The lack of skilled IT workers is hurting the deployment of emerging technology, according to a new survey from Gartner. In areas from cloud to cybersecurity, this crisis is expected to last for years to come.
IoT work is carried out by three types of
professionals:
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.
Though
responsibilities will vary greatly depending on the industry, other duties may
include designing, coding, and testing features of products meant to connect to
other devices.
Certain
projects may also involve creating embedded software that’s cloud-compatible, which enables products to integrate
properly with one another.
Average salary in US is $164,235 per year.
Developers
who want to make the most of the opportunities of IoT should foster skills
across a range of key topic areas including:
The devices,
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.
Prototyping
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.
The embedded
programs are often developed using C++ or C, however Python and JavaScript are becoming more
popular for prototyping IoT devices.
Connectivity
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.
In addition
to network design, developers should have a working knowledge of network
standards, protocols, and technologies.
These include
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.
Web and
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
now.
Web and
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.
Cybersecurity
is paramount in any IoT discussion. IoT devices are quite vulnerable to
security compromises. IoT security considerations should include, at a minimum:
As millions
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.
Artificial
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.
Many IoT
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
databases.
IoT
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.
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