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RFID, AIDC, and IoT News: Most IoT Projects Failing, Deloitte Says, but Technology Help is On the Way


Progress Along Five Key Vectors will Make Projects Easier, Enhance Success Rates

July 18, 2018
SCDigest Editorial Staff

The hype machine for Internet of Things (IoT) technology is running full bore, that's for sure.

That makes the data referenced in a blog post by consulting firm Deloitte, based on a survey from Cisco Systems, that close to three-fourths of IoT projects were failing in the US, the UK and India all the more interesting.

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Batteries powering LPWAN sensors can last for years, with the networks providing connectivity for IoT devices for as little as $3 per year.

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Why the tough IoT sledding? Security issues are at the top of the list. Other challenges include implementation complexity and cost, lack of talent with required IoT skills, and difficulties finding real value from IoT-generated data, especially processing it in real time to gain actionable insights.

The better news: Deloitte says much progress across five key vectors, as summarized below:

Security: Deloitte says that new generations of hardware are helping to overcome the technical challenges of securing IoT devices, while machine learning is helping to secure the networks that connect them.

Earlier generations of IoT devices simply lacked the necessary computing and battery power to run traditional cybersecurity applications and protocols, leaving them vulnerable to attack. But now microprocessor manufacturers have introduced low-power hardware products that embed security features, such as providing trusted identities to certify devices on networks, directly into IoT devices.

Securing IoT has also been a challenge because existing security tools designed for corporate IT networks were poorly suited for recognizing threats in networks of IoT devices. But cybersecurity solutions tailored for IoT networks are becoming widely available, Deloitte says.

Platforms: The evolution of so-called IoT platforms is making deployment easier, Deloitte says.

These platforms make it easier to integrate IoT hardware, networks, and applications. Providers are also reducing the complexity of building solutions by pre-integrating third-party technologies through vendor partnerships. Major platform providers now have dozens of hardware partners, and sometimes this is enabling companies to get IoT proofs of concept and pilots up and running in a matter of just weeks.

Deloitte observes that "vertical" IoT solutions continue to arrive on the market. These offerings pre-integrate sensors, devices, analytics, and other components to create complete solutions.

Manufacturers have taken advantage of such turnkey IoT solutions. For example, Deloitte cites one luxury clothing retailer deployed a platform with pre-integrated software, sensors, in-store analytics, and RFID tags from different vendors to gain insights on shopper behaviors and real-time inventory visibility.

Low-Cost, Power-Efficient Networks: Something called low-power wide-area networks (LPWANs) are proliferating worldwide, providing connectivity at low cost and with low power requirements, a crucial advance IoT applications that relies on battery-powered sensors and spans large geographical areas.

In fact, Deloitte says major telecom players have launched more than 40 LPWANs, while smaller LPWAN specialists are also expanding their proprietary networks globally.

Batteries powering LPWAN sensors can last for years, with the networks providing connectivity for IoT devices for as little as $3 per year. In comparison, cellular connectivity for IoT devices can cost at least a few dollars per month. Rapidly falling LPWAN module prices can also help reduce implementation costs, with some already less expensive than traditional cellular connectivity.


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Deloitte notes that the growth of these LPWAN networks is helping drive adoption of IoT-based devices for applications such as condition-based monitoring and optimization of capital assets in smart cities, smart utilities, and smart agriculture projects.

Artificial Intelligence: Deloitte says AI technologies such as machine learning and computer vision are increasingly being used to analyze IoT-generated data and automate operational decision-making, saying that nearly every major IoT platform vendor has now augmented its offerings with AI capabilities.

The rich insights and self-learning that AI can provide enhances the value and utility of the IoT in applications such as process optimization, predictive maintenance, dynamic routing and scheduling, and security.

Analytics On The Edge: Interestingly, Deloitte says that increasingly the analysis of data generated from IoT devices is occurring not in the Cloud or other centralized approach but at the network "edge," physically close to where the data is generated

New hardware and software product launches related to edge computing and the IoT have increased more than 30% so far in 2018 compared to the entire year of 2017

Analyzing data at the edge sidesteps the latency associated with transmitting data between the sensors that generate it and the Cloud-based applications that analyze it. Lower latency makes it possible to generate real-time alerts and insights that can improve operational safety and performance in industrial, enterprise, and smart city settings, among many others.

Deloitte cites a Gartner prediction that the majority of industrial IoT data analysis will happen at the edge by 2022, up from less than 10% last year.

All this progress is likely to make IoT projects easier to develop and increase the success rate.

"As barriers to adoption of IoT technology in the enterprise continue to fall, business and technology leaders would do well to keep an eye on these vectors of progress," Deloitte concludes.

Any reaction to Deloitte's take on IoT progress? Let us know your thoughts at the Feedback section below.


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