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. 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.
Non-Geek’s A-to-Z Guide to the Internet of Things
Learn what all those techy words and acronyms mean in this go-to resource that defines 101 IoT terms.
Understanding Data Streams in IoT
Read how event stream processing technology identifies patterns in data streams as events happen – so you can use real-time, streaming data from IoT to make fact-based, automated decisions.
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.
Retail
IoT unites data, analytics and marketing processes across locations. Retailers capture IoT data from in-store and digital channels and apply analytics (including artificial intelligence, or AI) for real-time, contextual listening and to understand behavior patterns and preferences. They often use IoT connected devices like RFID inventory tracking chips, cellular and Wi-Fi systems, beacons and smart shelves in their Internet of Things strategy.
Manufacturing
IoT connects all phases of the Industrial Internet of Things (IIoT) process – from supply chain to delivery – for a cohesive view of production, process and product data. Advanced IoT sensors in factory machines or warehouse shelves, along with big data analytics and predictive modeling, can prevent defects and downtime, maximize equipment performance, cut warranty costs, boost production yield and enhance the customer experience.
Health Care
IoT technology captures data streaming in real time from the Internet of Medical Things (IoMT) – such as wearables and other medical connected devices that monitor exercise, sleep and other health habits. This IoT data enables precise diagnoses and treatment plans, improves patient safety and outcomes, and streamlines care delivery.
Transportation and Logistics
IoT with geofence-enabled location intelligence and AI, deployed across the value chain, can deliver greater efficiency and reliability for transportation and logistics companies. This technology can improve service quality, reduce downtime and boost customer satisfaction. It can also enhance safety and reduce costs by managing, tracking and monitoring connected vehicles, freight and other mobile assets in real time.
Government
IoT applications are used to address many real-world issues – traffic congestion, city services, economic development, citizen engagement, and public safety and security. Smart cities often embed IoT sensors into the physical infrastructure, such as streetlights, water meters and traffic signals.
Energy
The Internet of Things helps providers deliver reliable, fair-priced services and products. IoT connected devices and machines predict problems before they occur. Distributed grid resources like solar and wind are integrated through IoT. And behavior data – such as that collected from smart homes – improves convenience and security, and informs development of customized services.
Learn More About Industries Using This Technology
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
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 efforts. 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 mining, data lakes 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
Next Steps
Dig deeper as you get started with the Internet of Things – from setting strategy to measuring IoT success.
SAS® Analytics for IoT
From the time you first access Internet of Things data to when you deploy models and trigger alerts, SAS Analytics for IoT helps you get more value from your enterprise IoT investments. Learn more about SAS Analytics for IoT or request a demo now.
Recommended Reading
-
Article
Edge computingWith traditional methods, data is captured, stored and analyzed later – limiting how quickly businesses can act on insights from the data. With edge computing, IoT data is processed at the edge of a network – right where it’s created or collected – avoiding delays and enabling real-time processing and action.
-
Article
IoT: The customer experience accelerator you can't afford to ignoreIoT represents a powerful source of data that, when combined with analytics, can yield insights on everything from behavior to emotions to health. And that's why it's key to improving customer experience.
-
Article
How to drill a better hole with analyticsFrom drilling holes to preventing health care fraud, learn about some of the new technologies SAS has patented with IoT and machine learning technologies.