The internet of things (IoT) has transformed the way we interact with technology, enabling seamless connectivity and smart automation across industries. And growth of IoT isn’t slowing down anytime soon – according to a report by Grand View Research, the global IoT device management market size was valued at $1.88 billion in 2022 and is expected to register a CAGR of 34.9% from 2023 to 2030.
The Biggest Challenge in IoT Software Development
The biggest challenge in software development for IoT is that the software platform is often secondary to the hardware. Many IoT companies are hardware-centric, which leads to taking shortcuts in the software engineering process.
For an IoT firm, the biggest valuation component, when they ultimately sell, is in their platform and not in the hardware. The hardware will get commoditized. But the software platform is the real differentiator. To make the product excel as an IoT solution, both the software and hardware must be crafted with care.
Another large risk in IoT development is not investing in the software engineering platform. You need to manage, control, and communicate with all your products. Once you get a few thousand devices out in the field, you can quickly run into a situation where you roll out an update that “bricks” thousands of devices – turns them off, makes them sub-functional, or non-functional.
If this happens, you are looking at sending technicians out to thousands of customers, or issuing thousands of RMAs. Regardless, this is a literal killer for companies, especially IoT firms in their early stages.
How to Fix The Problem
These problems can be fixed by simply taking the process seriously. Find a software platform partner with experience in the IoT space. Just bringing on software developers at the cheapest rates is a terrible idea for IoT.
IoT software has to be engineered, not developed, and should be approached with care and entrusted to individuals with the experience to get IoT solutions built right, built fast, and built to last.
What Are the Key Features to Look For in an IoT Platform?
- Operate at Scale. IoT platforms need to be efficient enough to scale up to handle hundreds of thousands of devices.
- Ease the Management of Devices. IoT software platforms must ease the management of fleets of devices out in the field in a few key ways:
- Provide real time feedback on device performance.
- Safely manage over-the-air (OTA) firmware updates to devices.
- Centrally manage the configuration and operation of all the devices.
IoT Software Development Security Concerns
In a 451 Research survey of IT decision-makers, 55% of respondents ranked IoT security as a top priority when asked to rank which technologies or processes their organizations considered for current or planned IoT initiatives.
The largest security concern in IoT development comes from the connection of the IoT devices to the central platform. This is due to the scale of IoT and the inherently unreliable state of network connectivity between IoT devices and the platforms with which they communicate.
Security has to be addressed at multiple levels, and developers must consider:
- Everything down to the use of TLS (transport layer security) for transport encryption, and communication protocols the devices use.
- Unique, rotating authorization keys that are exchanged between the device and platform.
- The security of the platform itself.
Remember, if the platform is compromised, that could compromise thousands of devices out in the field. The importance of security is significantly heightened with IoT platforms because of their connectivity and scale.
One of the most secure ways to connect to the IoT platform is to only have device-initiated connectivity, through HTTP/S or communication protocols like MQTT (message queuing telemetry transport) or WebSockets.
Best Practices for Managing and Analyzing IoT Data
Real-Time Analytics
Real-time analytics data is especially crucial in the early stages of growth for an IoT company. This provides both the hardware and software engineering teams with the diagnostic data needed to resolve issues early on.
Because scale and efficiency are so critical in IoT solutions, advanced remote diagnostics and platform instrumentation are crucial to working out kinks in new products being delivered to the marketplace. If it’s missing, it can:
- Slow down issue resolution
- Lead to disastrous situations where the entire fleet could go down
Economics and Scale of Storage
IoT solutions generate vast amounts of incoming data. A common mistake is not storing data in a way that makes analysis easy. There’s also a risk of storing data in technologies that become extraordinarily expensive to scale–storage is usually the largest OpEx component for IoT platforms.
Your team needs a data management storage and analytics strategy that balances scale and cost.
Otherwise, once you have thousands of devices out in the field, the operating costs of your cloud environment could completely kill profitability.
Best IoT Testing Tools and Methodologies
In order to effectively test IoT applications, the software engineering team needs to work closely with a QA team who is intimately familiar with the hardware, the firmware, and the software.
Testing IoT applications is complicated by the multiple layers involved. Not only do you need to test different versions of different software components, you must also test each software component version against different device models AND each device model firmware version.
Your end-to-end QA process should use a broad testing matrix to validate a particular build of your IoT software with all models and supported firmware versions of those device models. This allows you to validate that a code deployment won’t break anything, as well as verify that it delivers the desired capabilities.
You need three dedicated environments for your IoT platform:
- QA Environment: should be updated weekly and is used by the development team; should have devices connected so you can validate/break/fix at a high frequency.
- Integration Environment: once a software version has been validated in the QA environment, it advances to the integration environment where customers use it on a limited, non-production basis.
- Scaling Testing Environment: before releasing to production, you must test at scale to make sure you have not introduced code that will destroy the scalability of your platform. Here, having realistic and scalable device simulators that can effectively mimic production-scale traffic is crucial.
As software architects, it is crucial to stay ahead of the curve by understanding the intricacies of IoT software engineering to deliver robust and secure solutions. There is no room for error in IoT.
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