Examples of using Iot data in English and their translations into Vietnamese
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By 2023, the purchase and sale of IoT data will become an essential part of many IoT systems.
By 2018, these companies will be hosting 40% of their IoT data on someone else's cloud.
AWS IoT Analytics, for example, makes it easy to run sophisticated analytics on massive volumes of IoT data.
By 2023, buying and selling IoT data will become an essential part of many intelligent and connected systems.
Web content and online ads can be customized to a deeper extent using the troves of new IoT data.
monitor and analyze IoT data from sensors and other devices.
Ethernet-based wireless IoT device, integrated with IoT data acquisition, processing, and publishing functions.
RFID is one of the primary sources of IoT data, which means ensuring its security is of the utmost importance.
fleet applications, this IoT data platform provides assistance with energy monitoring, asset utilization, and vehicle tracking.
monitor and analyze IoT data from sensors and different gadgets.
fog computing are strongly on the rise for the same exact reasons: an IoT data deluge.
automatic building doors, is using the IBM platform to analyze IoT data.
In communications companies, the most prevalent IoT data sources include audio devices(45%), followed by mobile phones(42%).
CDN, IoT data sharing, storage and more.
This demands data-driven systems that combine management and IoT data to help authorities manage the city and enable the physical and digital worlds to be integrated.
One of the key pillars of a robust IoT data platform is Apache Kafka,
While 60% of executives that McKinsey surveyed said that IoT data yielded significant insights, 54% admitted that they used less than 10% of that IoT information3.
Makers of industrial machinery or auto manufacturers, for example, can create new business models by applying IoT data and solutions to offer their products as a service.
This year, we expect to see businesses in Asia Pacific starting to increasingly use IoT applications that are capable of delivering IoT data for use across the enterprise.
It is the easiest way to run analytics on IoT data and get insights to make better and more accurate decisions for IoT applications