Living on the edge—or should we say, at the edge via fog or edge computing—is becoming an increasingly popular business model. Edge computing, i.e., embedding computing infrastructure near the end devices, along the “edges” of a network, often to accelerate time-to-insight and reduce costs, can solve a real need for IoT (Internet of Things) applications that require very fast response times. It can also create opportunities for autonomous edge operation, which can benefit from ultra-fast AI (artificial intelligence) data-processing technology. But is AI too power-hungry and expensive to operate at the edge?
Orphan devices and solutions in the fast pace world of the IoT (Internet of Things): Have you really given much thought to this topic? For the purposes of this column, when it comes to orphan technology, I am basically going to address devices, platforms, and solutions that have been abandoned by their original developers for one reason or another.
When we talk about the IoT (Internet of Things), we talk a lot about growth, growth, growth. That’s because no matter how much we all want to avoid hype, there are just so many areas of opportunity for the IoT, and it’s hard not to talk about the possibilities. A quick Google search on the IoT will tell you things like: We can expect 12.86 billion IoT sensors and devices to be in use by 2020 in the consumer sector alone, and vertical-specific sensors and devices will exceed 3 billion by 2020.
IoT. This three-letter acronym has been gaining in importance to businesses each and every day. Its ability to capture and manage data is being referred to as the new oil and it’s spilling into every industry.
IoT (Internet of Things), AI (artificial intelligence), and ML (machine learning). All of these words are changing every industry at a very rapid clip. If you read this column a few weeks ago, you learned that machine learning is an application of artificial intelligence, in which computer systems “learn” by making data-driven decisions.
When a company’s all-in with the IoT (Internet of Things), it may seem like it has a one-track mind: all IoT, all the time. This week, AT&T has been that company, announcing several different ways it’s moving forward on IoT initiatives, ranging from connected-device cybersecurity to energy and building management solutions, global enterprise Wi-Fi, and beyond. As a key player in the space, AT&T’s latest moves—making new ecosystem partnerships and expanding various IoT-related programs—advance IoT innovation and adoption in the industry as a whole.
Is American manufacturing declining? A new survey from Leading2Lean suggests a majority of Americans believe yes, it’s declining; but perhaps it is wrong. The IoT (Internet of Things) is certainly changing the face of manufacturing in America and outside of it, but it’s also opening doors to new efficiencies that can lead to higher profit margins and the ability to offer personalization, among other benefits. The next generation of Industry 4.0 leaders will need a new set of skills to maximize the value IoT technologies offer manufacturing and other industrial sectors.
Imagine a marine company saving almost a half-million dollars in fuel per vessel annually by leveraging AI (artificial intelligence); consider the effect a savings of $1.5 million per ship could have on a cruise line operator thanks to reduced fuel consumption, and ponder the impact data and AI-enabled decisionmaking could have on a tugboat operator looking to catch engine, fuel pump, and other equipment issues before they affect performance. Two companies will integrate their IoT (Internet of Things) offerings to enable more success stories like these early, real-life wins.
The use of IoT (Internet of Things) technologies in the enterprise realm is growing by leaps and bounds, and this growth has caught the eye of cybercriminals looking to exploit vulnerabilities in connected devices and systems for their own gain. As the IoT becomes more of a focus for cybercriminals, cybersecurity must simultaneously become more of a focus for the businesses using IoT solutions.
Artificial intelligence and machine learning are having a considerable impact on the changing tide in manufacturing. The change is so impressive it is actually playing a role in many industries. Its impact is so impressive that for this column I am going to dig into the difference between AI (artificial intelligence) and machine learning.
What factors are most critical when selecting a service or product? Trust is one of the most important in building a brand, according to a recent survey that reveals how well four cell service brands connect with their customer base.
This week has us all taking a moment to pause and remember the deadly attacks that brought America to its knees. Al-Qaeda terrorists hijacked four planes carrying innocent passengers, and two of them were flown into the two towers of the World Trade Center in New York, which toppled to the ground, leaving devastation in their wake.
Some really exciting IoT (Internet of Things)-enabled solutions are helping governments, communities, individuals, and organizations address some really tough global issues, such as how best to provide humanitarian disaster relief in times of crisis.
Security is such a huge consideration for any business undergoing a digital transformation, and this is true for manufacturers that are automating their factories. The threat of hacks and breaches is real, but it’s not a good enough reason to not invest in the IoT (Internet of Things).
Safety and interoperability are key components of the next generation of transportation, which will feature autonomous capabilities that rely on sensors and other smart devices to connect vehicles to each other and to the surrounding infrastructure.