Top 7 must-have IoT skills to boost your career
The internet of things is growing rapidly and becoming increasingly complex. IoT professionals will need an array of skills to succeed as this trend continues.
Devices of all types in every environment -- including mobile phones, automobiles and industrial equipment -- are now connecting to the internet.
By 2025, Statista predicts the total number of connected devices will reach 75 billion. As a result, engineers, developers and other IoT professionals are in increasingly high demand. These professionals will need a diverse skill set that enables them to develop and maintain IoT infrastructure at scale, at every level of the technology stack.
Here are some must-have skills that IoT professionals need to keep up with what some have termed "the IoT explosion."
1. Artificial intelligence and machine learning
IoT and AI are converging to form the artificial intelligence of things (AIoT). Gartner predicted that more than 80% of enterprise IoT projects will involve some AI component by 2022.
IoT devices collect large amounts of data called sensor data, which organizations then analyze. For example, a manufacturing plant could use IoT sensors to report the site temperature, which is then recorded in a database that tracks the temperature data for all sites. AI and machine learning could then help database administrators organize data, determine how to maintain the correct temperature and optimize the facility. Using AI also facilitates predictive analytics to improve the environment in the future. AI makes the data that IoT devices collect useful, helps filter redundant data out of big data stores and performs complex data analysis using data science.
Learn how AI brings new capabilities to edge IoT devices.
2. Node.js development
Node.js is a popular open source development environment for developers who are looking to pivot into IoT space. Node.js is often used in tandem with connected devices, such as Arduino and Raspberry Pi.
Arduino is a single-board microcontroller known for making embedded programming easier by interfacing with sensors and other inputs and outputs. Raspberry Pi is a low-cost, miniature, single-board computer used as a lightweight software development tool with languages such as Python and Node.js. Both devices are good teaching tools for people who want to get into these languages in an IoT context. Node.js enables Arduino and Raspberry Pi to communicate with each other.
Node.js is well suited to a distributed IoT environment, which quickly processes real-time data. It can handle multiple tasks at once because of its asynchronous, event-driven input/output model.
Learn about some of the features of Node.js 14, one of the latest iterations of this server-side runtime environment.
3. Mobile app development
Mobile apps often control IoT devices, so it is important for IoT developers to know how to create user-friendly, high-performance mobile applications. IoT applications should also be cross-platform and be able to communicate effectively with cloud servers and a range of hardware. Like most aspects of IoT, mobile apps should also perform well with real-time data.
Learn the basics of how to develop a mobile application for IoT implementations.
4. API automation and testing
Application programming interfaces (APIs) enable IoT devices to exchange real-time data efficiently and accurately; it's how IoT devices communicate with each other. Therefore, it is important for IoT professionals to be well versed in API testing. Because of IoT's complex and distributed nature, it is also important to automate tests where possible.
An example test case for IoT would be to ensure that a certain physical condition picked up by a sensor is represented properly in the program. Another example is to test what happens when the data structure of an IoT monitoring system is updated. For example, will changing the way data is organized within the system change how the data is processed? Any changes should be noted and tested to make sure the desired change occurred.
Hone your API testing skills with this best practices checklist.
5. Information security
Infosec professionals are in high demand in the IoT space. Securing IoT infrastructure is difficult because of the array of implementations and devices that IoT includes. Security engineers in this field need to be creative and adaptable in how they approach vulnerability assessments, accounting for both physical and logical weaknesses in IoT endpoints. There is also demand for security personnel that are skilled with tools from specific vendors, such as Orbit, a business management platform, and Cloudflare, a secure content distribution network.
One weakness of IoT -- specifically industrial IoT -- is password security. Often, administrators neglect to change manufacturer-set default passwords, because many devices in this space are not geared toward usability. They operate autonomously much of the time and do not have users regularly accessing them. Unchanged passwords make it significantly easier for intruders to guess the generic passwords and break into IoT systems to steal data or perform network reconnaissance.
Learn some best practices for password hygiene.
6. UI/UX design
IoT's security problem and need for competent user interface and user experience designers go hand in hand. The more user-friendly an IoT device is, the easier it is for security personnel to dynamically update security settings.
Good user experience also makes it easy for users to understand how a given IoT product provides value to their organization. With all the information IoT devices generate, good UX and responsive web design are crucial to creating a secure flow of data from sensors to applications to people. UX designers in the IoT space must be able to collaborate with IoT software developers to make this a reality.
7. Cloud computing
The distributed cloud computing framework is an important concept for IoT professionals. Instead of processing the data solely at the edge -- the closest to the place in a network where data gets created -- or in a centralized cloud database, distributed computing mixes both approaches, processing some data at the edge and some centrally. Time-critical data or data that requires less processing could be processed at the edge and close to the source. Data that is not time sensitive or requires more intensive processing can be sent to a centralized location farther from the source.
Learn how the IoT edge cloud creates the perfect balance of edge and cloud computing for IoT implementations.
How to improve IoT skills
To improve IoT skills, the IT professional needs to identify areas to develop. This can be done by reviewing a list of common skills or a job description for IoT. Peer reviews and manager assessments are also helpful to determine skill improvement opportunities.
Here are some ways to enhance and improve skills:
- Pursue training online, through workshops or at conferences.
- Look into certifications or a college degree.
- Find an experienced mentor for questions and advice.
- Ask questions for clarification.
IoT speaks many programming languages -- such as Java, Python, PHP, Swift and C# -- and requires experience in a variety of frameworks such as hardware, software, cloud, analytics and user interface. It's also equally important to maintain these skills over time because this field is always changing.
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