport operations.
Internet of Business says
With IBM also moving deeper into blockchain platforms and related technologies, its aim to be an arbiter of trust and transparency in, and for, the enterprise alongside its cognitive services is becoming clear.
Earlier this month, IBM unveiled a new system to help detect bias in a range of popular AI and machine learning platforms.