The document discusses the role of software testing in Industry 4.0, highlighting the importance of testing IoT devices to ensure their functionality, usability, and security within a connected ecosystem. It emphasizes next-gen testing methods like crowd testing and AI-driven techniques that help manage the vast amounts of data generated by these devices. The IoT market is projected to see significant growth, necessitating advanced testing approaches to support this evolution.

1. Role of
Software Testing
in Industry 4.0
It is a facet of testing the world of connectedness with IoT gadgets, virtual
reality, wearables with real-time associations along with testing of the
intervened digital ecosystems. Software testing involves the process by which
scalability, flexibility, and tangibility of the connected devices is achieved.
The functionality and usability of these connected devices should be tested
thoroughly to ensure effective working in the digital ecosystem. Extensive
testing is fundamental to ensure successful IoT product launches into the
market that delivers value.
Moreover, these IoT devices are connected to various apps on smartphones,
tablets or laptops; each with different operating systems, versions and different
devices for which crowd testing can be a good fit. Some of the other critical
next-gen software testing methods include Smart wearables testing, IoT testing,
Big Data testing, and usage of AI in testing.
A recent report by Markets and Markets states that “The IoT testing market size
is estimated to grow from USD 302.9 Million in 2016 to USD 1,378.5 Million by
2021, at a Compound Annual Growth Rate (CAGR) of 35.4% from 2016 to 2021.”
The IoT ecosystem encompasses mainstream applications including home
automation, smart appliances, wearables, health and fitness apps and more.
The industrial IoT (IIoT) embraces the same concepts of Industry 4.0 and
includes the integration of some of the more complex devices and systems with
networked sensors and software. Evidently, IoT testing involves various types of
tests across all system components.
The various types of IoT testing required to enable scalability, performance, and
security of smart (connected) applications involves Edge testing, Protocol and
device interoperability testing, Security and privacy testing, network impact
testing, performance, and real-time testing, and end-user application testing.
IoT testing also involves the performance testing of software-hardware
components of devices, Compatibility testing across multiple domains,
user-experience testing and exploratory testing.
Next-Gen Software Testing
Methods to Dominate Industry 4.0
IoT Testing
With the influx of millions of connected devices, IoT triggers a massive inflow of
Big data. The data consists of structured data, unstructured data, images,
contextual data, and real-time data.
Big data should be augmented to effectively store, manage and extract value
from continuous streams of IoT sensors data. Sensors, in reality, send
gigabytes of data that can be used by big data technologies to process it and
deduce valuable insights to help in quick decision making.
Therefore, it has become a clear need to test big data and gain insights from
patterns to understand data behavior.
Big data testing
The usage of AI technologies like deep learning and machine learning
algorithms help derive insights rapidly from IoT connected devices. The IoT
continues to proliferate as connected smart devices become critical for
individuals and businesses.
The IoT market is projected to be worth $1,490.31 billion by 2024, this explosive
growth is set to continue more in the coming years.
IoT allows the flow of data between devices, and AI can be helpful. Evidently, as
much of the IoT application is composed of services outside the control of the
application, an effective way of test automation strategy is to embrace AI and
ML (Machine learning).
It requires intelligent models to auto-generate tests using AI and ML that allow
teams to analyze data from testing and to identify patterns. Moreover, AI is
expected to be the key enabler to the growth of the future IoT revolution with
digital ecosystems all around and is expected to take it to a new level.
Adoption of AI in Testing
Crowd testing is an effective technique that is applied to a system under test. It
basically involves the testing of software on a large number of devices,
browsers, and operating systems and significantly all tests are executed in
parallel by different testers. This sort of testing not only involves testing the
software configurations, but it also involves the APIs testing with other
connected devices.
Crowd testing tests on various markets, regions and on a variety of devices
which helps to get an understanding of the functionality and usability of the
system under test in various conditions.
Generally, in crowd testing the client, the organizer of the test, and a pool of
crowd testers are involved. Today, crowd testing is gaining importance in the
world of connected devices especially in Industry 4.0
Crowd Testing
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