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Cisco Internet of Things: Applications in Manufacturing
BERND HEINRICHS | March 1, 2016
The development of Tencent and its products and services has profoundly influenced the way millions of Internet users communicate with one another socially and will continue to do so in the future.
Article | March 3, 2020
By the end of this year there will be 5.8 billion Internet of Things (IoT) endpoints, according to Gartner. And depending on how IoT devices are counted the number is even higher. Statista, for example, estimates the device count for 2020 to be more than 30 billion. Security remains a big challenge for IoT as a strategy to be successful. IoT devices are still not being designed with security as a top priority.Mary O’Neill, VP of security at Nokia, noted in a press conference at MWC Los Angeles 2019 and reported by SDXCentral, that “if an IoT device today is plugged into the network and it doesn’t have protection on it, it’s infected in three minutes or less.”Jake Williams, founder of the security firm Rendition Infosec, said that “IoT vendors emphasize, often rightly, that their products improve quality of life, but they often neglect to disclose the risk of these devices to consumers. The onus of understanding how an IoT device might impact security should not be purely on the consumer. The vendor shares this responsibility.
IoT is huge, but AI has the potential to supercharge the technology even more. Gartner predicts that this year 80 percent of all enterprise IoT projects will include AI. One area where many have been critical of IoT is a lack of good security. When coupled with AI, that could be improved, but some worry that AI can also be used as a tool to defeat IoT security. Dean Chester, cybersecurity author, wrote that “AI can be used for IoT security, or it can be used against it.”Melvin Greer, Chief Data Scientist, Intel Americas , said that “AI and IoT are no longer in separate swim lanes. AI closes the loop in an IoT environment where IoT devices gather or create data, and AI helps automate important choices and actions based on that data. Today, most organizations using IoT are only at the first ‘visibility’ phase where they can start to see what’s going on through IoT assets. But they’re moving toward the reliability, efficiency and production phases, which are more sophisticated and require stronger AI capabilities.
ABI Research says cloud vendors are investing in the data and analytics services space as they attempt to get on board the IoT value chain. The researcher forecasts that cloud suppliers will grow their share of IoT data and analytics management revenues from US$6 billion in 2019 to US$56 billion in 2026. Cloud vendor’s revenues come primarily from streaming, storage, and the orchestration of data. Analytics services across cloud vendors, on the other hand, are less differentiated, as reflected in pre-built templates such as AWS Sagemaker and Microsoft Azure Notebooks which leverage the open source Jupyter project. Considering that many cloud vendors are in the early stages of analytics investment, cloud vendors are relying on their partners for addressing more specific advanced analytics and vertical market needs.
Perhaps no more than a decade ago, the notion of ‘smart cities’ probably implied thoughts of which metropolitan areas could be said to have the greatest density of schools, colleges and universities. You want a smart city? Okay, how about Oxford, Cambridge, Massachusetts, Washington DC, Paris and so on. But that’s (obviously) not what we mean by smart cities today. In this post-millennial age, we define a smart city is a municipality that uses information and communication technologies (many of which will gravitate towards the Internet of Things (IoT) and the data backbones that serve it with application processing, data analytics and increasing amounts of AI) to increase operational efficiency, share information with the public and improve both the quality of government services and citizen welfare.
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