Using a DJI Drone to record house build

Using waypoints to make amazing drone videos.

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Drones provide an inexpensive, easy way to record from high above and far away with little or no training. There is no pilot’s license required for small but competent drones, but you do have to avoid no fly zones such as airports, certain municipalities, or harassing individuals. As a person who builds and fixes computing systems (technology, process, people) for a living and a person who tinkers with everything from computers to IoT to cars and boats to houses for fun, it was always my desire to build a house. I’ve been using my DJI Phantom 3 SE (no longer manufactured) drone to thoroughly document the build process.

Modern drones are relatively easy to fly. That doesn’t mean the pictures, especially video, will look any good. I took lot of ugly video at first. There always is the thrill of being aloft, which you can observe from your phone. The DJI Phantom 3 SE (my older drone) and newer drones use GPS or GPS+GLONASS, typically fly for about 20 to 30 mins, range 1/2 to 1 mile, record at 720p or 1080p, hover within 0.5 to 0.1m if you just let go of everything even in a stiff breeze, newer ones avoid objects, and fly at up to about 50 MPH.

I prefer a dedicated controller, but many can be flown from just a smartphone. Many  have advanced abilities to follow-you or at least the controller, circle a known point, do special effects, respond to hand gestures, or fly a pre-assigned flight path made up of waypoints.

Waypoints are your friend when making a video. The best way I’ve found to get a good video, excluding editing (not covered here), is to set a flight path via waypoints, save the mission, and then run the mission.  There are numerous youtube videos out that illustrate the process. I’ve included a video from DJI below to illustrate the process using my DJI drone, but other drones and drone manufacturers have similar abilities.

The real trick is when you run your mission is to set the “Head to:” setting to “FREE”. In head to mode FREE, you control where the camera points. So now you know the drone will fly the mission, not crash, and you can focus on pointing the camera. Shots always are more dramatic if you can move the camera on 3-axis. You already have motion, but you tilt up and down and pan side to side. You’ll get a pretty decent video without editing.

In addition, you can repeat the mission since it saved for you. By flying the same mission, you can see changes over time. In the case of my house build, I have flown around the home site in each stage of the build. I now have a video library I can check to see the house slowly being built.

Enough people have expressed interest in my house build in Florida that I am going to write a new blog on it. Once I get enough content, I’ll post the new WordPress site here.

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Looking at Salesforce & dreaming big

SalesForce (SFDC), more than any other SaaS company, has paved the way for SaaS as model for selling a business service underpinned by technology. SFDC understood before most that SaaS was not a new way to pay for software and software implementations, but a way to swiftly create value. No business wants to buy software, hardware, networks, computers, data centers, and IT people (gag! cough! expensive!). Businesses want buy solutions to their problems and enable more revenue and profit. All that other “stuff” which I personally care a lot about, is not the core of business.

I saw the following article in TechCrunch. It looks at what is right, wrong, and what are the ongoing trends base on SFDC.
There are a lot of important messages. I think older IT businesses found before the iPhone fail to understand or take advantage of the “the consumerization of IT” or the fact that “compute is very inexpensive”. On the other hand, a more established providers do understand need for  “enhanced security due to increased exposure” and “computing is location agnostic” (hybrid cloud). A lot of compute will grow outside of corporate data centers, but I don’t think corporate data centers will entirely disappear in the near term.
Under computing is cheap, I saw this little snippet.
“By comparison, at the same time that Salesforce was founded, Google was running on its first data center—with combined total compute and RAM comparable to that of a single iPhone X. That is not a joke.”  And 11 years before that I was in class with professor lamenting they paid more for 256 bytes of memory than we were paying for 256 kbytes of memory.
Around the same time (1988), I was reading an article that has stuck with me for 30+ years which I can’t find. It basically stated that at the time “X Windows System”  was developed, it ran so slow it was impossible to use (minutes to paint a scree), but that developers had confidence that the CPU, Networks, and Graphics would catch up – and they did. We’ll see this same pattern with AI, VR, Blockchain, etc. today.
The real lesson is go BIG when you are innovating. The computing, often driven by IBM (see Summit – worlds fastest computer with whole new architecture), has an amazing history of catching up and passing our wildest dreams.
So dream big and go innovate. There are whole new technologies being built to meet the challenge.
 

GitHub purchase by Microsoft

From my view, Microsoft bought GitHub for 2 major reasons – access and information. Access is the first reason and it enables an extension of their own tools and cloud. My assumption is GitHub will soon find the first option for tools and for cloud to be Microsoft’s unique line up. Why would a developer publish to AWS, Oracle, Google, or IBM if a single button press got you the latest features and tightest integration by going to Azure. They won’t eliminate or block the others, they’ll just make Microsoft the default.

I don’t think Microsoft is buying GitHub to bury it or ruin it. Microsoft is not exactly the biggest promotor of open source, but they are an active player. This is not like Gillette buying the stainless steel razor blade patent so they could drag their feet on producing one and get more money out of their existing products. If Microsoft blocked GitHub, I think the world would just develop an alt-GitHub or shift to competitor.

The second is probably the more important: information. GitHub is where developers, programmers, and coders dream. They put snippets of code which are glimmers of the future. Simply understanding what libraries, language, databases, tools, and clouds are being used, frequency, and in what combinations will yield bright headlights into the near future. If you release a new library, you can now easily see its uptake in the community. Put more money into it if it’s yours, alter yours to look more like the winner, partner where you can’t win, or buy it up if it’s a good investment.

As long as Microsoft uses a respectful hand and doesn’t become the evil overlord, I think the purchase of GitHub will yield a bounty of information by which they can steer their own development of tools and products. For a company that has jumped in late on the Internet, Open Software, and Cloud, they sure do an impressive about faces.

 

Digital Twin: the 2018 agile wind tunnel with quantum future

Digital Twins enable testing of real world testing of complex systems. The concept of living test lab has been dream for testers. Digital Twins are not static, but allow for constant new input based on the real world from IoT sensors. Digital Twins make use of AI, Machine Learning, and IoT to simulate complex system behaviors. IBM is working in our labs and with our clients to find exciting new ways to use and create digital twins.

When flight first started, a man had to risk his life to test each innovation. An innovation had a high threshold since the bet was a human life. Eventually, engineers built wind tunnels where they could simulate the effect of the air flow over the plane. While it no longer was risking a life, it had limitations on size (can’t fit an entire 747 in wind tunnel), was artificial, and was costly.  Also how do you simulate more complex events like sudden down drafts, lightening strikes, rough landings, wear and tear over years (metal fatigue, corrosion)? Now with digital twin, you can test the effect of changes to the digital twin of the airplane. We can run 100’s or 1,000’s of changes and combinations of changes to identify the impacts. Only the best of these changes will be put into use.

The while the changes put into use could be small, similar to agile built software application, they would add up to significant impacts. The feedback from the IoT devices in the real world will then update the digital twin allowing new sets of changes to be developed, deployed, and tested before the best combinations are rolled out in rapid succession. As most planes are now fly by wire and highly digital, incremental changes are possible to many of the systems. Today it might not be possible to reshape physical parts like wings, fuselage and rudders, but maybe in the future technologies could reshape the surface to change physical parts of the plane. Clearly there would need to be progression from test bed, to unmanned, to test flights before it went into passenger aircraft, but the rate of innovation in safety related industry goes up by orders magnitude and the risk and costs come down proportionally, too.

The ability to try millions and even billions of combinations in each digital twin is not yet possible as it would overwhelm the compute power of traditional binary computers. The rapidly evolving Quantum Computer may provide the power required to make machine learning nearly unlimited in capacity enabling deep learning and unlimited numbers of combinations of factors in our digital twins. You can even try out quantum for yourself in IBM’s DevOp environment – bluemix.

Benefits of digital twins can apply to almost any machine, group of machines, or ecosystem of lots of groups of machines. I wonder if in the future, a quantum digital twin could be more complex and subtle in its simulation than the real world. As of today, our models of reality pale in complexity to the real world. Below is simply mind map machine systems with a focus on transportation machines. It shows how digital twins can use data from other digital twins. It is model composed of multiple models.

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A network of machine ecosystems that can become digital twins

How could a digital twin help your industry? How can you take advantage of a digital twin to improve the quality of life and leverage the vast amount of data pouring out from mushrooming number of IoT sensors? It is an exciting problem to explore with real business implications.

Blockchain – enabling true digital transformation

Blockchain will significantly change how we hold and transmit items of value. The business process can finally be designed from the ground up as a digital process – truly transformed. The record of choice for the last 100+ years has been paper. Even when you scan a record, if the paper exist, it is the legal record.

We have birth and death certificates, laws, deeds, bank statements and even money (bills) on paper. The problem is we are becoming a digital society and paper is hugely inefficient. In addition, the processes for handling paper have stayed in place even with digital systems and are highly error prone. How likely is it that an error occurs upon copying or reading a document. Blockchain offers the opportunity for  processes to become 100% digital, secure, and low friction from birth to destruction.

The simplest definition of a blockchain is a digital ledger that is not terribly different from an old fashioned paper accounting ledger. A well implemented blockchain has 3+1 key characteristics. It is immutable meaning once a transaction is entered, it can’t be removed or altered. It is sequential in that each transaction is tied to the one before it and after it. It has consensus based peer nodes that can be distributed. I’ll add a fourth for a “well implemented” blockchain, that it has inherent security with multiple levels and is highly resistant to attack.

A blockchain is not Bitcoin or any single crypto-currency. Crypto-currencies like Bitcoin do run on blockchain technology. The data entered in the ledger for crypto-currency are financial transactions representing value. What fascinates me, and is the subject of this blog, is what else can you do with a Blockchain.

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In 3 recent experiences with obtaining a mortgages, I’ve had a 10%, 50%, and 90% paper based process. I’ll exclude the closing process which is still done on paper thanks to the government being nearly 100% paper based.

Bank 1 was 90% paper based. Everything went to the branch office as paper which they put in a box and shipped to the home office where it was processesed. Only the communication via e-mail was electronic.

Bank 2 was about 50% paper based. They allowed us to submit our documents via an upload, most documents were e-signed, and a few that presumably the government required wet-ink signed, we’d print, sign, and then upload them.

Bank 3, actually a mortgage service, never gave us a piece of paper, but I’d argue it was still only 90% digital. Someone was still transcribing from the uploaded images into the lender’s databases. Even if all of the paper was eliminated, Bank 3 still was working workflow designed for paper. It took limited advantage of the fact that everything was now digitized.

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Blockchain will change the above mortgage process. There will be no transcription and therefore less chances of error. Hypothetically, you’ll upload your information from a digital store on blockchain of IDs which will include multiple biometric authentication methods to confirm it’s really you. You’ll permission your lender to do research on your credit worthiness in various financial blockchains. It may even eliminate the need for the credit scores and credit bureaus as credit data can be gathered directly and relatively quickly (more on that later). At the same time, they will review your deed and other documents with the government making sure you are lien free.

All of the approvals, audits, and additional documents will be kept in the lending agency’s blockchain, but can link with permissions to other blockchain’s or simply make copies with reference to the source. Finally, your signatures will cause the down payment to be transferred along with the signatures of everyone involved from the bank, regulators, attorneys, auditors, county and state tax authorities, county court records, insurance agencies, buyers, and sellers. In theory, from discussion of the mortgage to the completion of the mortgage a day or few day process.

The biggest issue with blockchains, besides they are new and we are just starting to build applications for them, is that they are slow in terms of computer transactions. The slowness is mostly due to the consensus element. For all the nodes (computers) to agree it is valid entry, it can take up to a few minutes. While this is huge leap forward in terms of recording a legal records which can now take weeks or months, it far is too slow for sub-second transactions like purchasing on the internet or recording an entry at help desk. So for now, it is best applied to large block type transactions of higher value which fit the characteristics of blockchains.

Here are a few areas where blockchains are a natural:

  • Medical records (individual, hospital, doctor, etc.)
  • Government documents (deeds, judgments, laws, titles, licenses, etc.)
  • Financial documents (bank ledgers, investments, statements, etc.)
  • Supply Chains (farm to fork, inspections, transportation, etc.)

Where else might blockchains fit? What other technologies like AI might be integrated?

If you like to learn more about how you can build on the blockchain, IBM provides FREE tutorials on the Hyperledger, an open sourced blockchain.

 

If IBM Watson (AI) is so smart, why isn’t Watson able tell IBM how to make billions dollars?

“If IBM Watson (AI) is so smart, why isn’t Watson able to tell IBM how to make billions dollars? Can’t you just ask Watson how to make more money?” It was an earnest question from a skeptical client. We all want an oracle we can ask.

I answered “IBM Watson can’t just know how to make money. It has to be taught first by humans. A person must teach Watson the knowledge and then Watson can expand on it.” The simple answer is IBM Watson is similar to all Artificial Intelligence (AI) tools. It is just a tool and not an all-seeing, all-knowing oracle. Buying a chef’s knife does not make me a chef. The old saying is “a fool with a tool is still a fool.” Watson, or any AI, can’t just imagine ideas, create new solutions, or create new solutions. While it isn’t an oracle, it is highly useful tool.

The real purpose of this tool labeled as Artificial Intelligence, Cognitive Intelligence, or Assistive Intelligence is to provide computers with more human like interactions and understanding. Reading, writing, speaking, listening, seeing, and feeling are very human experiences. We define our world this way via our senses and sense of self being. At IBM, we have Watson focus more on the cognitive (thinking and feeling like a human) and being more supportive via assistive intelligence. The cognitive capability provides the computer a better and more natural way to move, communicate, interact, and learn in our human focused world.

A good example is Watson Cancer Diagnostics. It first was taught how to diagnose and treat cancer. The cognitive capabilities allowed it to speak, listen, write, and read both questions and answers. I even learned to read radiographs (visual). That gave the solution a baseline capability. Now it is moving onward by reading printed journals. We as humans think of it as nothing to extract information out of reading a book, but this is unstructured data which only a few years ago, computers couldn’t understand. Now with Watson, they can. Today Watson Cancer Diagnostics can work with doctors and suggest treatments, but ultimately, we still rely on the doctor to make the final diagnosis and treatment.

Water is the universal solvent. Humans are the universal problem solver. Computers are wonderful tools to enable humans. By adding cognitive capabilities, computers become even better and easier to use tools to assist us in shaping our world and hopefully for better.

 

Move, Adapt, or Die

Change is eternal in life, nature, business, and technology and you only have 3 options:  1) Adapt; 2) Move, or 3) Die.  I learned this truism in my 7th grade from my social studies class regarding animals response to ecological change, but the same is true for changes in our business environment.  The technology environment has forever been changed by CLOUD (IaaS, PaaS, and SaaS).  The software business and the systems integration (SI) will never be the same and is now presented with 3 simple options: 1) Adapt; 2) Move, or 3) Die.

As humans, especially business people, engineers, etc. who populate a lot of technology field, we believe we can overcome or stem the tide.  While this may work for short term or against small storms of change, it will not defeat real, substantial change any more than you can push back on walls of water from hurricanes.

IBM recognizes the power and importance of Cloud, even if it got off to slow start. Look at the emphasis. Less than 10% of IBM’s revenue is now from hardware. At the same time, everything from IBM is now on the cloud. IBM is even beating back its latest foe – Amazon Web Services (AWS). IBM Beats Amazon In 12-Month Cloud Revenue, $15.1 Billion To $14.5 Billion.

SAP has made a massive shift around SaaS and is adapting.  In 2013, Jon Reed, noted that even SAP executives would love to go on selling traditional on-premise perpetual licenses when he paraphrases the executive with ‘Hey, if we could continue to sell software to customers the way we’ve sold it to them for the last 40 years, we would. But they want new options.’  (more from Jon Reed’s Diginomica blog). Fast forward to 2016 and about 80% of SAP’s revenue is from 4 acquired SaaS products: SuccessFactors, Fieldglass, Concur, and Ariba. If SAP could figure out S/4 HANA cloud, they might even become a dominant SaaS ERP player.

Cloud and specifically SaaS to the software industry is a category 5 hurricane force of change driving a wall of water.  Remember when virtualization was only for non-proction. Now, most systems depend on virtualization.

Moving and adapting take time. So while almost everything will go cloud, it will take time. It will have to make IT and financial sense to move. The argument that some applications will not run well on the cloud will be a moot point when they are rewritten for the cloud.

The hurricane of cloud  in all forms is coming here. What are you doing to make sure your ready to move or adapt (and not die).