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Our Transformation is deep inside where we said we would never, never, go. We all need more information and discussion to successfully navigate our new never. You are never coming back once you transform.
Our last chapter we talked of catching and igniting our future from the tossed torches of transformation while at the same time not getting burned. Give that chapter a quick read or reread as never never is where these torches are landing.
No one can ignore that transformation's fire is in the air.
This chapter is about navigating the new never never, a virtual remoteness where transformation of everything is possible. Where we and no one else have ever been before.
Let start here, an article from Harbor Research on the End of the Era of Monolithic Apps:
Welcome! Your company is now a decentralized ecosystem!
The modern business enterprise has been deconstructing for decades. Companies used to develop the logistics, tools, and processes they needed right inside their four walls.
Today, no one thinks of a company as bound by the four walls of a building. Companies are ecosystems now, value-delivery networks consisting of a disassembled set of business functions and entities—some owned directly, many sub-contracted, but all requiring orchestrated data and information.
The days of monolithic applications are over. Microservices are the new way to develop, consume and manage applications. At the same time, because enterprises have diverse users, functions and entities, all with an overabundance of data flows and interactions, they need optimized tools to orchestrate the value presenting itself. Two critical forces are at work underlying this shift:..
This article from Forbes.com by Marcus East, Brand Contributor for Google Cloud, Rethinking Building Construction And Maintenance, With Help From The Cloud contains an important quote from William Ruh, CEO of Lendlease Digital:
Lendlease believes the future of the property industry revolves around leveraging the cloud and sensors to provide a digital twin of a physical building—before the building is even assembled—that can be modeled, explored, and analyzed using Google Cloud’s artificial-intelligence-based data services.
The insights provided are wide-ranging, from offering ways to cut overall energy consumption to improving safety and productivity. “The next phase of innovation is centered around autonomous buildings, using AI to automate the construction and operation of a building in a more holistic way.
This tweet from UIB (@uibglobal) advises customers that want their questions answered, issues addressed, and appointments scheduled quickly and without hassle should look to ChatBots for the answer.
That insight leads to this article from support function to growth engine: The future of AI and customer service. by MIT Technology Review Insights. Key passage:
In a February post, Gartner predicts, “By 2022, 70% of customer interactions will involve emerging technologies such as machine learning (ML) applications, chatbots and mobile messaging, up from 15% in 2018.”
Today, advancements in AI and machine learning are enabling deeper levels of customer engagement and service than ever before. Powerful and trainable algorithms can parse through massive amounts of data and learn patterns to automate and assist customer service processes. This technology is changing the face of customer service and helping organizations understand customers’ needs—often before they even do—providing the service they need at the right moment, says Jayesh Govindarajan, vice president of AI and machine learning at Salesforce.
This LinkedIn post has the full video for the latest Monday Live! discussion on the future of BAS distribution.
Convergence is a large part of our transformation. This article from Brian Turner CEO at Buildings IO, Inside Buildings IOT’s Ontology Alignment Project (OAP) talks about the convergence of Haystack and Brick, and the hope among many data-hungry people that a clear standard will emerge. Key quote:
When Google released the Digital Buildings Ontology, some questions began to surface. Why would Google do this? Why didn’t they use Project Haystack? Or Brick? I discussed possible answers in my article in September. Now, the biggest question is how do we take advantage of all the work that has been done by Project Haystack (Haystack), Brick Schema (Brick), and Google to make building data more accessible, and ultimately enable more intelligent buildings and smarter building management?
This article, Crabs in a Pail, by William Behn, President of Tosibox Inc., has a request for alignment:
As an outsider and interloper in the Building Automation vertical, it’s been interesting to compare and contrast BAS to other verticals embracing industry 4.0.
I wonder what would happen, vis-à-vis the severe labor shortage in your (our) industry, if the MSI community understood the value of creating new standards in their go-to-market strategy instead of relying on what we learned twenty years ago, thereby “teaching” facility managers and building owners what could happen with modern technology and a few well-executed investments.
For an industry becoming more relevant than ever with the pandemic, I wonder what could happen if the value chain were more aligned on a modern approach to everything… and I wonder if we don’t align, how long before someone “aligns” it for us?
This article on biometrics and access control, The Future of Access Control in Automated Buildings, by Imran Anwar, staff writer at Swiftlane, is (literally) in your face:
The coronavirus pandemic has disrupted the world and made safety more important than ever. Employers are now responsible to provide healthy and safe workplaces and many are looking to access control solutions to do just that…
Biometric access control involves the use of the individual’s biological data to allow or deny access to a facility or certain areas of a facility. The types of biometrics most commonly used for access control include:
Facial Recognition
Facial recognition technology makes use of artificial intelligence and computer vision to read and recognize faces. The facial recognition access control systems include a face reader that captures the face of the subject, converts it into a digital signal, and sends it to a cloud-based or on-site server for matching with authorized face credentials. Access is granted if the presented credential matches the stored credential and denied if there is no match.
Iris or Retina Scanning
A retinal scan identifies the most unique pattern of blood vessels in a person’s retina. It is performed by casting an invisible beam of low energy infrared into the person’s eye when they look at the scanner. The major limitation of retinal scanning is that the person has to focus on the scanner’s eyepiece from about three inches away. This biometric technology is rarely used for building or office entry, but is often deployed at high-security facilities that only a handful of people are authorized to access.
Fingerprint Scanning...
Enjoy your journey navigating the new never never — "Where no man has gone before.”
Ken Sinclair | Editor/Owner/Founder
Ken Sinclair has been called an oracle of the digital age. He sees himself more as a storyteller and hopes the stories he tells will be a catalyst for the IoT future we are all (eventually) going to live. The more than 50 chapters in that ongoing story of digital transformation below are peppered with HTML links to articles containing an amazing and diverse amount of information.
Ken believes that systems will be smarter, self-learning, edgy, innovative, and sophisticated, and to create, manage and re-invent those systems the industry needs to grow our most important resource, our younger people, by reaching out to them with messages about how vibrant, vital and rewarding working in this industry can be.