Using a DJI Drone to record house build

Using waypoints to make amazing drone videos.

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.
 

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.

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).

 

Terrific Practical 10 step path for success with Analytics from Jerry Kurz.

Thirty years of experience talking. Worthy of 15 minutes of your time.

Folks, I am very proud and happy to have my dear friend Jerry Kurtz do a guest blog on my site. Jerry runs the Cognitive and Analytics businesses in my portfolio, and is a long time IBMer. He has been in this field for 30 years across SAP, Managed Business Process Services and Analytics and […]

via And Jerry Says : A Path to SUCCESS with Advanced Analytics — Vijay’s thoughts on all things big and small

WordPress vs. LinkedIn

Which site is best for business blogs? I prefer WordPress’s powerful editing tools. I seem to get better “following” on LinkedIn. What is your advice, comments, suggestions, or ideal solution?

WordPress is a content management tool service that is excellent tool for writing blogs and creating consistent, stylistic web pages. It has basically eliminated much of the need for IT departments to create standard variable content for their websites. For example companies like CNN, Forbes, Vogue, MTV news, The Rolling Stones, Facebook , NASA use it to create content for their websites. There are 17 blog post every second of every day from WordPress and it’s wired into everything with over 45K plugins. All of this comes from a company with 449 employees.

Alternatively, LinkedIn blogs are simple with a single style sheet, text, pictures, and video. It is more of an expanded status than a blog and definitely not a content management service. LinkedIn is popular with over 500M users with about 40M being students. That is an impressive journey from being 4,500 members in 2003. LinkedIn is big with over 10K employees in 30 cities around the globe and providing 24 languages. They’ve made a long journey from being just “business Facebook.” That doesn’t even include the impact from the Microsoft acquisition.

I liked LinkedIn because their blogs seem to get the most notice and response. Even when I link my WordPress blogs to LinkedIn, they don’t get the same notice. I think it is because WordPress blog looks no different than any other web link on LinkedIn. I like WordPress because it is a great writing and content tool. I like having my own style, colors, indexes, and other features. For me, the ideal solution would be to have WordPress as the blog engine inside of LinkedIn. Maybe it’s a plugin that I just haven’t yet found. Something else for my “to do” list.

What do you suggest?

References below:

LinkedIn: About LinkedIn

WordPress Online Support: WordPress Interesting Facts

SkillCrust: WordPress Facts

Forbes: Microsoft acquires LinkedIn

Grammar saves lives & numbers can hurt

Pasta should be cooked in salty water even if the numbers say otherwise. Olive Garden in order to get lifetime warranties on their pots, eliminated salt in the water  and they still don’t salt the water as of today (April 2016). As a decent cook, and others agree, you need salt in the water if you want the pasta to taste good. Only some junior analyst who thinks Olive Garden is the pinnacle of Italian food would think saving about $80 a year, the price of pot or the loss of 3 customer meals, would have no impact. Plus to cover the lack of taste in the pasta, you have to add more salt and sugar, often corn syrup in commercial products, to the sauce.

When we use numbers, we need to make sure the numbers, analytics, or metrics correspond to a meaningful output. I’ve seen consulting companies cut consultants to increase savings, not recognizing that if you have fewer consultants, you’ll have less revenue since consultants are the product. In a classic case, the US government made selling ice cream and visits to beaches illegal in an effort to stop polio.  The increased ice cream sales and visits to the beaches was due to the heat. The same heat that enables the polio virus to stay alive long enough to  spread.

At SAP TechEd a few years ago, I watched with fascination as Nate Silver kept telling the interviewer that the thing we really needed was to have highly knowledge analyst who understand the complexity of real life topics – actual experts. The interviewer kept wanting him to expound on SAP tools, but Mr. Silver held his ground. It is not the tool, the metrics, or anything that is technical. Some tools are better or easier than others, and SAP has some great tools was all he’d say, but paraphrasing the interview, he said “you have to understand the subject,  the relationships, and why a number might go up or go down”. Once you know the basics of the real system, you can use the numbers to look deeper, but not until.

If grammar can save lives (“let’s eat, grandma” vs. “let’s eat grandma”) then analytics can ruin them. Many decisions, such as layoffs or substituting equivalent products, are made on the basis of numeric analysis. As responsible analyst, we must make sure our metrics of success, failure, and our discoveries makes sense. Does the data really explain the results? Is it reasonable? What is scientific, logical reason for the outcome?

As we make more data available online and accessible, we must make sure it is clear what the data represents. Finally, we have a duty to be ardent guardians of proper use of analytics and be aggressive prosecutors when others misuse data and analytics. Numbers, and the conclusion we derive from them, directly impacts people’s quality of life. Number’s can hurt.