IBM announced the opening of its world headquarters to Watson Internet of Things (IoT), located in Munich, in Germany. At the same time, IBM has launched a series of new IoT offerings, capabilities and ecosystem partners to extend the power of cognitive computing billions of connected devices, sensors and systems that make up the IoT
Munich, Germany is the world headquarters for the new unit IoT Watson of IBM and its first European center of innovation Watson. It represents larger investment of IBM in Europe for more than two decades . The campus environment will bring together 1,000 IBM developers, consultants, researchers and designers to drive deeper engagement with customers and partners. The IoT IBM headquarters will serve as an innovation laboratory for data scientists, engineers and programmers to build a new class of connected solutions at the intersection of cognitive computing and the Internet of Things.
"The Internet of Things will soon be the largest single source of data on the planet, but nearly 0 percent of these data is never done," said Harriet Green, CEO Watson IoT and education . "with its unique capabilities to sense, reason and learn, Watson opens the door for companies, governments and individuals to finally use this data in real time, the compare with historical data sets and deep reservoirs of accumulated knowledge and find unexpected correlations generate new ideas to take advantage of business and as well the society. "
customer Experience IBM Watson IoT
IBM also announced its plans to offer APIs Watson and services over the IoT platform Watson Cloud to accelerate the development of solutions and cognitive IoT services to help customers and partners understand the increasing volume and variety of data in a physical world that is becoming digitized.
With these moves, customers, start-ups, universities and an ecosystem of partners IoT - silicon manufacturers and solution-oriented industry suppliers - will open direct access, based on cloud IoT platform IBM to test, develop and create the next generation cognitive IoT applications, services and solutions.
IBM also announced that it has opened eight new IBM Watson IoT Experience Customer Centres across Asia, Europe and the Americas. Locations include Beijing, China; Boeblingen, Germany; São Paulo, Brazil; Seoul, Korea; Tokyo, Japan; and Massachusetts, North Carolina, and Texas in the United States.
The customer experience centers IoT provide customers and partners with access to technology, tools and talent to develop and create new products and services with the help of intelligence cognitive provided by IBM Watson IoT cloud Platform.
New API Watson IoT cloud services
new APIs and cloud services Watson Watson IoT Platform are established to accelerate the development of cognitive IoT solutions and services . four new IBM IoT API services include:
- The Natural Language Processing (NLP) API Family allow users to interact with systems and devices using simple language , human. Natural Language Processing solutions help understand the intent of human language by correlating with other data sources to provide context in specific situations. For example, a technician working on a machine may notice an unusual vibration. He can ask the system "What is the cause that vibration?" Using the data of NLP and other sensors, the system will automatically connect words to meaning and intent to determine the machine that it refers, and correlate recent interview to identify the most likely source of the vibration and recommend measures to reduce it.
- the Machine Learning Watson API Family would automate the processing of data and continuously monitor the new data and user interactions to classify data and results based on learned priorities. machine Learning can be applied to all data from devices and sensors to automatically understand the current conditions, this is normal, expected trends, the properties to be monitored, and suggested actions when a problem arises. for example, the platform can monitor incoming data equipment fleet to learn normal and abnormal conditions, including environmental and production processes, which are often specific to each piece of equipment. Machine Learning helps to understand these differences and configures the system to monitor the unique conditions of each asset.
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The Video and Image Analytics API Family allow monitoring of unstructured from the video stream data and image snapshots to identify scenes and patterns. This knowledge can be combined with data from the machine to get a better understanding of past events and emerging situations. For example, security cameras and video surveillance analysis can note the presence of a forklift infringing on a small area, creating a small alert in the system; three days later, an asset in this area begins to show decreased performance. Both incidents can be correlated to identify a collision between the truck and assets that could not have been easily video or data of the machine.
- The Text Analytics API Family is allow extraction of unstructured text data, including transcripts of customer call centers, the technician logs maintenance, blog comments, and tweets to find correlations and patterns in these vast amounts of data. For example, phrases reported by unstructured way - as "my brakes make a sound," "my car seems to slow down to stop," and "the pedal feels spongy" - can be linked and correlated to identify field problems potential in a particular brand and model of car.
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