Internet of Things and Bayesian Networks

@machinelearnbot

As big data becomes more of cliche with every passing day, do you feel Internet of Things is the next marketing buzzword to grapple our lives. So what exactly is Internet of Thing (IoT) and why are we going to hear more about it in the coming days. Internet of thing (IoT) today denotes advanced connectivity of devices,systems and services that goes beyond machine to machine communications and covers a wide variety of domains and applications specifically in the manufacturing and power, oil and gas utilities. An application in IoT can be an automobile that has built in sensors to alert the driver when the tyre pressure is low. Built-in sensors on equipment's present in the power plant which transmit real time data and thereby enable to better transmission planning,load balancing.


The #IoT and #Analytics @ThingsExpo #BigData #BI #AI #DX #MachineLearning

@machinelearnbot

The Internet of Things (IoT) promises to change everything by enabling "smart" environments (homes, cities, hospitals, schools, stores, etc.) and smart products (cars, trucks, airplanes, trains, wind turbines, lawnmowers, etc.). I recently wrote about the importance of moving beyond "connected" to "smart" in a blog titled "Internet of Things: Connected Does Not Equal Smart". The article discusses the importance of moving beyond just collecting the data, to transitioning to leveraging this new wealth of IoT data to improve the decisions that these smart environments and products need to make: to help these environments and products to self-monitor, self-diagnose and eventually, self-direct. But one of the key concepts in enabling this transition from connected to smart is the ability to perform "analytics at the edge." Shawn Rogers, Chief Research Officer at Dell Statistica, had the following quote in an article in Information Management titled "Will the Citizen Data Scientist Inherit the World?": "Organizations are fast coming to the realization that IoT implementations are only going to become more vast and more pervasive, and that as that happens, the traditional analytic model of pulling all data in to a centralized source such as a data warehouse or analytic sandbox is going to make less and less sense.


The #IoT and #Analytics @ThingsExpo #BigData #BI #AI #DX #MachineLearning

@machinelearnbot

The Internet of Things (IoT) promises to change everything by enabling "smart" environments (homes, cities, hospitals, schools, stores, etc.) and smart products (cars, trucks, airplanes, trains, wind turbines, lawnmowers, etc.). I recently wrote about the importance of moving beyond "connected" to "smart" in a blog titled "Internet of Things: Connected Does Not Equal Smart". The article discusses the importance of moving beyond just collecting the data, to transitioning to leveraging this new wealth of IoT data to improve the decisions that these smart environments and products need to make: to help these environments and products to self-monitor, self-diagnose and eventually, self-direct. But one of the key concepts in enabling this transition from connected to smart is the ability to perform "analytics at the edge." Shawn Rogers, Chief Research Officer at Dell Statistica, had the following quote in an article in Information Management titled "Will the Citizen Data Scientist Inherit the World?": "Organizations are fast coming to the realization that IoT implementations are only going to become more vast and more pervasive, and that as that happens, the traditional analytic model of pulling all data in to a centralized source such as a data warehouse or analytic sandbox is going to make less and less sense.


Why AI Would Be Nothing Without Big Data - TARC Business Review

#artificialintelligence

Via Forbes: Artificial Intelligence (AI) is one of the most transformative forces of our times. While there may be debate whether AI will transform our world in good or evil ways, something we can all agree on is that AI would be nothing without big data. Even though AI technologies have existed for several decades, it's the explosion of data--the raw material of AI--that has allowed it to advance at incredible speeds. It's the billions of searches done every day on Google that provide a sizable real-time data set for Google to learn from our typos and search preferences. Siri and Cortana would have only a rudimentary understanding of our requests without the billions of hours of spoken word now digitally available that helped them learn our language.


How smart buildings can use big data to shape the future of work

#artificialintelligence

For most organisations, the two largest investments are people and premises. So, when organisations redefine the relationship between their employees and their property, it's no surprise that efficiency and effectiveness gains can have an extraordinary impact on workforce productivity and wellbeing – and ultimately, the bottom line. It's this catalyst for change and the benefits that derive from it that has me as a business leader excited about smart buildings and smart workspaces. The opportunity is so much bigger than the often-promoted gains in energy and carbon reduction. See also: Do smart offices attract smart employees?