HomeTechnology4 factors that make testing of IoT solutions challenging

4 factors that make testing of IoT solutions challenging

By Naveen Joshi – Founder and CEO of Allerin

Works in Big Data,IoT , AI and Blockchain

• Diversity in the internal and the external framework of the various elements used in its network can make the IoT testing quite challenging. But, changes in the simulation models for the test can reduce the risk of error while testing these networks.

With technology impacting various facets of an organization, companies both, big and small, are looking for ways to integrate it with their existing systems. However, to apply any technology in practical situations requires testing of the proposed model. And, it is this that challenges the IoT testing teams of companies.

From intrinsic differences in the manufacturing styles to improper simulation environments, IoT testing is highly influenced by multiple factors that might result in dire consequences if not taken into consideration. Following are a few factors that make testing IoT solutions challenging.

1.  Custom configuration of hardware

The Internet of things is an umbrella term for networks made up of multiple, minute components. There is both hardware and software involved in building an IoT network. The company employing an IoT application doesn’t usually manufacture the hardware or program the software for it. Although both the design and code are assessed individually, testing them after integration can bring up problems due to their custom configurations. In bigger networks, the IoT chain uses different devices like gateways, routers, switches, hubs, and other high or low-level platforms. All this equipment comes with their pre-set configurations which may or may not be compatible with each other when connected.

2.  Obsolete technology of components

A new Apple product released every year deems the previous ones obsolete. Similarly, IoT devices, which are constantly upgraded, go obsolete with every advancement made in the IoT domain. New updates that are better and more effective than the previous ones are developed every single day. As a result, the devices built with the newly configured components work efficiently, with minimum resources and maximum output. Companies experience problems in testing these new products with an outdated version of the components used in IoT network. This can cause huge losses for the companies if all their existing systems turn out to be incompatible with the new devices.

3.  Different protocols between devices

Like hardware, IoT solutions involve a lot of contracts for communication. Integrating various aspects of a simple IoT solution consists of dealing with the edge devices, collecting data from low-level platforms, coordinating multiple interfaces with a central hub, and finally presenting the data on a display device as per its framework. All these activities require communication and coordination between different protocols of the devices in the network. The testing, done in isolated environments, might not produce the same results when the devices are connected with each other due to differences in the protocols architecture and framework of the software APIs.

4.  Inaccurate simulation for IoT testing

Another major challenge in testing IoT products is the testing environment. Due to a simulation-based testing pattern, IoT solutions are fed with ideal data generated by computers. This approach doesn’t allow for real-time data testing where the system is supplied with data acquired from the real sources that can then be worked upon for producing appropriate results. There have been changes in this approach now, and analysts currently employ test as a user methods for assessing IoT solutions.

Measures to mitigate these risks associated with the testing of IoT solutions involve studying and building better simulations which can closely replicate the system components and elements. CIOs and the development teams of an organization can work together to achieve better virtual networks which can then be extended to efficient physical networks.

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