When someone asks you, “Is IoT a good career?”, you have the right to start talking about job opportunities and salary.
However, if you want to genuinely evaluate whether an IoT career is right for you, you should ask yourself the following:
Are you excited to learn and work with the different layers of the IoT stack?
Because IoT is not a monolith.
An IoT solution involves hardware, connectivity, data, software, security, and increasingly AI.
Let’s take a look at some of the key areas that can form an IoT career.
IoT Career: Know the Layers – Hardware and Devices
First, most IoT solutions today revolve around devices and sensors.
A sensor can record temperature, motion, location, pressure, humidity, energy use, or machinery state.
Working with devices and sensors is one of the areas that can bring you deeper into hardware.
Some possible areas of investigation include:
Arduino
ESP32
Raspberry Pi
Embedded C
MicroPython
You do not necessarily need to become a hardware engineer to work with IoT.
However, knowing how IoT devices generate data is critical to developing your IoT skills. It allows you to see how IoT devices work and how to leverage them in your career.
IoT Career: Connectivity and Communication
The next logical question that has to be resolved is how to move data from one part of the solution to another.
Depending on the situation, an IoT solution can use any of the following:
WiFi
Bluetooth
Cellular
LoRaWAN
Ethernet
As a developer, you might be working with communication protocols such as MQTT or HTTP to enable communication between devices.
MQTT, for example, is a lightweight protocol used to send messages between devices.
This is a critical area in an IoT career since most problems in IoT stem from poor communication.
IoT Career: Data and Data Processing
At some point, every IoT application will need to process data.
This can be as simple as having a structure that allows you to store the data.
A sample of the data coming from a connected device would look like:
Device ID: Sensor-204
Temperature: 24.8C
Timestamp: 10:32:14
The data format can be more elaborate depending on the use case. Either way, this data needs to be processed somewhere in your IoT application. This is where your understanding of Python, databases, APIs, and data processing in general comes in.
Some of the technologies that you can use here include:
Python
SQL
REST APIs
Message queues
Time-series databases
IoT Career: Cloud and Edge
Some data in an IoT application is either too large or does not need to be processed immediately.
As a result, it is stored in cloud storage solutions.
Edge computing, on the other hand, allows you to process data closer to the device.
This is done to either reduce latency in processing or to improve privacy and security.
This opens up the opportunity for you to understand how cloud and edge technologies work in an IoT solution.
IoT Career: Security
Every connected device is a possible entry point for attackers.
IoT security solutions secure devices, data, and networks.
They help ensure that attackers cannot use IoT devices to gain unauthorized access to your network.
Some of the areas that you need to consider when dealing with security include:
Device authentication
Secure communication
Access control
Firmware
Securing APIs
Network security
An IoT career is a great fit for people who are passionate about network security.
In fact, IoT devices offer more ways to secure networks compared to traditional devices.
IoT Career: AI, Analytics, and Machine Learning
Modern IoT applications are largely about using AI and analytics to make business decisions.
Sensors collect data, and then analytics and machine learning help extract meaningful information from this data.
This can be done in a variety of ways depending on the use case.
A typical end-to-end workflow can look something like this:
Sensor
IoT Device
MQTT / Network
Cloud or Edge
Database
Analytics/AI Model
Dashboard or Automation
This is why we are seeing so many companies trying to conflate AIoT (AI + IoT). The main reason is that IoT data is critical to building AI models that can help organizations make decisions. Industrial applications of AI and IoT such as PharmaFlux AI represent the convergence of the two fields. In short, analytics and AI make IoT much more powerful and interesting as a field, and are definitely a good career option.
IoT Career Path: So What Should You Learn First?
At this point, you might be thinking about how to get started with learning IoT.
A good approach is to pick one area to start with.
If you like hardware, then start with ESP32 or Arduino.
If you like software, start with Python, APIs, and MQTT.
If you like infrastructure, start with cloud and networking.
If you like AI, start with Python, data analysis, and time-series analysis.
If you like security, start with networking and device security.
IoT Career Path: Final Notes
Whatever you do, avoid getting discouraged when learning IoT.
Do not try to learn IoT from a theoretical point of view.
Instead, try to create a working IoT application.
Try to connect something, store the data somewhere, and display it somewhere.
The following is a simple IoT application that you can try:
Temperature sensor
ESP32
MQTT Broker
Python application
Database
Dashboard
This simple project can teach you a lot about IoT, including how the whole system works.
This kind of hands-on experimentation is critical if you want to have a long IoT career.
IoT Career Path: Final Takeaways
An IoT career can be rewarding, but it requires you to be interested in different areas of technology.
IoT is intersecting with a variety of fields, including:
AI
Cloud computing
Edge computing
Cybersecurity
Data science
Therefore, when thinking about an IoT career, you should think of yourself as someone who is learning how to build applications that connect physical devices with software.
This is a great way to position yourself for the future since IoT will play a critical role in connecting the physical and digital worlds.
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