Internet of Things (IoT)
What it is and why it matters
The Internet of Things (IoT) refers to a vast number of “things” that are connected to the internet so they can share data with other things – IoT applications, connected devices, industrial machines and more. Internet-connected devices use built-in sensors to collect data and, in some cases, act on it. IoT connected devices and machines can improve how we work and live. Real-world Internet of Things examples range from a smart home that automatically adjusts heating and lighting to a smart factory that monitors industrial machines to look for problems, then automatically adjusts to avoid failures.
History of the Internet of Things
The term “Internet of Things” was coined by entrepreneur Kevin Ashton, one of the founders of the Auto-ID Center at MIT. Ashton was part of a team that discovered how to link objects to the internet through an RFID tag. He first used the phrase “Internet of Things” in a 1999 presentation – and it has stuck around ever since.
Ashton may have been first to use the term Internet of Things, but the concept of connected devices – particularly connected machines – has been around for a long time. For example, machines have been communicating with each other since the first electric telegraphs were developed in the late 1830s. Other technologies that fed into IoT were radio voice transmissions, wireless (Wi-Fi) technologies and supervisory control and data acquisition (SCADA) software. Then in 1982, a modified Coke machine at Carnegie Mellon University became the first connected smart appliance. Using the university’s local ethernet or ARPANET – a precursor to today’s internet – students could find out which drinks were stocked, and whether they were cold.
Today, we’re living in a world where there are more IoT-connected devices than humans. These IoT-connected devices and machines range from wearables like smartwatches to RFID inventory tracking chips. IoT-connected devices communicate via networks or cloud-based platforms connected to the Internet of Things. The real-time insights gleaned from this IoT-collected data fuel digital transformation. In the age of Industry 4.0, the Internet of Things promises many positive changes for health and safety, business operations, industrial performance, and global environmental and humanitarian issues.
The Internet of Things in Today’s World
The Internet of Things has had significant effects on our world. Learn how IoT is affecting our lives today, as the volume and variety of big data streaming from IoT expands and analytics technologies evolve.
Who's Using IoT?
Many industries use IoT to understand consumer needs in real time, become more responsive, improve machine and system quality on the fly, streamline operations and discover innovative ways to operate as part of their digital transformation efforts.
With the Internet of Things (IoT), we can understand the context (the time and place of the customer) to identify when we’re certain the customer needs help or an incentive to purchase, and we can respond proactively. Dan Mitchell Business Director for the Global Retail and CPG Industry Practice SAS
Learn More About Industries Using This Technology
We’re All Connected: IoT, Analytics and AI
Advanced analytics, including artificial intelligence (AI), is the way to harness value from the Internet of Things. Data management, cloud and high-performance computing techniques help manage and analyze the influx of IoT data from Internet of Things sensors. Insights from streaming analytics and AI underpin digital transformation efforts that result in better efficiency, convenience and security. See how connected devices, analytics and AI in the Internet of Things can make our world a better place to live.
How the Internet of Things Works
Being connected through the Internet of Things – to send, receive and often act on data – results in many smart IoT things that we can use to build a more secure, convenient, productive and intelligent world.
Already, Internet of Things capabilities play a significant role in businesses’ digital transformation practices. When we combine IoT data with advanced analytics and AI – leading to the “Artificial Intelligence of Things” – the possibilities seem endless. Learn the basic terms that define the Internet of Things and see how IoT works in the real world.
IoT Market Maturity
Since 2012, major changes in sensors have led to rapid maturing in the Internet of Things market – fueling digital transformation for many businesses:
- Sensors shrank. Technological improvements created microscopic scale sensors, leading to technologies like microelectromechanical systems (MEMS). This made sensors small enough to be embedded into unique places like clothing.
- Communications improved. Wireless internet connectivity and communication technologies have improved, so nearly every type of electronic equipment can provide wireless data connectivity. This allows IoT sensors, embedded in Internet of Things connected devices and machines, to quickly send and receive IoT data over a network.
How IoT Works With Key Technologies
Data management and streaming analytics. The Internet of Things puts high demands on data management for big data streaming from sensors. Event stream processing technology – often called streaming analytics – performs real-time data management and analytics on IoT data to make it more valuable. Key capabilities include filtering, normalization, standardization, transformation, aggregation, correlation and temporal analysis.
Big data analytics. IoT is a major contributor to big data – the massive volume, velocity and variety of structured and unstructured data businesses collect every day. Getting value from big data in IoT requires big data analytics. Related techniques include predictive analytics, text mining, cloud computing, data lakes, data mining and Hadoop. Most organizations use a combination of these techniques to get the most value possible from IoT.
Artificial intelligence. Artificial intelligence can multiply the value of IoT by using all the data from smart connected devices to promote learning and collective intelligence. Some of the core techniques that AI uses are machine learning, deep learning, natural language processing and computer vision.
Click on the infographic to learn more
Recommended reading
-
Article
Modern manufacturing's triple play: Digital twins, analytics & IoT IoT-powered digital twins revolutionize manufacturing with real-time data analysis, predictive maintenance and optimized production. Discover their transformational impact.
-
Article
5 ways to measure beehive health with analytics and hive-streaming dataThis analytical approach to understanding bee hive health can automatically alert beekeepers to changes in hive weights, temperatures, flight activity and more.
-
Series
Meet the data scientist: Daymond LingDaymond Ling believes the right personal traits are more important than technical skills when it comes to being a successful data scientist.