Posts Tagged → Internet of Things

Does Amazon Know What’s In Your Bank Account?

I watched a marketing webinar last night.  

It was free.  Typical of that genre, the point was to give away some information but sell you on a product or service that will give the rest of the picture.  That seems a good trade off considering their time and effort put into the creation of the webinar.  In return, learning from their experience made my time and effort watching it worthwhile.  That’s a fair market return.

Amazon knows what’s in your bank account 🙂

The presentation wasn’t interactive other than the pop up order form at the end.  So it was basically a recording, once produced it can be repeated with only the additional broadcast cost.  From what I can tell, it is played twice a day, most likely for a “limited time.”  The product being sold is more of the same information.  More extensive knowledge and examples are digitally boxed for download. Some level of customer service is implied.

For me, it potentially could be a good product.
The topic – Marketing – isn’t my strong suit, so I make an easy, albeit skeptical, target.  I might have bought it … but the price was a bit more than what I would spend.  I have a technique for shopping where if I like something enough to want to purchase it, I mentally calculate what it is worth – to me.  The process includes thinking about my bank balance, the relative “need” for the product or service, how long it will last, will it pay me in return, alternative resources that may or may not do the same things for more/less time and/or money.  The final consideration is Quality of Life  – will I be happier/faster/slower/better for having purchased it.  Whether a house or a pair of shoes, I scramble all that data to run it through the gonkulator that is my brain and contrive a cost I am willing to pay.

Then I look at the price tag.

Marketing & Economics 101

Ah price point – where supply and demand meet the wealth of nations. Wrigley made a fortune from penny sticks of gum.  Today’s $.99 ebook downloaded a million times is close to a million dollars (depending more on its one time set up cost.)  On the other end of the spectrum, the multi-million dollar yacht salesman needs 3 to hit the annual sales target.  One puts him out of business and five will hold over for another year.

Adam Smith touted that without the tethers of government interference, private monopolies, lobbyists or “privileged” entities, the free market wields the perfect price where supply and demand meet.  When banana crops fail, the price of those that make it to market goes up enough to meet whomever is willing to pay for more expensive bananas.

I’m sure he would have been spellbound by the much more elaborate threading of airline flight tickets.  An incredibly (I don’t use that word lightly) sophisticated algorithm cultures those seat prices like a mother hen, sub-minute by sub-minute searching databases and optimizing just how much the seat should be priced. Would Mr Smith’s contemplations and calculations hold under the intense smoothing of the pricing integral?  His theories have been smeared all of the earth with both creamy taste and reputed disgust.

He would’ve been further floored with the near-zero production costs of electronic products and services, although I’m sure he’d have much to say on it.  These are the elements of economic evolution that test free market capability in a global economy.

Big Data Price Point

Of course, you probably wouldn’t be here reading this unless you’re more interested in Big Data than my spending habits.  This is hardly business continuing education credit either.

But these “small” data examples are all market driven.  The future – the Big Data Price Point – is the price will shift according to your ability as much as willingness to pay.  That means the webinar product that I didn’t want to pay $497 would have been further discounted to the $247 that would have made me uncomfortable but ready to use my credit card.

How is this possible?  Supply and Demand.  For one, it is a product with almost zero production cost.  Unlike the widget  which requires materials, labor, manufacturing, storage, and distribution.  The digital warehouse doesn’t need a water supply or a janitor.  The one stored copy (and backup) replicates instantly.  There is a set-up cost; the knowledge must be conveyed creatively.  People are needed to develop the product which must be marketed and maintained.  The elegance of the digital effort minimizes the cost as the theoretical sales count grows infinitely.  This is not a scenario Mr Smith would have anticipated.

 As for demand, Big Data Price Point (PP) kicks in by knowing YOU along the same lines I mentioned that I use to make a purchase.  Big Data PP would figure out if I have enough cash or credit for the sale.  Big Data PP knows if I spend money on these types of products already.  Big Data PP knows whether this fit my spending lifestyle or if it is a reach.  Big Data PP determines if I can or cannot deduct it as a business expense.   Even more so, Big Data PP calculates whether I need deductions at this point, against how many deductions I have already accrued in my fiscal year.

Big Data PP will charge me a different amount than the next sale to a different customer.  An entity with a bigger bankroll may get charged more, or they may be offered a morphed package of sales for services I cannot afford:  X downloads, unlimited downloads, additional webinars or custom services.  

That’s not fair!

The same product is sold for different prices – because of how much I make?  Well … yah.  Want to write your Congressman or call your attorney?  Think again.

Buy now!!

Google (of course) is already doing it

And there are others.  As early as 2000, Amazon was “price testing” multiple prices for the same DVD.  They took some heat when consumers found out, so they dropped the practice (as well as the price.)  In 2005, dynamic pricing came into play again when a University of Pennsylvania study noticed prices differed according browsing history – someone who had shopped competitors would get the more competitive price.  In 2012, the Wall Street Journal reported how Orbitz ‘s offerings priced up to 30% higher for Mac users – Mac users have a higher income average.

Although the level of complexity may be surprising, we have become accustomed to cookies and their impact on our experience.  Most don’t appreciate the impact though on the bottom line in the shopping cart..  The Atlantic explains:

the immense data trail you leave behind whenever you place something in your online shopping cart or swipe your rewards card at a store register, top economists and data scientists capable of turning this information into useful price strategies, and what one tech economist calls “the ability to experiment on a scale that’s unparalleled in the history of economics.” –

The price of the headphones Google recommends may depend on how budget-conscious your web history shows you to be, one study found. For shoppers, that means price—not the one offered to you right now, but the one offered to you 20 minutes from now, or the one offered to me, or to your neighbor—may become an increasingly unknowable thing.

https://www.theatlantic.com/magazine/archive/2017/05/how-online-shopping-makes-suckers-of-us-all/521448/

I’m going to need to see your zip code, ma’am

Physical or virtual, cost of living has always been tied to location.  You can expect prices to be higher in New York City vice Greenbow, Alabama.  I’ve known friends who won’t shop the grocery stores near their house because they are reputed to have higher prices.  Then there’s the contra-pricing.  I live in a resort area and to help out those of us who “suffer” through the throngs of vacationers to live the other nine months in peace, there is “locals only” pricing.  That includes parking, some attractions and often secret pricing whispered over the phone ordering pizza or with the cashier for lattes.

Around the World

All the way back in the physical world, in Kenya most shopping is done in the very personal, one on one basis.  Outside the upscale Village Market shopping mall in Nairobi, the Masai Market meets weekly in an open lot across the street.  Advertised as an artisan fair of sorts, the goods are nevertheless likely to be found in a variety of souvenir shops anywhere in the country.  It’s the experience though, another country’s version of selling what makes them unique.

I was excited.  I was looking to find perhaps practical items to bring back home to share this lovely country’s culture.  I was accompanied by a local.  Although well-practiced at haggling from many countries around the world, I would need his native language and color to get a decent price.  Otherwise, I would get the “mzungu” price, their understandable upcharge for an American, which I deserve.  I didn’t expect to pay the same price as locals but I couldn’t afford the inflated price.  The average monthly wage in Kenya is $76.  Pricing is relative – to my location, my income, my nationality, my experience (traveler, savvy, job, education, common sense).  I should pay more but not more than what the gonkulator tells me.

In the cloud

Where you live is already calculated in your costs and the virtual world does not provide escape any more than it does anonymity.  My daughter realized a typical price difference phenomena when she went to college.  The prices she knew from shopping online at home increased noticeably on her laptop while in Washington DC.  She text a friend back home to shop simultaneously and compare.  She was shocked to find the results.  When she tried to change the zip code for delivery purposes – hoping to trick the system – the price refused to budge.  Amazon knew where she was.

Final Morph

So pricing in the virtual world has not gone into our personal pocket books yet (that we know.)  The online market does use digital information such as browsing history and location to triangulate your willingness to pay a certain price.  This is still within the Small Data genre of capability, utilizing mean and median sources.

Big Data Price Point though – and I believe it will – knows YOUR personal bottom line.  This is not a random variable calculated through the local and not so location population supply and demand.  Big Data Price Point knows exactly what price to set for you from all your transaction history in stores and online, your taxes, your job, your household status, and much more.

Is that scary?  Perhaps.  But it is already very close to possible.  

What would have happened with the Housing crash of the early 2000s? Big Data Price Point would have offered houses at rates that individuals could afford.  Would it have curbed the domino effect or accelerated it that much more?  Perhaps Big Data Price Point would have sensed the cumulative errors the isolated banks were unknowingly committing and eventually unwilling to admit.  It’s a twist again for Mr Smith’s legacy to wrap around.

The world out there is waiting to sell you the next Best Thing and Big Data or not, marketing will continue to morph to find the magic price you are willing to pay.  Big Data Price Point though will be oh-so intimately familiar with you and your money.  In the end though, Big Data Price Point can only posture the question:  will you buy?  

The answer is still up to you.

Ain’t Talkin’ ‘Bout Love and The Edge of the Internet of Things

https://techcrunch.com/2017/08/03/edge-computing-could-push-the-cloud-to-the-fringe/

Aint Talkin Bout Love and The Edge of the Internet of Things

 

I’ve been to the edge

And there I stood and looked down

You know I lost a lot of friends there, baby

I got no time to mess around.

  • – Van Halen, Ain’t Talkin’ ‘Bout Love

 

Ah … nothing like 1978 classic rock lyrics about getting/giving an STD to start off discussion on emerging technology.

The Edge or Edge computing is an important tenet in understanding the Internet of Things (IoT).  Wherein you may never reach the end of the internet, you can actually see the edge of the Internet of Things.  “Things” or sensors exist everywhere – anywhere in a process or across multiple processes – but at some point there is an end of the line.  From The Edge, sensors stand and look down … and out and around at the physical world. Because they are at the Edge, these nodes can be the furthest extent from the people and processes that are interested in the information or they could be right there where they are needed.  Thus this can be where you gain or lose the best data (friends). This is where measurements are real time… when there’s “no time to mess around”. The Edge is current discussion on security as well, keeping the systems and processes free from disease and evildoers. The Edge is an important feature in building and utilizing IoT.  

 

For Example

To explain how the Edge works, let’s go back to an old school intrusion detection system and smoke/fire alarm (I used this in my IoT Connections blog post.) Pre-Internet, intrusion detection or smoke/fire alarm systems had various sensors hard-wired into place to determine whether the desirable conditions (no fire or intruders) were being met.  Smoke and fire devices triggered alarms for heat or chemical substances within a physical building.  Burglar alarms were usually a circuit that once broken sounded the alarm.  For both, the alarm could be sounds or lights that were experienced just by anyone there or they could be connected via land lines to other players that could call emergency services.

When the sensors are triggered, the alarm sounds there at The Edge.  Anyone in the building who is aware of the alarm understands the dangers and has the ability to make decisions from that information, such as calling the police or fire department or taking others actions such as evacuations or defense procedures.  If the sensors are connected to a monitoring service, the responders are trained and ready to act appropriately.  Perhaps the system may be able to notify the emergency services directly.  That is Cloud decision space.

With the pervasiveness of the Internet and the autonomy of the design, you can easily understand the most preferable choice – an instantaneous, specific and desirable response to an emergent situation.  Thus the IoT has grown exponentially, leveraging the combination of ubiquitous sensors (active and passive, deliberate and advantageous) and omnipresent Cloud.  However, this popularity is changing.

http://www.businessinsider.com/internet-of-things-cloud-computing-2016-10

Keeping it Local

So Why NOT Use the Cloud?

For the 15 years that IoT has been growing, it has crawled the Internet as a natural progression.  Utilizing the ubiquity and ease of the Cloud made undeniable leverage of current operations and projected expansion.  Afterall, so far the Cloud is an amorphous, expanding universe that has served our needs.  We haven’t reached the end of the internet, so why not continue mining a perceived inexhaustible resource? However, recent developments have begun shifting the processing of the sensors back to The Edge for decision making.  Four reasons have driven it back.

 

Cost. The cost of sensors continues to drop, and the capabilities of those sensors are increasing.  Subsequently, more data with more fidelity is possible at multiple touch points.  Processing ALL the sensors in the cloud derives a resource tax.  Simply, you can buy more sensors by saving the cost of connecting to the Internet.  Or you can even more simply spend less money.

 

Security.  Proprietary or personal information is risked with exposure to The Cloud.  Keeping the information local to the sensors for decision at the source can be more effective as well as provide better security.  The Edge sensors still need safe-keeping but the damage control is more easily prevented or contained.

 

Design.  Just because the Cloud is there doesn’t mean you need to use it.  KISS.  The Cloud doesn’t necessarily fulfill the mission of the system created.  The Cloud is actually getting pretty crowded, and for now, this point in time, keeping the game locally may be in the best interest of the system.  Also, capability has developed to collect data from multiple sensors but interested parties have different access for different needs.

 

Speed.  “Instantaneous” is highly measurable now.  The meer fractional computation distribution of data still may not be fast enough.  For example, autonomous driving cars need Edge computing because the criticality of data for safe driving decision simply is too fast to zoom out and back to the Cloud.

 

Farm to Table

A current application of Edge computing is sensors planted with crops.  These nodes constantly provide feedback as to the soil’s properties, such as moisture content, mineral composition, and density.  The automated watering systems then deploy precise amounts meter by meter, not acre by acre, determined by real time monitoring.  Cost savings are realized in both water and fertilizer consumption.  The harvest is more bountiful and The Edge is more likely cheaper than utilizing a Cloud structure.

Ain’t Talkin’ ‘Bout Love

But The Edge is where sensors are beginning to do more of the heavy lifting of data processing and decision making – for now.  Technology will evolve and we will rock and roll with it. Be careful though because just as with The Cloud, you wouldn’t want to catch a virus or malicious attack any more than you would give one.  Always practice safe sensor deployment.  Like the 80s, all trends don’t die; they just come back around.

 

Previous post on IoT: IoT Connections

Next up:  PIoT vs IIoT

 

Look out for more than bones in the fish you’re eating … batteries included

With the Internet came the ability for computers worldwide to connect regardless of race, creed or country.  As the Internet evolves into the Internet of Things (IoT), more and more sensors – not just computers – connect to further enhance business, economics and life in general.  Food for example comes from around the globe.  Brazil provides 30%, Florida 15% and China coming in a close third.  How do you know it’s fresh?

Shipping fresh produce or fresh fish or fresh anything requires controlling environmental conditions that keep it safe for consumption at the table.  Originally it was refrigerated by some means deemed sufficient and let the eater beware.  Greater care was placed in the process by measuring the temperature and humidity of the container.  Eventually that meter was monitored.

Today, any safety conscience food provider has the means via the Internet of Things (IoT) to monitor the container wherever it is in the world from wherever the company is in the world in real time.  Giovanni Salvatore and ETH Zurich have taken even that capability a step further by developing a sensor that actually attaches to the fish or produce itself.  And it’s okay to eat it!  The sensor is far thinner than a human hair (eck, don’t think of how that became a measure.)  Not only is it edible, but it contains magnesium, which is good for you – in the right amounts.

It’s not quite in a market near you though.  The sensors still require a power source so the battery attached is a bit self-defeating at this point.  No worries though.  Several sensors in other industries have already been developed that don’t require power.  It won’t be long before you’ll checking the gills for a freshness date!

 

 

Source: https://www.engadget.com/2017/09/29/super-thin-edible-sensors-monitor-food-temperature/

Who is Betting $25 Million on the IoT? Who will be left behind?

Marc Andreessen is betting $25million

on the Internet of Things (IoT) becoming a big thing. His famous ability to forecast the evolution of emerging technology weaves a picture of sensors embedded in walls and doors and doorknobs. It makes today’s humble offerings – the likes of remote operation of your house security and appliances or fitness bands that connect to a mobile device and the cloud – seem kinda silly.

Marc Andreessen stretches out that belief a little further with his opinion that cell phones will become obsolete. In his perspective a single point of contact such as a cell phone is a limiting vision. He conceptualizes that screens will pervade many more surfaces so much that having to carry your own electronic portal seems a bit ridiculous. That’s an intriguing perspective from an expert on the subject. Goodness knows that a home phone or a pay phone seems quite antiquated today; even paying for a phone call is becoming upended. It’s becoming possible to speak to anyone in the world with an Internet connection and a choice of free apps.

So what happens to the countries …or continents … that are amassing mobile service by leaps and bounds but still lagging far behind? Are they going to be left even further behind …again? Will the technology gap drop those that can’t afford the latest and greatest?

Mobile Phone Adaption

Africa for example doesn’t have as many mobile devices per capita as the rest of the world, but they do use mobile phones in the din of the more remarkable remote locations. Their mobile technology isn’t so much smart as functionally adaptive, performing the most cursory and vital functions, such as currency, in more creative ways than more technologically adapted regions.

So how could it be possible this makes Africa a better candidate to take a technology leap than further advanced countries? Let’s looks at that.

In 2008 Intel reported on their self-developed “Technology Metabolism Index” – a map of what countries adapt technology relative to economics. What they found was that those that “have” don’t necessarily beat out the “have nots” to adopting new technology. The United States had a relatively low index in consideration of the greater resources, access and availability of new technology.

tmi_2007_global_map

Some experts worry that a technology gap threatens to leave behind vast swaths of the world population too poor to afford new innovations, but Nafus work could be seen as evidence that more complex dynamics are at play than just disposable income levels. http://www.wired.com/2008/06/intel-anthropol/

Intel’s Dawn Nafus, a Cambridge PhD, conducted the study in order to better determine the potential of emerging markets versus mature markets. Her team found a couple of surprises. The first is a bit counter-intuitive.

Population size is actually a constraint on technology adoption, just the sheer number of connections between people seems to slow adoption.

The research also supported that foreign direct investment, or how much money foreign firms pour into a country’s economy, can actually constrain how fast technology is adopted. Again, it’s not what you’d think, when more money usually portends resources and capabilities.

Didn’t See It Coming

So let’s look at another technology adaptor story – Colombia. For years, Colombia was known for illegal drug activity that held it hostage. By investing in technology growth its economy has tripled from what it was 10 years ago and its middle class has increased 50%. The country’s remarkable make over has attracted US businesses, increasing import from the US to Colombia by nearly 400% since 2003. Google, Facebook and Microsoft have established presence in country, and of course, Starbucks is there as well to fuel the creativity.

150312172901-colombia-latina-america-780x439

The advances are attributed in great part to fostering entrepreneurship in tech hubs such Ruta N in Medellin and Bogoda’s HubBOG, a 5-year-old tech campus. These hubs are a common theme worldwide.

Another reason entrepreneurs may want to take a strong look at Colombia is because it’s coming online quickly. The Colombia government is working to bring 63 percent of its population online by 2018, according to a report by Colombia Reports. It also boasts 69 percent smartphone adoption, according to the GSMA “Mobile Economy” report for Latin America. http://www.cnbc.com/2015/05/07/three-growing-start-up-cities-in-south-america.html

Big Data Africa Opportunity

According to the TMI index map, a case could be made for South America, Africa, Eastern Europe or the Far East to make Big Data a turn-around industry for any of these regions or countries within.

The availability of Big Data is an inevitable global factor that grows exponentially continuously. Because it is ubiquitous and open source, in Africa or any of the other emerging regions, Big Data is a tremendous opportunity.

Big Data is already deployed in multiple directions: competitive industry, government interest and non-government action. Where there is a will, there is a Big Data way. Training and deployment of all levels of Big Data tools are ubiquitous, given connectivity. Big Data has a relatively low cost of entry as well.

Innovation Hubs in Africa

Africa already has a healthy network of these centers. The number of technology centers in Africa has increased dramatically over the past couple of years. More than half of African countries have a technology hub and leader South Africa has nineteen. According to World Bank, more than half of African nations have at least one tech hub, totaling around 90. In 2014, investment in tech hubs has gone from $12 to $26 million.

Africa Mobile Adaption

A wide variety of participants are needed to make Big Data work. The Big Data industry has an extreme shortage of data scientists and technicians. Even the occupation “data scientist” is actually not as straight forward as it would seem. This is opportunity to find a niche or create a new one.

Not Another NGO

The volume, velocity and variety of data accumulating are a worldwide phenomenon. Perhaps it is relative size, but every person in every country is creating more and more streams of information. In the same thread, every business creates and has access to tremendous amounts of data, but who uses it varies greatly. It’s not a necessity now for entity differentiation, but it is rapidly becoming so.

Those that don’t adapt to utilizing Big Data will get left behind – corporation or country.  We are in a global economy ecology as well.  In a post 9/11 world, we can’t leave others behind and hope for the best.  We’ve got to create the rising tide to lift all boats.  Bring on the Big Data.