Imagine machines efficiently working side by side with humans to troubleshoot critical conditions based on a collaborative process informed by machine and human learning. Augmented by machine intelligence and the constant monitoring capabilities provided by Internet-connected sensors, human technicians and engineers could find their efficiency vastly enhanced.
It sounds like something from science fiction. But it’s possible today, using Internet of Things (IoT) technology with Unified Communications (UC) and predictive artificial intelligence (AI).
With IoT sensors embedded in a network connected device — whether it’s an elevator, a truck, or an entire factory — machine data can be transmitted directly from the field. AI-based solutions can detect the first signs of stress and predict the time and point of device or equipment failure. The system can then alert those responsible for keeping the devices or equipment running.
Armed with information, technicians can try to fix the problem remotely. If that doesn’t work, an engineer can be dispatched to the field.
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Using AI-based predictive software, an engineer can cross-reference incident data with thousands of similar cases to find the probable cause and the likely best solution. UC technology can help the engineer efficiently troubleshoot the issue directly from the field – retrieving manuals from a cloud-based team workspace, posting incident photos to a team chat room, or launching a video conference to consult with peers. With the problem fixed, the system can automatically send the engineer to the next job.
We call this new way of working, “machine-to-human (M2H) collaboration.” Machines form part of a virtually seamless system, working alongside humans whose capabilities they can augment and expand.
The advantages of M2H collaboration are manifold:
Collaboration between humans and machines likely will not be limited to a single function. It could drive companies to break data out of siloes, creating companywide platforms to act as a “single point of truth” for all the enterprise’s data. Rather than supplanting existing applications, this data-aggregation platform could connect your helpdesk, your CRM, your contact center, and other parts of the business, using a holistic approach to data to help all functions get better results. M2H framework solutions by AT&T combine the company’s strengths across IoT, Unified Communications, and Contact Center solutions. These solutions are standards-based, and device and network agnostic. And AT&T uses a consulting approach to identify the points in the customer’s infrastructure that can benefit from machine-to-human collaboration.
Augmented by machine intelligence and the constant monitoring capabilities provided by Internet-connected sensors, human technicians and engineers could find their efficiency vastly enhanced.
Underpinning this framework is AT&T DataFlow, a managed, cloud-hosted IoT service. AT&T DataFlow helps enterprise customers connect remote devices and collect, transform, and orchestrate their machine data. The data can be integrated with enterprise systems and acted upon by those systems– for example, to automatically trigger alerts, generate trouble tickets, and create team rooms for collaboration.
The future can be built on successful machine-to-human collaboration, with machine learning augmenting and extending human intelligence to help keep complex systems constantly running, with minimum downtime and enhanced cost efficiency.
And for those companies working with the right technology and the right partners, that future has already arrived.
Entirely new experiences, revenues, profitability, customer relationships, business insights, and processes are now possible using IoT services and solutions.
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