What Does an IoT Developer Do?
IoT work is carried out by three types of
- The network specialists that manage connectivity.
- The data analysts that gather data from the devices and interpret it.
- The engineers who create the platforms, software, hardware, and systems that allow these devices to function.
IoT developers fall into this third category; these
individuals oversee the creation of the devices or sensors themselves,
including most prominently, programming software that allows the device at hand
to both connect with other systems and function properly on its own.
responsibilities will vary greatly depending on the industry, other duties may
include designing, coding, and testing features of products meant to connect to
projects may also involve creating embedded software that’s cloud-compatible, which enables products to integrate
properly with one another.
salary in US is $164,235 per year.
who want to make the most of the opportunities of IoT should foster skills
across a range of key topic areas including:
- Application design
- Application development
- Data and artificial intelligence (AI)
with their sensors and properties, involve knowing a bit about hardware design.
IoT device design may be prototyped using platforms such as Arduino or
single-board-computers like the Raspberry Pi, with custom printed circuit
boards (PCBs) developed at a later stage.
with these platforms requires circuit design skills, as well as
micro-controller programming, and an understanding of hardware communication
protocols like serial, I2C, or SPI that are commonly used to establish
communication between the micro-controller and the connected sensors and actuators.
popular for prototyping IoT devices.
is another key aspect of IoT, which enables devices to communicate with other
devices as well as communicate with applications and services that are running
in the cloud. Network design and management are essential skills within IoT.
to network design, developers should have a working knowledge of network
standards, protocols, and technologies.
Wi-Fi, Low Energy Bluetooth, Zigbee, cellular, RFID technologies that are used
in consumer applications, and Low Power Wide-Area Network (LPWAN) technologies
like LoRa. LPWAN also includes SigFox and NB-IoT (narrow band IoT) that offer
lower cost, low-power long-range wireless connectivity, which are better suited
to large-scale and industrial IoT applications.
Application design and development
mobile applications provide user interfaces for interacting with and consuming
data from IoT devices. IoT devices, however, may have their own user interfaces
(UIs). UI and UX design skills are some of the hottest skills in IoT right
mobile applications are developed using high-level languages, with Java, Swift,
and Node.js among the top languages for IoT app development. GPS programming
skills are in particular demand, as many IoT applications, including wearables
and smart vehicles, are location-aware.
is paramount in any IoT discussion. IoT devices are quite vulnerable to
security compromises. IoT security considerations should include, at a minimum:
- Endpoint access
- Data encryption where necessary
- Appropriate authentication
of new devices enter the IoT landscape each day, the gateways of attack grows.
IoT devices have been used to launch Distributed Denial of Service (DDoS), as
well as other severe and damaging attacks.
With so much at
stake, security engineering skills are highly regarded within IoT. These
include threat assessment, ethical hacking, encryption to ensure data
integrity, securing network architectures and applications, as well as event
monitoring, activity logging, and threat intelligence.
Data and AI
Intelligence (AI) has become an intrinsic part of IoT networks. Intelligent big
data analytics involves applying cognitive computing techniques drawn from data
mining, modeling, statistics, machine learning, and AI.
devices generate latency or time-sensitive data, so it is necessary to filter
or discard irrelevant data. Key technologies and platforms for data analytics
that IoT developers should develop skills in include Hadoop, Spark, and NoSQL
developers, now and into the future, will require greater machine learning and
AI skills. Developers should be prepared to cultivate a diverse set of skills,
and be agile and willing to adapt to new processes, platforms and tools.