TG Tech Briefs: Stories Worth Sharing for Week Ending February 28, 2015

Some recent tech stories that I find interesting and worth sharing.

12 Emerging Trends that Everyone Missed at CES Thomas Frye always has a unique and sometimes far-out perspective on things. For those interested, Frye’s DaVinci Institute is a local organization that hosts speakers and events for the geek-crowd. I’ve attended a few of his events, and they are affordable and usually interesting. Check them out.

Portable Battery Pack Market worth $11 Billion by 2020 The portable battery pack market is projected to grow by 20% per year for the next 5 years, $11B. Because this such a big market, we need to be realistic and accept that we will ride the coat-tails of other people’s technology and R&D investments.

Global Asset Management, 11 Years On This is a fun retrospective on what’ changed in battery-powered asset tracking over the last 11 years. What hasn’t changed? Battery technology for the most part.

Indoor Location Market worth $4.4 Billion by 2019 Here’s a sister industry that flies under the radar, but is 10 times the size of the criminal justice tracking market. The "Indoor Location” market is largely focused on retail, track and trace, and emergency management applications using tag-based, RF-based, and sensor-based technologies.

Speaking of indoor location, have you ever wondered why there is not a terrestrial or ground-based equivalent to the Global Positioning System? I have, and it turns out that there are two companies in the US developing such systems: UrsaNav and Locata. Such systems could reduce dependency on satellites (which can be taken out) and drastically improve location fixes indoors and other impaired areas. Only time will tell if these systems come to fruition.

TG Tech Briefs: Stories Worth Sharing for Week Ending February 21, 2015

Some recent tech stories that I find interesting and worth sharing.

Top Hacker Exposes Home Detention Bracelet Flaw A computer hacker in New Zealand has demonstrated how electronic monitoring bracelets can potentially be fooled by "spoofing". At a computer security conference, he demonstrated how a bracelet could be wrapped in foil, preventing it from reporting its location, then the signal mimicked by a laptop using a $500 transmitter and some custom software. What we don’t know is how knowledgeable this hacker was about the product he spoofed. Will demonstrations like this become more common as the electronic monitoring industry comes under increased scrutiny?

Newest US GPS 2F-8 Satellite Goes Active The fourth modernized Global Positioning System satellite launched this year has completed in-orbit testing and joined the constellation. The Boeing-built Block 2F series of a dozen spacecraft offers advanced atomic clocks, stronger anti-jamming, a new third civil signal, and longer design life. Three more GPS satellites are scheduled for launch in 2015. It’s nice to know that our GPS constellation is being upgraded on an ongoing basis.

Laser-Radio Links Upgrade the Internet This way-cool technology uses parallel radio and laser links to move data through the air at high speeds, in wireless hops of up to 10 kilometers at a time. This is being pitched as a cheaper and more practical alternative to laying new fiber optic cables, and is in trials with three of the largest U.S. Internet carriers. It is also being rolled out by one telecommunications provider in Mexico, and is helping build out the Internet infrastructure of Nigeria.

Wireless Gadget Recharging with Sound Waves Here’s yet another addition to the dozens of battery charging technologies under development. Under this approach, sound vibrations are harnessed from the air using piezoelectric transducers, which in turn convert that mechanical energy into electricity. This is all very theoretical at this time… a true R&D project, but interesting nonetheless.

TrackR Bluetooth Tag Sold with Luxury Designer Wallet at Macy’s Retailer Macy’s is now selling a $100 leather wallet from Royce Leather together with a Bluetooth tracking tag from TrackR to help locate the wallet if it gets lost. I thought this story was interesting not because of the technology (which is impractical for “true GPS tracking”) but simply because it illustrates how ubiquitous location-based services are becoming across so many different products. People generally understand the concept of location tracking, and I think that makes it more acceptable to society as a whole.

A Map of Every Device in the World That's Connected to the Internet This is just one those interesting pieces of info that seemed worth sharing.

TG Tech Briefs: Stories Worth Sharing for Week Ending December 20, 2014

There have been lots of stories over the past few weeks about wearables and sensor technology.

A New Chip Could Add Motion Sensing to Clothing A company called mCube has made a new kind of accelerometer that is small and cheap enough to lead to smart electronics in clothing and sports equipment.

First Look at Simband, Samsung's Health-Tracking Wearable of the Future & The Apple Watch May Solve the Usual Smart-Watch Annoyances Samsung’s new health tracker is equipped with six sensors, and its modular design means developers can add their own proprietary sensors as well. The six sensors it comes with can keep tabs on your daily steps, heart rate, blood pressure, skin temperature, and how much sweat your sweat glands are producing. The blood pressure sensor is a photoplethysmogram (PPG) sensor. The Apple Watch also has a PPG sensor.

Sweat Sensors Will Change How Wearables Track Your Health Researchers have discovered that perspiration may carry far more information and may be easier to stimulate, gather, and analyze than previously thought. This electronic sweat-patch uses paper microfluidics to wick sweat from the skin through a membrane that selects for a specific ion, such as sodium. Onboard circuitry calculates the ion concentration and sends the data to a smartphone. The electronics within the patch are externally powered, as in an RFID chip.

More Than Skin Deep & Artificial Skin That Senses, and Stretches, Like the Real Thing Both of these stories are about a thin, stretchable material that in which sensors and electronics can be incorporated. Making electronic devices that are skin-like will ultimately allow us to intimately integrate very advanced semiconductor technology and sensors with the body.

Radio-Controlled Mouse Hints at New Diabetes Treatment In this fascinating research at my alma mater Rensselaer Polytechnic Institute, mice were made to respond to a radio signals by releasing insulin. One day this might allow people with type 1 diabetes to use an app on their phone to alleviate their disease at a cellular level.

Finally, being in the electronic monitoring industry for criminal justice, as well as from Colorado, I get asked lots of questions of about marijuana detection. There are few press releases popping up about marijuana breathalyzers, such as this one from Washington State University and this one from Lifeloc. These stories are high on promises but low on details. What’s not stated is that concentrations of delta-9 THC in breath are so low that there is no reliable sensing technology outside of traditional, lab-based chromatography. My opinion is that this is a really a law enforcement issue; not an electronic monitoring issue. THC does not readily disappear from the body, so there are many reliable ways to determine if somebody has recently used marijuana. But there is no reliable chemical test to determine if a person is under the influence of pot right now, and I don't see one coming for some time.

TG Tech Briefs: Stories Worth Sharing for Week Ending December 13, 2014

Here are the latest product development and technology news that I find interesting.

New Smartphone Battery Goes From Dead To 70 Percent Charged In 2 Minutes,Scientists Say This team of researchers in Singapore have supposedly developed a way to charge batteries quickly by replacing the graphite normally used in the battery's anode (negative pole) with a gel made from titanium dioxide. They have applied for a grant to build a large-scale battery prototype for electric car tests, and say these new batteries could reach the market within two years.

New iPads Come with Special, Multi-Carrier “Apple SIM” & Apple's Quiet Attempt to Shake Up Wireless Carriers Could Benefit Us All Have you heard about the new “Apple SIM” that comes with latest iPad? It’s a software programmable SIM, meaning you can change carriers without swapping the SIM card. Participation is limited now, but Apple is trend-setter, so I imagine that we will all be able to advantage of such a SIM 2 or 3 years down the road. This could have a huge impact on how cellular carriers compete for business!

Gartner's Top 10 Strategic Technology Trends for 2015 There’s nothing earth-shattering, or even surprising, on Gartner’s list if you follow technology… but the concept of software-defined infrastructure is quite intriguing to me.

The'Internet of Things' Will Be The World's Most Massive Device Market And Save Companies Billions Of Dollars The growth in mobile computing and the Internet of Things (IoT) continues to amaze me... a projected 6.7 billion connected device shipments in 2019! (Yes billion, with 9 zeroes.)

Finally, I found the chart below from MIT Technology Review very surprising and worth sharing. This one chart provides great insight into the whole Net Neutrality debate, and explains why a few companies who need tons of bandwidth will be more than willing to pay-to-play. The impact, if any, on small users like us remains to be seen.

Measuring Product Development Productivity

I've recently been involved in a number of discussions about how to measure product development productivity, and I thought this was a great topic worth sharing. I've wrestled with this topic for much of my career, and have developed some pretty strong opinions on the subject.

First, I am not in favor of what I think of as "easily quantifiable but hollow metrics" such as lines of code, number of work items, number of drawings, number of ECOs, etc. Why? Because these measure effort and not results, and they may have little relationship to the success of the business. Remember, the whole purpose of product development is to help a business accomplish its goals. There are teams that can crank out tons of code that does not help the business in the least. Inversely, some teams may produce things that really matter to the business with a much smaller code base. Which team would you rather have?

Therefore, product development metrics need to be related to goals that are important to the business. These goals probably have something to do with increasing profits, revenue, or market share by introducing new products and features, but there are many other possibilities. Coming up with such metrics is admittedly easier said than done.
Here are two metrics that I have evolved into to over time:

1) Revenue from new products introduced in the past three years. This is pretty easy to measure and can be tailored to for any business. Perhaps it's 1 year instead of 3. Perhaps revenue is replaced by the percent of end-users who use new software features released in the past year. You get the idea.

2) ROI from development effort. This is much more complicated. Actually, the "I" part is pretty easy, but the "R" part can be tough; it will require debate and agreement among various stakeholders. This is also a long-term metric, as large projects may take years to produce any ROI at all.

I'm interested in your thoughts and comments. What metrics do you use?

The Half-Empty Promise of Big Data

Anybody who works in a high-tech industry or product development knows that “big data” is one of today’s hottest buzz words. As I sat through numerous panel discussions and education sessions at a technology conference last week, “data mining,” “big data,” or “analytics” worked their way into almost every talk, no matter the subject. The typical context was that “big data is the key to solving this problem,” or “Data mining is the new Holy Grail in our industry.” Except in many cases these expectations are probably unrealistic.

Data mining is the analysis of large quantities of data to extract previously unknown interesting patterns and dependencies. Conventional thinking is that we can now mine mountains of data generated in our increasingly connected world, piece together important relationships and amazing connections that we never knew existed, and change the world. Or so they say. As a quantitative number cruncher and data geek, I see the potential.

But I also see a big pitfall in this thinking which is rarely talked about. Quite simply, most data being collected is simply not that useful. It's mundane personal data (locations, what websites a person visited, what purchases they made), and mining large sets of mundane data will produce some rather humdrum results at best. As an example, consider the shopper club cards used by most grocery chains. After analyzing billions of purchases by millions of people over the past two decades, what have the stores learned? That some people buy Pop Tarts in addition to flashlight batteries before a big storm. Interesting? Perhaps. World changing? Hardly.

The best applications of big data that I’m familiar with do not entail data mining at all, which has become a buzzword, and gets misused to mean any type of large-scale data analysis. For example, predicting flu outbreaks real-time based on citywide emergency room visits is a great use of big data that has both health and economic benefits. But it's not data mining. It's just plain old data analysis, with certain input variables that are predictive of an output variable. There is nothing unlikely or surprising about these relationships, but we are now able to query data in real time from sources that were previously unavailable or unconnected.

There are many great uses for big data, but people in high-tech industries and product development have developed unrealistic expectations, particularly for data mining. Most data being collected is simply not that useful, and this leads to the half-empty promise of big data.

Predicting Mash Efficiency in an "Igloo-Style" Homebrew System, Part 2

As follow-up to the last blog entry, I’ve updated my mash efficiency prediction model with 6 more batches of beer, doubling the sample size. Variables were described in the previous article, and I also added a new variable called "Experience," which is really just the batch number on my new system. All input variables and the resulting mash efficiencies are shown in Table 1.

I analyzed the data using the same ordinary least squares regression (OLS) technique described in Part 1, but this time the resulting model was highly predictive of mash efficiency. OLS results are shown in Table 2, where it's seen that the most significant variable by far is Experience on the new system, as the magnitude of its t-stat is much larger than any of the others. Grain Crush is also significant, and Average Mash Temperature is approaching statistical significance. (As a rule of thumb, a t-stat whose magnitude is 1.96 or greater indicates statistical significance.)

Using the coefficients from Table 2, I built a mathematical model for mash efficiency,

and the model's predicted mash efficiencies are plotted against the actual mash efficiencies in Figure 1. In a perfect model all points would lie directly on the diagonal line, and this model's points, shown by blue diamonds, are very close to that line, providing visual support that the model is very predictive. In fact, the adjusted R-squared of the model is 0.89, which is outstanding and essentially means that the model accounts for 89% of the real-world variation.

My conclusions from this experiment are as follows:

1. It took a lot more batches than expected to start achieving consistent mash efficiencies. With the exception of the sixth batch on my new system, where I presumably got lucky, it took a surprising ten batches before results started looking repeatable. I don't know exactly what caused my learning curve, but I presume it has to do with sparging method, transfer times, stirring technique, and other "brewing moves."

2. When starting to brew on a new system, use the same mash thickness, mash temperature, and mash duration every time until you start to achieve consistent results. Until then, the effects of these variables will be imperceptible within the "noise" anyway.

3. Much of the brewing science and theory homebrewers consume is applicable only after you're able to achieve consistent mash efficiencies. On my last three batches I've finally averaged about 87% efficiency with an overall variation of less than 5%. If I can keep this the same for the next three or four batches, I may start to experiment with mash thickness, temperature, and duration again.

Overall, many homebrewers like myself enjoy the science aspect of this hobby, and can sometimes focus a bit too much on recording numbers out to third decimal place. But until your process is controlled enough to achieve consistent mash efficiencies, none of this really matters. Such control is harder to achieve than expected when using an "igloo-style" homebrew system, but keep aiming for it!