Evolution of IOT Devices
Early IOT devices were typically based on quite simple architectures. Typically, they would incorporate a simple microprocessor, a sometimes separate radio chip (often Bluetooth Low Energy), and some sensors; their only function would be to gather some data and transmit it onwards to other systems. Since then, IOT devices have developed enormously in terms of performance, features and sophistication. This article looks at these trends and what the future holds.
First wave IOT devices were often doing little more than replacing a cable, or enabling functions such as configuration and setup to be done on a tablet or phone. There was a lot of value gained by linking systems that had previously been isolated, or by the simplicity of replacing a wired architecture with a wireless one. The IOT devices did little more than read data in, and transmit it onwards somewhere else. The focus, particularly for Bluetooth Low Energy devices, was minimising power consumption to allow extended lifetimes when powered by a battery.
Onboard microprocessors
Quite early on, chipsets with integrated radios and microprocessors became the norm. However, there is a night and day difference between the processors in early devices and those of the latest generation devices. Typically based on ARM cores, early devices would have the most basic M0 core running at perhaps 16MHz. The state of the art today has M33 core devices running at up to 320MHz – a 20x speed increase in little over a decade. This has been achieved without increasing power consumption, and indeed reducing it in some cases.
The most advanced devices offer multicore processors, typically independent network and application processors, which allows real time response to inputs without interfering with over the air communications. Often this has allowed end device manufacturers to dispense with additional microprocessors even for more sophisticated applications.
Security “built in” not “added on”.
Security in early IOT devices was typically weak, with encryption of over the air traffic being about the limit of what was offered. This is no longer acceptable, as IOT systems become ever more connected and integrated into mission critical applications. Secure microprocessors, incorporating cores such as ARM Trustzone, and secure key storage for end-to-end authentication and encryption are becoming standard. The European Cyber Resilience Act is making much of this obligatory, but even in other regions, the reputational risk of insecure systems is driving an increased focus on cyber security.
The majority of IOT systems will incorporate over the air update capabilities to fix security flaws as well as provide feature updates, just as phones, tablets and PCs already do. However, these require strong authentication and encryption processes to be helpful, otherwise they could cause more harm than good. In addition to secure software, physical tamper resistance is also likely to become standard in the future.
Rich Peripheral Sets
A further development has been the range of peripheral connections supported by modern devices. Early devices were largely focused on reading sensors, via fairly simple connections such as SPI and I2C. The next generation offers a much broader range of options, including ethernet drivers, CAN buses, high speed USB, dedicated audio drivers and more. In addition, some devices offer separate programable peripheral cores to allow users to develop their own drivers without impacting the main application processor.
AI at the edge
The concept of AI functionality on a small battery powered device may seem strange, given the typical image of AI as something delivered by vast server farms. However, small AI inference engines are appearing on IOT devices. The idea is not to run a Large Language Model (LLM) general purpose AI, which would be unfeasible. Rather, the concept is to run an inference engine, targeted at a limited problem domain, using an AI model trained on some larger system. Potential applications could be simple speech recognition, face detection, or intelligent presence detection.
The aim of such systems is to achieve more efficient processing than conventional manually created logic, and thus reduce power, enable new applications, or perhaps reduce the complexity of sensors systems. AI enhanced edge computing can also reduce network traffic by locally analysing and summarising data, and provide a low latency response locally.
Such an application of AI may turn out to be more immediately useful and profitable than the grand vision of general intelligence via LLMs, which comes with major issues of cost and resource consumption. The viability of huge LLM based systems is still in the balance today, in terms of the potential revenues justifiing the capital outlay.
Multi-radio, Multi-protocol
Early IOT devices were typically focused on a single task, such as offering a BLE radio, together with a protocol stack offering profiles defined in the Bluetooth specification. They were generally deployed in bespoke closed solutions.
The growing trend is for multiprotocol devices, that offer support for multiple standards – for instance BLE and Thread, or Zigbee. This can allow a device to work in different types of network. The 2.4 GHz radio band has many different types of radio operating in it, and a device might offer any or all of BLE, Wi-Fi, Thread, Zigbee and ANT+. However other open bands such as the 925/868 MHz sub-Giga band also have multiple radio protocols defined, and there are devices that support multiple standards.
Application Level Protocols
One driver for multiprotocol devices is to create products that support open standards, such as Matter, Apple HomeKit, Google Home, or Amazon’s Sidewalk. These protocols allow devices to interact with third-party systems, with independent interoperability testing available to give confidence to consumers that their products will work seamlessly together.
In the professional sphere, there are standards for applications such as lighting, with DALI+ being one example.
The cost of supporting these more complex and adaptable solutions is that devices need more non-volatile memory and RAM to support the protocol stacks required. IOT devices have had to grow in capacity to match these requirements.
What next?
Looking forward, all of these trends look set to continue. Devices will continue to add more computing power, more memory, and diverse and adaptable peripheral systems. Multi-core devices may become the norm, with dedicated processors for different functions such as radio, applications, security, peripherals and advanced AI functions. Security will be an ongoing battle between IOT system designers and malevolent actors. Security functions will become of increasing importance as IOT systems become more integrated and mission critical. Physical tamper protection features will be required and may also become standard.
Conclusions
In the decade or so that IOT has existed as a concept, devices have come a long way. From simple Bluetooth radios, IOT devices are becoming closer to being “mini-computers” offering a wide variety of functions and autonomous operation. This offers both opportunity and challenge for system designers, to make good use of the capabilities on offer whilst maintaining a coherent overall system structure at acceptable cost levels.
For examples of Multi-radio processors, see ISP5261-WX - Wi-Fi 6 and Bluetooth Low Energy Module, LoRa Modules for Low Power Wide Area Network and ISP3080 Series – Combo UWB and BLE module with antennas
For examples of modules with high computing power and/or dual cores see ISP2654, ISP2053 series - Dual-core Bluetooth Low Energy 5.3 Modules, ISP5261-WX - Wi-Fi 6 and Bluetooth Low Energy Module
This article first appeared in the March edition of "Components in Electronics, and can be seen here Components in Electronics March 2026 - Evolution of IOT Devices
