Why the intelligent edge is central to tomorrow’s IoT

Gowri Chindalore of NXP Semiconductors

We’ve all seen the projections about how many devices will soon be connected to the internet of things (IoT), says Gowri Chindalore, head of Strategy, Edge Processing, NXP Semiconductors. IDC, for example, predicted the figure will exceed 41 billion by 2025. Much has been written about the opportunities this will unlock to make our homes, work, play and travel more efficient and sustainable.

But the explosion of data that underpins these advances is causing headaches for those creating products, services and supporting infrastructure. Many early IoT devices rely on the cloud to process the data they collect. This model has been driven in part by the effectively limitless compute capacity in the cloud, coupled with the constrained onboard processing capabilities of many IoT devices.

The limitations of offloading to the cloud

Sending data to and from the cloud has its drawbacks, though. Firstly, transmitting data uses energy and bandwidth. More data means you need more of these costly and finite resources. Secondly, sending data to the cloud introduces latency, which limits the effectiveness of certain applications.

Thirdly, offboarding information introduces privacy and security risks. Data collected by smart home devices, for example, will reveal a lot about when you’re at home and when you’re out. If this information is sent to the cloud, can you be sure it’s done securely? Where is it stored, and in what form? Who has access to it?

Introducing the intelligent edge

As more devices collect more (and more sensitive) data to be processed, the need to address these challenges is becoming increasingly pressing. This is one of the big drivers behind the rise of the ‘intelligent edge’.

In this model, rather than sending all data to the cloud, key processing and decision-making is done close to the connected device – at the local network’s ‘edge’. This reduces the aforementioned latency, energy consumption and bandwidth use, while enabling users to keep private data within the confines of their own infrastructure.

At the heart of the intelligent edge is machine learning. Currently in this context, we’re talking primarily about inference. This is where the edge device uses a pre-trained machine learning model to make a decision based on new data being collected by local sensors.

A screenshot of a cell phone  Description automatically generated

Figure 1: Researchers at ABI predict that shipments of devices capable of onboard AI inference is expected to reach two billion by 2024. (Source ABI; image courtesy of NXP Semiconductors)

Driving the shift to AI at the edge

The significant growth of inference in such resource-constrained environments is made possible by improvements to inference processing, and specifically the technologies used to accelerate it.

The first generation of machine learning accelerators – if they were accelerators at all – were largely software-based, with a CPU running an instruction set. The second generation introduced dedicated hardware, such as GPUs and DSPs. Today, we have the third generation, which uses features such as hardware-based pruning and compression. The more of this that gets done in the hardware, the more energy-efficient the process becomes, since you reduce the use of software and CPU cycles.

A screenshot of a cell phone  Description automatically generated

Figure 2: Energy efficiency improvements are seen with machine learning accelerators. (Source: NXP Semiconductors)

What today’s intelligent edge can enable

As humans, much of our communication is delivered using more than just words: our tone, facial expressions and hand gestures all contribute to the way we instinctively communicate and understand one another. Using edge-based inference, today’s designers can enable their products to pick up on these signals, thereby crafting increasingly natural-feeling interaction experiences. Techniques can include facial and other object- and gesture-recognition, voice-recognition, tonal analysis and natural language processing.

Elsewhere, intelligent edge devices can enhance safety. For example, smart home edge kit could be trained to recognise danger signals, such as alarms going off, a person’s fall, glass breaking or a tap left dripping or running. On sensing the problem, the system could then alert the owner, enabling them to react accordingly.

What comes next?

The next few years will likely see many new IoT products and services coming to market that leverage this increasingly capable intelligent edge.

We talked about how we’re currently at the third generation of AI-acceleration capabilities. Future generations could include neuromorphic or in-memory computing, spiking neural networks or, eventually, quantum AI. These developments will help accelerate another trend that’s currently emerging, which is the ability to implement the actual training of machine learning algorithms at the edge.

It promises to be an exciting time for designers, engineers, businesses and consumers alike, with our technology becoming more helpful, more secure and more sustainable.

The author is Gowri Chindalore, head of Strategy, Edge Processing, NXP Semiconductors.

Comment on this article below or via Twitter: @IoTNow_OR @jcIoTnow

RECENT ARTICLES

Panasonic and Jasmy unveil Web3 Platform for IoT data control

Posted on: March 28, 2024

Panasonic has joined forces with Jasmy (JASMY) blockchain to introduce a Web3 platform that will facilitate the connection of personal data on the Internet of Things (IoT). The collaboration between the Japanese-based blockchain and Panasonic Advanced Technology was initiated in February, but the official announcement was made on March 26.

Read more

Driving connected personalised user experiences with Generative AI

Posted on: March 27, 2024

As the world continues to rapidly move towards digitalisation, customer expectations are also on the rise. Around the globe, telcos are grappling with meeting these expectations. As well as ensuring connectivity in a secure, seamless, and consistent manner 24/7, to compete and differentiate, operators now need to provide personalised experiences that are as unique as

Read more
FEATURED IoT STORIES

What is IoT? A Beginner’s Guide

Posted on: April 5, 2023

What is IoT? IoT, or the Internet of Things, refers to the connection of everyday objects, or “things,” to the internet, allowing them to collect, transmit, and share data. This interconnected network of devices transforms previously “dumb” objects, such as toasters or security cameras, into smart devices that can interact with each other and their

Read more

The IoT Adoption Boom – Everything You Need to Know

Posted on: September 28, 2022

In an age when we seem to go through technology boom after technology boom, it’s hard to imagine one sticking out. However, IoT adoption, or the Internet of Things adoption, is leading the charge to dominate the next decade’s discussion around business IT. Below, we’ll discuss the current boom, what’s driving it, where it’s going,

Read more

9 IoT applications that will change everything

Posted on: September 1, 2021

Whether you are a future-minded CEO, tech-driven CEO or IT leader, you’ve come across the term IoT before. It’s often used alongside superlatives regarding how it will revolutionize the way you work, play, and live. But is it just another buzzword, or is it the as-promised technological holy grail? The truth is that Internet of

Read more

Which IoT Platform 2021? IoT Now Enterprise Buyers’ Guide

Posted on: August 30, 2021

There are several different parts in a complete IoT solution, all of which must work together to get the result needed, write IoT Now Enterprise Buyers’ Guide – Which IoT Platform 2021? authors Robin Duke-Woolley, the CEO and Bill Ingle, a senior analyst, at Beecham Research. Figure 1 shows these parts and, although not all

Read more

CAT-M1 vs NB-IoT – examining the real differences

Posted on: June 21, 2021

As industry players look to provide the next generation of IoT connectivity, two different standards have emerged under release 13 of 3GPP – CAT-M1 and NB-IoT.

Read more

IoT and home automation: What does the future hold?

Posted on: June 10, 2020

Once a dream, home automation using iot is slowly but steadily becoming a part of daily lives around the world. In fact, it is believed that the global market for smart home automation will reach $40 billion by 2020.

Read more

5 challenges still facing the Internet of Things

Posted on: June 3, 2020

The Internet of Things (IoT) has quickly become a huge part of how people live, communicate and do business. All around the world, web-enabled devices are turning our world into a more switched-on place to live.

Read more