IoT – Internet of Things – is slowly, surely and intricately connecting gadgets to our lives. Be it vehicles, home appliances, medicinal equipment or embedded electronics, microchips have enabled collecting data and controlling devices remotely over a network.

Such devices have transformed the way industry works. Cisco believes that the economic value added by the “Internet of Everything” will be nearly $19 trillion by 2020, while a McKinsey Global Institute research report suggests it will be $6.2 trillion by 2025. In any case, it is a very large number, and dwarfs past technology trends [e.g. $150 billion for Fintech by 2021 as per a PWC report; Cybersecurity, at nearly $1 Tn, as reported in PR News Wire.]

The Stumbling Blocks

However, this journey to achieving the lofty goals is fraught with challenges:

1. First is the lack of uniform standards and protocols, which are also difficult to achieve because each device is one of its kind. This causes different devices to use different network technologies and operate on various networks. This is becoming more of a problem since devices are starting to interact and execute pre-determined decisions and pre-programmed inbuilt logic. Compatibility and behavior become suspect and need to be tested for consistency.
2. Traditional frameworks are not yet capable of capturing, routing, analyzing data, and providing insights for meaningful business decisions. This also makes managing the data difficult, needing huge storage, strong data management, and analytical skills.
3. Privacy and security concerns will become a major concern in the IoT ecosystem. There have been several instances of hackers taking over unsecured webcams to spy on the owners. For homes to remain a haven, IoT developers have a responsibility of ensuring their products and solutions are immune to access by the undesirable intrusion.
4. The huge amount of data that sensors generate every millisecond introduces several complexities in managing it. The 4 Vs of Big Data: Volume, Velocity, Variability, and Veracity will have to be dealt with efficiently.
5. Different resources and technologies need to be integrated as IoT straddles different types of devices. Some of the technologies typically used in IoT include:

1. RFID (Radio Frequency Code) tags and EPC (Electronic Product Code)
2. NFC (Near Field Communication) for facilitating two-way interactions between the devices.
3. Bluetooth to enable short-range communications mostly in wearable technologies.
4. Z-Wave, a low power RF communication technology for home automation, lamp controlling etc.
5. WiFi for transferring files, data, and messages seamlessly.

1. Sustenance is yet another challenge as many device makers are startups that may or may not be able to sustain in the long run, or may get taken over.
2. Failure to map or incomplete mapping of relevant systems to IoT deployment contributes to device failure.

The Rollout does not typically consider the practical use of the IoT devices or how they will play into the daily life of the users. The focus is on the flash rather than the substance – it will take time for the useful business processes to be identified and put into place.

During a Cisco survey of 1,800 IT leaders in the US and UK, a strong message that emerged is that one needs to be ready for the failure of IoT initiatives. As many as 60 percents of IoT projects could not scale up after the proof of concept phase. The survey also revealed that nearly 75 percent of IoT initiatives are business failures.

Testing to Clear the Path

The causes could be rooted in poor project management, architectural development without foresight, or during the rollout. While some are dependent on business decisions, the technology aspects can and should be tested in a timely manner as well as periodically on an ongoing basis.

While a start-up may ambitiously decide to integrate testing with development, an external testing partner with a cross-domain, technology, and protocols experience can help improve the chances of success of the initiative. Involving the testing partner right at the project planning stage can help anticipate and incorporate course correction at every stage to minimise the cost and time of development. It also frees up resources for research and development, while the testing team provides the inputs needed to make it a high-quality product.

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