The Internet of Things at the Crossroads

Stephen DeAngelis

June 05, 2019

Most discussions about crossroads focus on decision-making and choosing a direction to head. For example, author Mary Buchan (@MidLifestyleRN) writes, “Life presents us with moments of decision — crossroads where we either choose a new direction and move on, or cling to what we already have and be miserable.” Much less discussed — but to me a more interesting topic — is what comes together at crossroads. Drop the “decision point” analogy and view crossroads as places where people, ideas, and disciplines meet. Some of the best innovations result when people from different disciplines meet at the crossroads of a challenge. Crossroads represent network nodes and, in that light, the Internet of Things (IoT) can be considered a crossroad that connects things. Leslie Langnau (@DW_3DPrinting) views the IoT as a place where design, manufacturing, and supply chains converge.

She writes, “One might say the manufacturing world has become obsessed with the global network of connected devices and people. Rightfully so, as these performance insights can greatly improve the way we manufacture products.”[1] The challenge, she notes, is ensuring the things being produced meet all of the standards, regulations, and expectations demanded of them in an increasingly complex world. She asserts IoT connected devices “introduce complexity and risks to operations and the overall supply chain as distributed teams struggle to manage terabytes, or even petabytes, of data across multiple systems and platforms.” She continues, “With greater complexity, we expect to see an increased risk of product quality issues and product launch failures. Manufacturers must seek better ways to manage their design processes, improve the customer experience, and reduce quality defects.” The answer, she believes, is using the IoT as a crossroads where designers, production teams, and supply chain professionals meet to solve problems.

The Internet of Things at the crossroads

It’s well documented that IoT technologies remain in their infancy. Among the things people are wrestling with are standards, protocols, and privacy issues. Data breaches and malware incidents are forcing governments around the globe to regulate these growing concerns. In addition, Langnau notes, “Product innovators are forced to contend with a deluge of data as they struggle to effectively coordinate dispersed teams to design, validate, and build new products on ever-tighter schedules and budgets.” If that isn’t challenging enough, Langnau argues, new product development and introduction (NPDI) teams must understand and leverage the vast amounts of data constantly being generated by IoT-enabled devices. She concludes, “With this new IoT paradigm, multidisciplinary design and development-team collaboration early and throughout the entire product lifecycle is essential to product launch success.” That puts the IoT at the crossroads. Using the IoT as a collaborative tool, Langnau believes contributors will be connected and synchronized to the point where:

  • The entire product team can work on the same version of the product.
  • Each discipline is synchronized with the others wherever they interface.
  • Everyone can see the project details, milestones, and deliverables that lead to an on-time launch.
  • The product is designed from the ground up to meet regulatory requirements.
  • Tests are run at every phase to ensure interoperability and manufacturability.

Langnau concludes, “The untapped potential of IoT is still unfolding. Although information shared with connected devices can produce meaningful insights during production and customer use, it has yet to be fully leveraged to automate continuous product design improvement.” Although she discusses the extraordinary amounts of data being produced by IoT-enabled devices and the need to find meaningful insights from that data, she doesn’t address the cognitive technologies necessary to produce those insights.

Artificial intelligence at the crossroads

So much data is being generated nowadays virtually everyone accedes to the fact that analysis can no longer be accomplished without the aid of artificial intelligence (AI). Megan Crouse (@abmdigi) writes, “Artificial intelligence is … a big part of conversation in industrial applications. Intelligence for most of these companies is defined as machine learning, complex automation, and predictive maintenance, areas in which traditional industrial providers are bumping up against new companies dedicated to the AI space specifically.”[2] When most people discuss the IoT (or Industrial IoT), they are really talking about an ecosystem consisting of sensors, connectivity, and analytics. You really need all three parts of the ecosystem. Some people, however, view the IoT as a separate entity from the analytics portion of the ecosystem. For example, Anna Solana (@sol_anna) writes, “There are concepts and technologies that come better as a pair, just like pen and paper, knowledge and power or nuts and bolts. … The Internet of Things and Artificial Intelligence are also one of those dance partners with perfect connection that are meaningful together.”[3] Whether you see analytics separate from or part of the IoT ecosystem, it’s essential to making the IoT work. Solana explains:

“IoT is about connecting machines and making use of the data generated from those machines, which is huge. In fact, IDC research group estimates that the amount of data created annually will reach 44 zettabytes in 2020 and up to 180 zettabytes (180 + 21 zeros) by 2025. And there is no end in sight to this flood of data as there are new connected devices every minute. This data needs to be processed before travelling through the networks to produce useful actions such as traffic control, climate prediction or crime detection. This is where AI needs to play an important role, be it by the means of Machine Learning, Cognitive Computing reasoning, natural language processing, speech recognition and vision (object recognition), human–computer interaction or dialog and narrative generation.”

One might even conclude the analytics part of the IoT is what puts it at the crossroads of collaboration and decision-making.

Concluding thoughts

Returning to the more traditional notion of what happens at the crossroads (i.e., decision-making), IoT providers must decide whether to work together to overcome challenging problems or continue on the path leading to dysfunction, confusion, and dissatisfaction. Crouse explains, “Security remains a concern for the Internet of Things. Demonstrating another challenge to broad adoption, [a report from ABI Research] says IoT players presented ‘a rather confusing and fragmented mix of technologies and approaches,’ and that ‘the critical need for standardization was not addressed sufficiently.’ Overall, the field remains in transition, with a disconnect between offerings and practical solutions.” The crossroads is a great place to be if you want to understand how things work. The crossroads also produce angst when decisions must be made. The IoT may be the key to solving many problems, especially in the supply chain, but providers of IoT technologies must work together if they are going to choose the right road to take us all to a better the future.

Footnotes
[1] Leslie Langnau, “IoT Crossroads: design, manufacturing, and supply chains will converge,” Design World, 21 April 2019.
[2] Megan Crouse, “Industry Overview: Connectivity is Growing, But Remains ‘Fragmented’,” Manufacturing.net, 17 April 2019.
[3] Anna Solana, “IoT and AI: Why it Takes Two to Tango,” IoT Evolution, 23 April 2019.