IBM, AT&T Partner to Bring IoT Tools to Developers

By Darryl K. Taft  |  Posted 2016-07-14 Print this article Print
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IBM and AT&T have teamed up to deliver open-source tools and services to developers working on Internet of things applications using the IBM Cloud.

IBM and AT&T have expanded their relationship to further empower developers to create Internet of things applications.

The two companies are pooling their resources, bringing IBM's cognitive computing technologies together with AT&T's connectivity capabilities to help developers build IoT solutions on the IBM Cloud using open-source tools as well as proprietary offerings.

IBM and AT&T will provide open-source IoT tools such as IBM's Node-RED and open standards such as MQTT. Node-RED is a visual tool for wiring IoT. Built by IBM Emerging Technologies, Node-RED is a tool for wiring together hardware devices, APIs and online services for IoT application development.

MQTT, formerly known as the Message Queuing Telemetry Transport protocol, is a machine-to-machine (M2M) protocol for IoT connectivity. It was designed as a lightweight publish/subscribe messaging transport and is useful for connecting with remote locations where a small code footprint is required and network bandwidth is at a premium. MQTT is a key component of the Eclipse Paho open-source IoT project.

IBM noted that according to the VisionMobile "2016 Internet of Things Megatrends" report, the number of IoT developers will rise to 10 million by 2020—growing 100 percent over the 5 million IoT developers around today.

"We have heard the call from developers and businesses for more tools to make IoT a reality and together with AT&T, we are bringing together powerful platforms and services to drive collaborative innovation," said Harriet Green, general manager of IBM Watson IoT, Commerce & Education, in a statement.

Green added that this collaboration enables individual developers to tap the power of cognitive computing and combine it with massive amounts of data streaming from billions of connected devices, sensors and systems.

"Both companies bring a wealth of open-source and open-standards assets and experience to the fore," said Charles King, principal analyst at Pund-IT.

In addition, IBM will bring its Watson capabilities to bear, while AT&T will provide access to its IoT platforms Flow Designer and M2X, as well as AT&T Control Center and access to the AT&T network.

"IBM's Watson cognitive solutions and AT&T's global network, along with its Flow Designer and MX2 platforms, will provide powerful assets for IoT projects," King said. "In combination, that should provide a powerful attractant to the developers that IBM and ATT are targeting with their collaborative effort."

Meanwhile, AT&T also is working with IBM on a new IoT starter kit for developers. Eventually, developers will gain access to an integrated toolkit of AT&T and IBM technologies to more easily build IoT apps.

Yet, for now developers can use the AT&T tools along with the IBM Watson IoT Platform, IBM's Bluemix cloud environment, IBM's OpenWhisk serverless computing APIs, Watson APIs and other IBM services to build IoT applications.

"From farming to fleets, there are many companies that would benefit from real, actionable IoT data," said Chris Penrose, senior vice president of AT&T IoT Solutions, in a statement. "Combining technologies with IBM can advance the developer experience, so they can build comprehensive IoT solutions for businesses."

The newly announced IoT partnership between IBM and AT&T comes two years after an earlier partnership around creating IoT applications for smarter cities.

In 2014, IBM and AT&T pledged to combine their analytic platforms, cloud and security technologies to help organizations gain more insights on data collected from machines in a variety of industries.

That AT&T and IBM alliance focused on creating new solutions targeted for city governments and midsize utilities, said Michael Curry, vice president of WebSphere product management at IBM. The companies empowered organizations to integrate and analyze vast quantities of data from assets such as mass transit vehicles, utility meters and video cameras. This information enabled cities to be able to better evaluate patterns and trends to improve urban planning and utilities to better manage their equipment to reduce costs.


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