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IoT Usability—Going Beyond the Early Adopters
John Koon posted on May 13, 2000彩 |
What hurdles stand in the way of IoT adoption?

According to , manufacturing has the highest Internet of Things (IoT) adoption, followed by transportation, information, and wholesale trade. On the other hand, IoT investment by agriculture, oil and gas exploration, health care, and smart cities is much smaller. However, these sectors are already creating ways to put the IoT to work. 

For example, IoT applications can help farmers monitor field conditions and crop health as well as automate processes like watering. In addition, the IoT can help improve oil field operations by tracking asset health and production levels while ensuring safety compliance. Furthermore, health care workers can use the IoT to locate patients and equipment, reducing delays. Cities can find the IoT essential for tasks such as tracking utility usage, managing traffic, or even identifying disease outbreaks.

Despite the IoT’s potential and the enthusiasm of early adopters, according to a recent , only about one-quarter of IoT projects succeed. 

While early adopters worry about interoperability, late adopters are more concerned about IoT security, connectivity and management.

In general, the late adopters worry about IoT complexity, the availability of IoT expertise, and having an ecosystem for collaboration. They want to be able to connect, gather, understand and use the IoT data without having to worry too much about security, network connectivity, and managing the IoT devices. Also, having an ecosystem and opportunities for collaboration in place will go a long way toward supporting their efforts to find customized solutions for their business cases.

In short, the late adopters want a more user-friendly IoT. The IoT can become more usable through data security assurance and connectivity and management improvements, as well as via the fostering of an ecosystem.

Improving Connectivity with Edge Computing

IoT connectivity can be improved when data transfer is made more efficient by transferring only relevant and high-quality data.

Centralized computing requires that data be moved from end-user IoT terminals at the edge of the network to the central cloud server for analytics, even though most of the data is not useful. Then, the results of the analytics need to be sent back to the end terminal. As cloud computing’s data transfer speed is finite, transferring large datasets between the network edge and the cloud can easily lead to congestion and significant delays, in turn slowing data-driven decision-making. 

By pushing data processing to the network edge, one can achieve faster data analytics and decision-making closer to the point of data collection and execution. Shifting most of the computing to the edge will reduce the amount of data transfer significantly so that only the relevant data will be transferred. This way, most of the bandwidth is freed up for data transfer and latency (or delay) will be minimal.

Connectivity is also a cost issue. Large-volume data transfers are costly; in edge computing, the cost of data transfer will go down accordingly.

Improving Connectivity with 5G

Connectivity can also be enhanced with faster data transfer so that congestion will be minimal despite the volume of data. The development and implementation of 5G will accelerate data transfer significantly. 

Compared to 4G, 5G improves speed 10x to 100x. And the broader network coverage enabled by 5G significantly shrinks data transfer times. For example, the download of a full HD movie, which takes minutes on a 4G network, will take only seconds with 5G. Moreover, 5G can support a diverse range of use cases and a high density of devices. 

Improving Management by Solving the Power Supply Bottleneck

As businesses begin managing an increasing number of IoT devices, they will want to spend less time managing each device. The power supply is a major bottleneck with such devices. Most IoT devices are battery powered because they are installed in remote or hard-to-reach places. When the batteries run out, replacing them becomes a pain point and something to postpone as much as possible.

Some companies are working on developing battery cells with longer life spans, while others are trying to increase the power efficiency of devices. 

Such strategies are not without caveats. For one, the supply of lithium that is needed to make batteries is limited and may curb its use in IoT devices. When the cells in these batteries need to be replaced eventually, the cost of time and labor will be considerable.

Therefore, batteryless IoT devices are under development. Harvesting energy from their environments, such as mechanical (vibrations), solar, body heat, or industrial heat waste, these IoT devices could circumvent the conundrum of batteries as a power source entirely.

Improving Management with Interface Design

Interface design for IoT applications is challenging due to the complexity of a system that contains many IoT devices. 

A network of IoT devices involves many users, nodes, interfaces, data points, and even multiple systems. There are numerous interactions among the users and the virtual system. What is more, users need a seamless and unified interface that connects the digital and physical worlds.

Because the late adopters feel overwhelmed by the complexity of the IoT, the interface should help them visualize and understand the data so that they can extract business value from the analytics. Late adopters are concerned about system security and connectivity, so the interface must keep users updated on system issues such as which nodes are online, which are offline, and where any breach is occurring.

If the interface is difficult to use, view or understand, the perceived value of the system will decrease. Likewise, a smooth and user-friendly interface will help users see the value of and justification for the cost of the system.

Improving Data Security

Security risks need to be mitigated to put users at ease. 

In the central cloud computing model, one data security concern is that most data are stored in one place and may be vulnerable to tampering or theft during transfer. In the edge computing model, data security risks are much more distributed across many nodes. The decentralized storage and processing of data reduces the risk and possibility of a breach, as it is much more labor intensive for hackers to try to break into the nodes one by one.

In addition, the automation of security updates will reduce oversight and increase security, as well as improve IoT device management. Making firmware patching automatic will reduce the delay or neglect of security updates. Alternatively, users can be prompted to approve the latest updates whenever firmware updates are available so that security issues can be fixed promptly and thoroughly.

Fostering an Ecosystem to Encourage Collaboration

Lastly, because the late adopters feel less confident about managing and using new and complex technology, it is crucial to create an ecosystem that helps them understand, develop and implement the technology. It is analogous to having a forum for students—a place where participants can discuss a complicated subject and help each other progress together, even collaborating on practical projects.

In the Cisco survey mentioned above, the participants stressed the importance of collaboration and fostering the ecosystem. IoT solutions are sector, domain, and even location specific. Therefore, enabling developers to create customized solutions is crucial. 

Hardware design novices will need specific expertise, tools and templates to get started. A product needs input from designers, engineers and software developers to create a prototype as well as make improvements. The try-and-learn approach is essential, and collaboration will help developers share their knowledge and learn from each other’s mistakes and successes. 

The Future

The main difference between early adopters and late adopters is that early adopters are already on board and much more willing to tolerate uncertainty, risks and bugs. For the late adopters to get on board, they will need to see evidence of performance, reliability and system value. 

Therefore, the late adopters need consistency in connectivity and data security, as well as the user-friendliness of the system. The management of the IoT networks can be automated to increase the ease of use further. In short, reliable networking and the bridging of IT and operations will go a long way toward increasing the IoT’s practicality.


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