Among all the challenges of adopting enterprise IoT—security, connectivity, and budgeting—one is most likely to disrupt your operation: Building effective back-end data systems.
That’s our takeaway from a 2023 report by the open-source nonprofit Eclipse Foundation. The Eclipse survey found that more than half of respondents were already deploying IoT solutions, while another quarter would launch their projects over the next two years. In other words, these weren’t IoT greenhorns.
When asked to name the top operational challenge, however, the greatest share of respondents—nearly 23 percent—listed “processing and managing IoT data.” When you look at the history of IoT development over the past decade or so, that makes sense. It takes some very particular skills to develop software that turns IoT data into usable intelligence. Those skills remain in short supply.
Welcome to the IoT skills gap. It’s real, it’s persistent, and it’s not likely to change any time soon. Luckily, there’s a workaround: low-code tools for building and customizing IoT systems, from data management to user interfaces.
Here’s a quick explanation of the IoT skills gap, followed by an introduction to low-code solutions that are available right now, this very day.
“When asked to name the top operational challenge, the greatest share of respondents—nearly 23 percent—listed ‘processing and managing IoT data.'”
-weeve
The Origins of the IoT Skills Gap
Coding skills are niche by nature; a firmware developer probably won’t know what to do with big data analytics. As an essentially hybrid technology, IoT requires multiple strands of deep technological expertise. To bring a custom IoT application to fruition, for example, you need experts with profound experience in:
- System/machine integration
- Data science and analytics
- IoT security
- Cloud software development
- User experience and user interface design
- Data project management
As these fields relate to IoT, there’s not exactly a lot of standardization (yet). Protocols and technologies are proliferating, but many of them follow their own developmental pathways. That makes interoperability a challenge. So the skills gap runs deeper. The rapid pace of innovation is also leaving education and training programs behind. Until training infrastructure catches up to technological development, we’re left with just a handful of experts.
Where do these rare IoT experts go? They tend to get hoovered up by large corporations with deep pockets. Small and medium-sized enterprises can rarely find enough experts to build a team, let alone afford the salaries.
The skills gap won’t last forever. Industry groups like the Open Connectivity Foundation are working on standardizing IoT technologies. Training programs are popping up at major universities. But what if you need a custom IoT application to solve pressing business challenges today? That’s the challenge.
And that’s when you need low-code tools built specifically for IoT applications.
How Low-Code Tools Help to Bridge the IoT Skills Gap
A low-code tool is a software platform that allows you to build an application without much coding skill. Think of a website builder like Squarespace: Anyone can use drag-and-drop tools to build a site.
With an IoT low-code tool, of course, you’re not just building websites. You’re using pre-made components, templates, and—yes—drag-and-drop interfaces to develop custom IoT applications. That allows you to add new functionality to an existing IoT system. It can even help you build a fully custom IoT application from scratch.
Low-Code IoT Development: A Hypothetical Example It’s hard to generalize about IoT systems, since they all serve highly specific functions. But here’s one example of greenfield IoT development using low-code tools based on our experience at weeve; hopefully it’ll help you conceptualize your own IoT projects. Say you have a wastewater container on your shop floor. You need to know when the level hits a certain point so you can dispose of it safely; you also need to know if a leak pops up. You have a connected fluid-level sensor. You have a leak-detection device. How do you get those bits of hardware to send an SMS to your mobile phone when your wastewater container needs attention? Assuming your hardware’s all in place, a low-code tool allows you to create these alerts in just a few minutes. You add a simple module to the low-code platform environment and the tool handles all the configuration and installation—no coding expertise necessary. Even better, once you build this logic function, you can scale it from one to 100 wastewater containers with the click of a button. That’s the power of low-code IoT. |
So who uses these tools? It could be anyone on your team who knows the IoT devices or systems you’re already using. If you’re building from scratch, your existing IT team won’t have trouble with a low-code solution—provided you choose the right one.
Choosing a Low-Code IoT Tool: 8 Features to Look For
Today’s market offers a handful of low-code IoT tools. How do you know which one is right for your project? Most users get the best results with a tool that provides these 8 capabilities:
- User-friendly design: Take a look at the tool’s development platform. Is the user interface intuitive and easy to operate? If so, that’s a good sign.
- Wide-ranging integrations: Low-code tools should work with the devices, services, and platforms you prefer—and these integrations shouldn’t require custom coding on your part.
- Built-in security: Choose a tool with native encryption and access control. That way, security is built into your application from the start.
- Simple scalability: If you program a function, your tool should bring it to all your devices as easily as possible.
- Flexible customization: Low-code tools should provide ways for you to go deeper and develop even more customized applications. (Incidentally, that’s why we recommend “low-code” rather than “no-code” tools; you want the option for custom code development even if you don’t use it.)
- Platform-agnosticism: Some IoT platforms may offer low-code tools, but they lock you into a single ecosystem. Instead, choose a tool that works with any IoT device, service, or platform. You’ll get better interoperability and more flexibility down the line.
- Edge-computing support: Edge computing is on the rise in IoT. (That Eclipse survey found that 53 percent of organizations were using or planning to use edge computing within 12 months.) Work with a tool that allows you to run applications on the edge, i.e., locally on devices.
- AI integrations: Machine learning can supercharge IoT systems. Make sure your low-code tool supports integrations with machine learning and other AI technologies to stay future-proof.
Finally, there’s the question of speed. How quickly can you create new functionality for your IoT system with a low-code tool? A solution with plenty of pre-built components and a drag-and-drop interface will offer the quickest, most satisfying results. That way, you don’t have to wait for the IoT skills gap to narrow. You don’t even have to wait until tomorrow. With low-code IoT tools, you can get the benefits of enterprise IoT in just moments—no coding expertise necessary.