Slide the “time clock” into position with Arduino

Years ago, if you wanted to track employee hours, you needed to have them punch a time card. Saunders Machine Works, however, uses a facial recognition system running on an iPad for this purpose, meaning they had to figure out how to sense employees of different heights. What they came up with is a fixture that automatically raises and lowers the tablet, using a stepper motor and linear rails.

The project employs a Lidar sensor on the bottom of the device to detect employee presence, and another above the iPad’s mounting hardware to sense when it’s at the correct height, moving until the top sensor is clear. Control is provided by a pair of Arduino Nanos.

Be sure to check it out in the video below!

Arduino Blog

That’s another fine mesh you’ve got me into: Part 1

CIOs developing IoT strategies might take note of a particular section of Gartner’s Top 10 Strategic Technology Trends of 2018, says Clare Grant, general manager at Red Hat Mobile, where it describes the emergence of the intelligent digital mesh: “Gartner calls the entwining of people, devices, content and services the intelligent digital mesh. It’s enabled by digital models, business platforms, and a rich, intelligent set of services to support digital business.”

This is where IoT, analytics, edge computing and AI can be combined to deliver information so that organisations can offer a more immersive experience.

The combination of IoT, analytics and AI and, I would argue, mobile, can impact application development, integration and management by fuelling the need for apps to be developed and deployed for traditional, mobile and stateless environments.

CIOs should plan for maintaining core systems in the most cost-effective way, while constantly updating, securing and scaling apps, so that their organisations can respond quickly and flexibly to user and market demands.

So how can they manage change with finite resources? And how can they extend existing applications to mobile and other digital use cases?

Modern app development

Rather than being directed solely by internal IT departments, software development has shifted towards a more user-centric model, with demand for features and services often being driven by users engaging through multiple digital channels.

Today, software should be developed faster, updated more frequently and be able to integrate with multiple business functions and engagement channels, including mobile, messaging, the web and social media.

The industry has figured out how to connect back-end systems with mobile apps, now organisations should also interface with connected devices, analytics and AI apps.

Organisations that can deliver apps that quickly respond to changing conditions across multiple engagement channels can gain an advantage over those that are stuck in lengthy review cycles and tied to inflexible architectures.

In its Top 10 Strategic Technology Trends of 2018, Gartner has included:

AI foundation
Intelligent apps and analytics
Intelligent things
Digital twins
Cloud to the edge
Conversational platforms
Immersive experiences
Continuous adaptive risk and trust

Build on successes

While ‘the intelligent digital mesh’ may conjure images from a sci-fi movie, AI and IoT technologies ultimately provide either new apps or extend the functionality of existing apps.

Clare Grant

CIOs working with limited budgets and tighter timeframes should avoid reinventing the wheel and re-use existing models and infrastructure where possible. Many of the issues that surface with the integration of AI and IoT are similar to those faced and solved by mobile app developers when enterprise mobility was in its infancy.

Some organisations have become more strategic in their approach, no longer treating mobile as a separate project but seeing it as a broader part of their enterprise application landscape and their digital transformation strategy. I believe the integration of AI and IoT is likely to follow the same path to maturity.

Working with the open source community can also aid in IoT and AI app experimentation. The community can work together to solve common issues. Organisations can then select productised enterprise-ready versions of community-developed innovations that are built for scale.

The author of […]

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That’s another fine mesh you’ve got me into: Part 2

As IoT adoption increases and the number of connected devices proliferates, writes Clare Grant, general manager at Red Hat Mobile, I believe it will become unsustainable for organisations to integrate point-to-point.

Application Programming Interfaces (APIs) can play a crucial role in application development in the intelligent digital mesh because they enable connected devices and AI apps to interact with data stored in enterprise back-end systems, in a more secure and repeatable manner. In this way, large enterprises can respond in a more agile way to change and disruption, such as damaged infrastructure, stock substitutions, route variations, price increases, or product improvements.

Managing multiple point-to-point communication

The opening up of APIs can also enable organisations to provide uniform interfaces to internal and external developers, partners and customers, to help improve data exchange and transactions. In addition, APIs enable the open source community to create new functionality and value.

At your service

Microservices, whereby application functionality is developed as independently deployable services, enable organisations to experiment with new features and more rapidly respond to changes and disruption.

Microservices architectures still require integration capabilities such as transformation, orchestration and connection, so that data can be shared across multiple systems and services. An agile integration approach, taking advantage of APIs, containers, and distributed integration technologies, can be used to bring integration into the application development processes.

Changes to client-side functionality require equal flexibility on the backend. Using an integration platform, developers can more quickly create and scale lightweight integration services, based on APIs. Business workflows rely on core systems of record and supporting IT infrastructure. In addition to AI and IoT datastreams, the Intelligent Digital Mesh will still require data from back-end systems to power apps and help deliver business value.

Enabled by containers

With an increasing number of different applications running in an enterprise, from the newer AI, mobile, and IoT applications to the more traditional business intelligence, web, and other industry-specific applications, the delivery and management complexity can quickly escalate. This is where the role of containers and a container-based platform can come into play.

By deploying microservices in containers, independent development teams can deliver them. Container technologies are designed to eliminate bottlenecks in performance and facilitate agile integration that underpins independent app development and scalability.

As AI and IoT combine and users become accustomed to an increasingly connected and data-driven environment, apps can become subject to continuous updates and unpredictable demands for elastic scalability, often independently from one another. Containers enable the continuous development of lightweight, tested units of app deployment that can scale independently on demand. Most importantly, containers enable consistent version management of system units and provide portability for existing apps so that they can be deployed in different environments without too much retooling.

Embrace the mesh

As with enterprise mobility, successful implementations are more likely to be strategic rather than tactical. Organisations should avoid working in silos and view AI, IoT, data analytics and mobile developments as part of the overall technology roadmap.

Clare Grant

I expect the emergence of the intelligent digital mesh to help drive enterprises to adopt modern app […]

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Smarter circuitry instills intelligence and the Internet of Things into business and products

Modern electronics are omnipresent. Sometimes they’re front and center—like when we gawk over the breathtaking colors of a new Ultra HDTV. But more and more, they’re cleverly positioned behind the scenes—like when a smart thermostat turns down the heat after it determines that no one’s at home, or when sensors on an airplane wing identify a surface crack that maintenance crews can’t detect themselves.


Want to glimpse the future of electronics? Follow the data.

At home, in industry and in the outside world, our electronics are now shaping our daily lives, and in the next few years, they’ll do so in more powerful ways than ever. “Speeds and feeds” are no longer the driving force behind next-generation electronics. Enabled by the fast-growing IoT, it’s now about building products that work more intelligently, integrate with other devices and machines, and streamline our lives and businesses by automating tasks for us behind the scenes.

It won’t necessarily be faster chips and sharper screens defining the leading edge of electronics of tomorrow, but advances in artificial intelligence and machine learning that, when applied to the complex web of data spinning off all our “things,” will make sense of it all and enable a whole new marketplace of services and capabilities. Here’s a look at just a handful of those, and some ways our connected electronics will change our lives—and ourselves.

Machine learning applied to health and wellness

IoT sensors and other types of instrumentation are generating so much data so quickly that concerns about the glut of information overwhelming end users are rampant. Our machines will soon help make sense of all that information and turn noise into signal. Millions of people are scratching the surface of this concept today through technologies like fitness bands, which currently collect data on activity level, heart rate and blood oxygen, and report it back to your smartphone or other devices. But for now, most of that data is left to the user to interpret. As sensors get more sophisticated, watch for bands to offer AI-driven guidance on diet and exercise, and even watch for warning signs of potential diseases. The more data that the legions of bands on the market generate and upload (anonymously) to the cloud, the better these diagnoses will get.

Now extrapolate that idea to a national or international level. Could the CDC spot a pandemic in the making by noting body temperature spikes in certain world regions via algorithm? With conceivably billions of data points to process, it’ll take a mountain of processing power to make sense of complicated trends in real time. Looking further afield, one can imagine AI being used in conjunction with mobile drones to monitor key hotspots or even deliver medication with pinpoint accuracy.

A new vision for VR

The Internet of Things isn’t new technology any longer; we’re way beyond merely “talking to” things with embedded processors and wireless radios. The future lies in how IoT technology is leveraged within each of these technologies. Today, we have smart washing machines and smart thermostats, but we’re not far off from a day when smart refrigerators and smart stoves talk to each other, working in tandem with you, the homeowner, to get a healthy dinner on the table by telling you exactly what ingredients you need and when, and automatically reordering items when they run out.

The IoT means business

Meanwhile, in heavy industry, legions of sensors embedded into industrial equipment will soon reinvent—and automate—much of the job of service and support. From manufacturing plants to oil wells, technicians will arrive on a job site not with a tablet with manuals and charts, but probably VR headsets to show them exactly how and where to service a problematic machine, highlighting what components need to be replaced, even showing him which bolts need to be removed in order to make the repair. Dozens of internal sensors will feed data in real time to an AI unit in the cloud that in turn relays to the technician whether everything is running as it should. The upshot: quicker repairs and lower overall downtime.

“The ability to overlay data on real world images has many B2B uses, thanks to the growth of the Internet of Things,” says IBM’s Bret Greenstein, Vice President, Watson Internet of Things Consumer and Digital Business. “With systems like Watson, which can learn from and understand unstructured data, the ability to integrate the real world and virtual worlds will make VR even more powerful.”

Big data will make shopping extremely personal

Visit any online store you’ve done business with and you’ll likely be greeted by name and offered a selection of items chosen specifically to appeal to you. These items may be based on your past purchases, demographic data, time of year and any number of other variables, all of which collectively comprise “big data” as we’ve come to know it. But as everyone who’s been offered, say, some spicy lingerie after a single Valentine’s Day purchase knows, these algorithms can be blunt, and once they learn something wrong, hard to set back on the right course. Salvation lies in the form of hyper-personalization technology, where dozens of data points about an individual are exploding into hundreds or even thousands. Retailers are going to know an awful lot about you, though whether that works to the consumer’s benefit remains an open question.

The upshot of this will be the development of new technologies that will give consumers a greater ability to manage their own electronic paper trail—and progressive companies that integrate privacy protections into their business processes. As Greenstein explains, “emerging technologies like blockchain will give users a transparent, personal record of where their data has gone, and cognitive systems will help users to understand exactly how their data is being used.”

Today’s electronic technologies represent a mere taste of what’s to come. By truly understanding this dynamic market and consumers’ preferences within it, manufacturers can get ahead of the curve and find innovative ways to create value.

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