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The topic of IoT and farming keeps coming up.

Last month Steve Lohr of the New York Times wrote a fantastic piece on The Internet of Things and the Future of Farming. His colleague Quentin Hardy wrote a similar piece, albeit with a big data slant, in November 2014. If you have not yet read either article, I suggest you take the time to do so and also watch the video of IoT at work at a modern farm. It’s one of the better IoT case studies I’ve come across and shows real and practical applications and results.

Both stories highlight Tom Farms, a multi-generation, family owned farm in North Indiana. The Toms won’t be setting up a stand at your local farmers market to hawk their goods. With over 19,000 acres they are feeding a nice portion of America and conduct farming on an industrial scale producing shipments of more than 30 million pounds of seed corn, 100 million pounds of corn, and 13 million pounds of soybeans each year.

As the video points out, technology, data and connectivity have gotten them to this scale. After the farm crisis of the 1980s, they double-downed and bought more land from other struggling farmers. Along the way they were proactive in researching and developing new production technologies - everything from sensors on the combine, GPS data, self-driving tractors, and apps for irrigation on an iPhone.

Farmers and Tablet PC

Photo Credit: Gary McKenzie on Flickr

All this technology is taking farming to a new level, in what is know as Precision Agriculture. The holy grail of precision agriculture is to optimize returns on inputs while preserving resources. The most common use of of modern farming is used for guiding tractors with GPS. But what other technologies are out there?

For that, the Wall Street Journal explored yesterday startups that put data in farmers' hands. Startups like Farmobile LLC, Granular Inc. and Grower Information Services Cooperative are challenging data-analysis tools from big agricultural companies such as Monsanto Co., DuPont Co., Deere & Co. and Cargill Inc.

The new crop from all of these technologies is data.

This changes the economics for farmers making them not just traders in crops, but in data, potentially giving them an edge against larger competitors that benefit from economies of scale (to compete against giants like Tom Farms).  

With the amount of venture investment in so-called agtech start-ups reaching $2.06 billion in the first half of this year there will be plenty of bytes in every bushel.

For a deep dive into Precision Agriculture, the history and the technologies behind it, I suggest registering for and reading the Foreign Affairs article, “The Precision Agriculture Revolution, Making the Modern Farmer.”

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Mapping the Internet of Things

You would think that in this day and age of infographics that finding a map laying out the ecosystem of the Internet of Things would exist. Surprisingly, a Google search doesn’t appear to return much. Neither does a Twitter a search.

Recently though I found two worth sharing. One from Goldman Sachs and the other from Chris McCann which I found very interesting - A Map of The Internet of Things Market.

Goldman Sachs’ map is pretty generic but it takes IoT related items all the way from the consumer to the Industrial Internet. In a September 2014 report, “The Internet of Things: Making sense of the next mega-trend”, Goldman states that IoT is emerging as the third wave in the development of the Internet. Much of what we hear about today are on the consumer end of the spectrum - early simple products like fitness trackers and thermostats. On the other end of the spectrum, and what I think IoT Central is all about, is the Industrial Internet. The opportunity in the global industrial sector will dwarf consumer spend. Goldman states that industrial is poised to undergo a fundamental structural change akin to the industrial revolution as we usher in the IoT. All equipment will be digitized and more connected and will establish networks between machines, humans, and the Internet, leading to the creation of new ecosystems that enable higher productivity, better energy efficiency, and higher profitability. Goldman predicts that  IoT opportunity for Industrials could amount to $2 trillion by 2020.

IOT-map_goldmansachs2014.png

 

Chris McCann, who works at Greylock Partners, has an awesome map of the Internet of Things Market (below). This is what venture capitalists do of course - analyze markets and find opportunities for value by understanding the competitive landscape. This map is great because I think it can help IoT practitioners gain a better understanding of the Internet of Things market and how all of the different players fit together.

The map is not designed to be comprehensive, but given the dearth in available guidance, this is a great starting point. The map is heavily geared towards the startup space (remember the author is a VC) and I think he leaves out a few machine-to-machine vendors, software platforms and operating systems.

Other maps I found that are interesting are:

Thingful, a search engine for the Internet of Things. It provides a geographical index of connected objects around the world, including energy, radiation, weather, and air quality devices as well as seismographs. Near me in earthquake prone Northern California I of course found a seismograph, as well as a weather station, and an air quality monitoring station.  

Shodan, another search engine of sorts for IoT.

And then there is this story of Rapid7’s HD Moore who pings things just for fun.

If you have any maps that you think are valuable, I would love for you to share them in the comments section.



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IoT Security - Hacking Things with the Ridiculous

In the 1996 sci-fi blockbuster movie “Independence Day”, there is a comical seen near the end where actor Jeff Goldblum, playing computer expert David Levinson, writes a virus on his Macintosh PowerBook that disables an entire fleet of technologically advanced alien spaceships. The PowerBook 5300 used in the movie had 8 MB of RAM. How could this be?

Putting aside Apple paying for product placement, we’re not going to stop advanced alien life who are apparently Mac-compatible.

I cite the ridiculous Independence Day ending because I was recently reading through a number of IoT security stories and began thinking about the implications of connecting all these things to the network. How much computing power does one actually need to hack something of significance? Could a 1997 IBM Thinkpad running Windows 95 take down the power grid in the eastern United States? Far fetching, yes, but not ridiculous.

Car hacks seem to be in the news recently. Recall last month’s Jeep hack and hijack. Yesterday, stories came out about hackers using small black dongles connected to a Corvette’s diagnostic ports to control many parts of the car through, wait for it, text messages!

Beyond cars and numerous other consumer devices, IoT security has to reach hospitals, intelligent buildings, power grids, airlines, oil and gas exploration as well as every industry listed in the IRS tax code.

IBM’s X-Force Threat Intelligence Quarterly, 4Q 2014 notes that IoT will drag in its wake a host of unknown security threats. Even IBM, a powerful force in driving IoT forward, says that their model for IoT security is still a work in progress since IoT, as a whole, is still evolving. They do suggest however five security building blocks: secure operating systems, unique identifiers for each device, data privacy protection, strong application security, strong authentication and access control.

In the end, it will be up to manufacturers to build security from the ground up and continual work with the industry to make everything more secure. As we coalesce around an ever evolving threat landscape, it will be the responsibility of smaller manufacturers, giants like IBM and industry organizations like the Industrial Internet Consortium and Online Trust Alliance’s IoT Trust Framework to help prevent the ridiculous from happening.

 

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Do You Believe the Hype?

I’m guilty of hype.

As a communications consultant toiling away at public relations, media relations and corporate communications, I’ve had my fair share of businesses and products that I’ve helped get more attention than it probably deserved. Indeed, when it comes to over-hyping anything, it’s guys like me and my friends in the media who often take it too far.

Recently though, I came across an unlikely source of hype - the McKinsey Global Institute.

In a June 2015 report that I’m now reading, McKinsey states, “The Internet of Things—digitizing the physical world—has received enormous attention. In this research, the McKinsey Global Institute set to look beyond the hype to understand exactly how IoT technology can create real economic value. Our central finding is that the hype may actually understate the full potential of the Internet of Things…” (emphasis is mine).

If McKinsey is hyping something, should we believe it?

Their report, “The Internet of Things: Mapping the Value Beyond the Hype”, does point out that “capturing the maximum benefits will require an understanding of where real value can be created and successfully addressing a set of systems issues, including interoperability.”

I think this is where the race is today - finding the platforms for interoperability, compiling data sources, building security into the system and developing the apps that deliver true value. We have a long way to go, but investment and innovation is only growing.

If done right the hype just may be understated. McKinsey finds that IoT has a total potential economic impact of $3.9 trillion to $11.1 trillion a year by 2025. They state with consumer surplus, this would be equivalent to about 11 percent of the world economy!

Do you believe the hype?

 

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Given all the buzz happening in the market around IoT, We looked at related projects in the crowd funding website Kickstarter.com to see how are IoT projects doing with respect to all the other ones.

We chose projects which have either “IoT” or “Internet of Things” either in their title or description and here are our findings.

The success rate of projects at Kickstarter is around 37.5%, for Technology projects it is 21% which is a lot less than the average success rate of projects. In Spite of this our analysis shows that the success rate of IoT projects is 44%, which is pretty good news. People are realizing the importance of IoT and are willing to fund the related projects.

 

The projects locations are almost concentrated in US and Europe with a few scattered in Asia and Australia

 

Because the projects are spread all over the world the goals of money to be raised were also in different currencies so to be able to analyse the monetary part we normalized all the numbers to US dollars.

The total sought out money for all the IoT related projects ( ongoing, successful and failed ) in Kickstarter is around $4.7 million and the actual pledged amount for the projects is around $1.5 million.

If you only consider the projects which have made it the total sought out and pledged amount is approximately $1.2 million. So only 2% of the pledged amount went to the unsuccessful projects which is usually the case with most of the projects on Kickstarter.

The average requested funding for all projects is around $60 thousand while the average funding requested by the successfully funded projects is around $44 thousand. For the failed projects it is $3500.

The top 10 successfully funded projects along with their links are given below

 

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Big Data, IOT and Security - OH MY!

While we aren’t exactly “following the yellow brick road” these days, you may be feeling a bit like Dorothy from the “Wizard of Oz” when it comes to these topics. No my friend, you aren’t in Kansas anymore! As seem above from Topsy, these three subjects are extremely popular these days and for the last 30 days seem to follow a similar pattern (coincidence?).

 

The internet of things is not just a buzzword and is no longer a dream, with sensors abound. The world is on its way to become totally connected, although it will take time to work out a few kinks here and there (with a great foundation, you create a great product; this foundation is what will take the most time). Your appliances will talk to you in your “smart house” and your “self-driving car” will take you to your super tech office where you will work with ease thanks to all the wonders of technology. But let’s step back to reality and think, how is all this going to come about, what will we do with all the data collected and how will we protect it?

 

First thing first is all the sensors have to be put in place, and many questions have to be addressed. Does a door lock by one vendor communicate with a light switch by another vendor, and do you want the thermostat to be part of the conversation and will anyone else be able to see my info or get into my home? http://www.computerworld.com/article/2488872/emerging-technology/explained--the-abcs-of-the-internet-of-things.html

How will all the needed sensors be installed and will there be any “human” interaction? It will take years to put in place all the needed sensors but there are some that are already engaging in the IOT here in the US. Hotels (as an example but not the only one investing in IOT) are using sensors connected to products that they are available for sale in each room, which is great but I recently had an experience with how “people” are the vital part of “IOT” – I went to check out of a popular hotel in Vegas, when I was asked if I drank one of the coffees in the room, I replied, “no, why” and was told that the sensor showed that I had either drank or moved the coffee, the hotel clerk verified that I had “moved” and not “drank” the coffee but without her, I would have been billed and had to refute the charge. Refuting charges are not exactly good for business and customers service having to handle “I didn’t purchase this” disputes 24/7 wouldn’t exactly make anyone’s day, so thank goodness for human interactions right there on the spot.

 

“The Internet of Things” is not just a US effort - Asia, in my opinion, is far ahead of the US, as far as the internet of things is concerned. If you are waiting in a Korean subway station, commuters can browse and scan the QR codes of products which will later be delivered to their homes. (Source: Tesco) - Transport for London’s central control centers use the aggregated sensor data to deploy maintenance teams, track equipment problems, and monitor goings-on in the massive, sprawling transportation systemTelent’s Steve Pears said in a promotional video for the project that "We wanted to help rail systems like the London Underground modernize the systems that monitor it’s critical assets—everything from escalators to lifts to HVAC control systems to CCTV and communication networks." The new smart system creates a computerized and centralized replacement for a public transportation system that used notebooks and pens in many cases. http://www.fastcolabs.com/3030367/the-london-underground-has-its-own-internet-of-things

 

But isn't the Internet of Things too expensive to implement? Many IoT devices rely on multiple sensors to monitor the environment around them. The cost of these sensors declined 50% in the past decade, according to Goldman Sachs. We expect prices to continue dropping at a steady rate, leading to an even more cost-effective sensor. http://www.businessinsider.com/four-elements-driving-iot-2014-10

 

 

The Internet of Things is not just about gathering of data but also about the analysis and use of data. So all this data generated by the internet of thing, when used correctly, will help us in our everyday life as consumer and help companies keep us safer by predicting and thus avoiding issues that could harm or delay, not to mention the costs that could be reduced from patterns in data for transportation, healthcare, banking, the possibilities are endless.

 

Let’s talk about security and data breaches – Now you may be thinking I’m in analytics or data science why should I be concerned with security? Let’s take a look at several breaches that have made the headlines lately.

 

Target recently suffered a massive security breach thanks to attacker infiltrating a third party. http://www.businessweek.com/articles/2014-03-13/target-missed-alarms-in-epic-hack-of-credit-card-data and so did Home depot http://www.usatoday.com/story/money/business/2014/11/06/home-depot-hackers-stolen-data/18613167/ PC world said “Data breach trends for 2015: Credit cards, healthcare records will be vulnerable http://www.pcworld.com/article/2853450/data-breach-trends-for-2015-credit-cards-healthcare-records-will-be-vulnerable.html

 

 

Sony was hit by hackers on Nov. 24, resulting in a company wide computer shutdown and the leak of corporate information, including the multimillion-dollar pre-bonus salaries of executives and the Social Security numbers of rank-and-file employees. A group calling itself the Guardians of Peace has taken credit for the attacks. http://www.nytimes.com/2014/12/04/business/sony-pictures-and-fbi-investigating-attack-by-hackers.html?_r=0

 

http://www.idtheftcenter.org/images/breach/DataBreachReports_2014.pdf

 

So how do we protect ourselves in a world of BIG DATA and the IOT?
Why should I – as a data scientist or analyst be worried about security, that’s not really part of my job is it? Well if you are a consultant or own your own business it is! Say, you download secure data from your clients and then YOU get hacked, guess who is liable if sensitive information is leaked or gets into the wrong hands? What if you develop a platform where the client’s customers can log in and check their accounts, credit card info and purchase histories are stored on this system, if stolen, it can set you up for a lawsuit. If you are a corporation, you are protected in some extents but what if you operate as a sole proprietor – you could lose your home, company and reputation. Still think security when dealing with big data isn’t important?

Organizations need to get better at protecting themselves and discovering that they’ve been breached plus we, the consultants, need to do a better job of protecting our own data and that means you can’t use password as a password! Let’s not make it easy for the hackers and let’s be sure that when we collect sensitive data and yes, even the data collected from cool technology toys connected to the internet, that we are security minded, meaning check your statements, logs and security messages - verify everything! When building your database, use all the security features available (masking, obfuscation, encryption) so that if someone does gain access, what they steal is NOT usable!

 

Be safe and enjoy what tech has to offer with peace of mind and at all cost, protect your DATA.

 

I’ll leave you with a few things to think about:


“Asset management critical to IT security”
"A significant number of the breaches are often caused by vendors but it's only been recently that retailers have started to focus on that," said Holcomb. "It's a fairly new concept for retailers to look outside their walls." (Source:  http://www.fierceretail.com/)

 

“Data Scientist: Owning Up to the Title”
Enter the Data Scientist; a new kind of scientist charged with understanding these new complex systems being generated at scale and translating that understanding into usable tools. Virtually every domain, from particle physics to medicine, now looks at modeling complex data to make our discoveries and produce new value in that field. From traditional sciences to business enterprise, we are realizing that moving from the "oil" to the "car", will require real science to understand these phenomena and solve today's biggest challenges. (Source:  http://www.datasciencecentral.com/profiles/blogs/data-scientist-owning-up-to-the-title)

 

 

Forget about data (for a bit) what’s your strategic vision to address your market?

Where are the opportunities given global trends and drivers? Where can you carve out new directions based on data assets? What is your secret sauce? What do you personally do on an everyday basis to support that vision? What are your activities? What decisions do you make as a part of those activities? Finally what data do you use to support these decisions?

http://www.datasciencecentral.com/profiles/blogs/top-down-or-bottom-up-5-tips-to-make-the-most-of-your-data-assets



Originally posted on Data Science Central 

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At the CES 2015, I was fascinated by all sorts of possible applications of IoT – socks with sensors, mattresses with sensors, smart watches, smart everything – it seems like a scene in sci-fi movies has just come true. People are eager to learn more about what’s happening around them and now they can.

 

While I was at there I attended a talk given by David Pogue – he is awesome. He pointed out that the prevalence of smartphone is the key to the realization of the phenomenon called “Quantified Self.” I agreed with him. Smart phones play a vital role as a hub where all our personal data converge and present, seamlessly. The fact that you carry your smartphone around all the time and that the screen size perfectly reveals all the information results in a catalyst for wearable devices, IoT or what we like to call it, Intelligence of Things.

 

It’s all relevant; Big Data, IoT, Wearable, Cloud Computing… While most data is uploaded to the cloud, the client devices are generally powerful enough that the computing can be decentralized. That said, small data (client side) and big data (server side) form an eco-system where small data triggers the knowledge base cultivated by big data and does the predictive analysis and decision making in a timely manner. Furthermore, your smartphone gathers versatile data and is able to analyze cross-app data to personalize your application settings. For example, what about optimizing navigation based on my physical condition? Or how about suggesting the best route according to my health along with the weather? These individual data records might be small, but collectively they enrich the content of analysis and contribute some amazing value. We at BigObject really appreciate this context of Big Data.

 

Marc Andreessen once said, “I think we are all underestimating the impact of aggregated big data across many domains of human behavior, surfaced by smartphone apps.” For us here at BigObject, the next big thing in big data is to find out a methodology that can link multiple data sources together and identify the meaningful connections between that data. Most importantly it must be responsive enough to deliver actionable insight and simple enough for people to adopt. That is the key to fulfill a connected world. 


Originally posted on Data Science Central

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The Internet of Things (IOT) will soon produce a massive volume and variety of data at unprecedented velocity. If "Big Data" is the product of the IOT, "Data Science" is it's soul.

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Let's define our terms:

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Internet of Things (IOT): equipping all physical and organic things in the world with identifying intelligent devices allowing the near real-time collecting and sharing of data between machines and humans. The IOT era has already begun, albeit in it's first primitive stage.
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Data Science: the analysis of data creation. May involve machine learning, algorithm design, computer science, modeling, statistics, analytics, math, artificial intelligence and business strategy.
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Big Data: the collection, storage, analysis and distribution/access of large data sets. Usually includes data sets with sizes beyond the ability of standard software tools to capture, curate, manage, and process the data within a tolerable elapsed time. 
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We are in the pre-industrial age of data technology and science used to process and understand data. Yet the early evidence provides hope that we can manage and extract knowledge and wisdom from this data to improve life, business and public services at many levels. 
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To date, the internet has mostly connected people to information, people to people, and people to business. In the near future, the internet will provide organizations with unprecedented data. The IOT will create an open, global network that connects people, data and machines. 
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Billions of machines, products and things from the physical and organic world will merge with the digital world allowing near real-time connectivity and analysis. Machines and products (and every physical and organic thing) embedded with sensors and software - connected to other machines, networked systems, and to humans - allows us to cheaply and automatically collect and share data, analyze it and find valuable meaning. Machines and products in the future will have the intelligence to deliver the right information to the right people (or other intelligent machines and networks), any time, to any device. When smart machines and products can communicate, they help us and other machines understand so we can make better decisions, act fast, save time and money, and improve products and services.
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The IOT, Data Science and Big Data will combine to create a revolution in the way organizations use technology and processes to collect, store, analyze and distribute any and all data required to operate optimally, improve products and services, save money and increase revenues. Simply put, welcome to the new information age, where we have the potential to radically improve human life (or create a dystopia - a subject for another time).
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The IOT will produce gigantic amounts of data. Yet data alone is useless - it needs to be interpreted and turned into information. However, most information has limited value - it needs to be analyzed and turned into knowledge. Knowledge may have varying degrees of value - but it needs specialized manipulation to transform into valuable, actionable insights. Valuable, actionable knowledge has great value for specific domains and actions - yet requires sophisticated, specialized expertise to be transformed into multi-domain, cross-functional wisdom for game changing strategies and durable competitive advantage.
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Big data may provide the operating system and special tools to get actionable value out of data, but the soul of the data, the knowledge and wisdom, is the bailiwick of the data scientist.
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Originally posted on  Data Science Central
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The Internet of Things may be giving over to the Internet of Everything as more and more uses are dreamed up for the new wave of Smart Cities.

In the Internet of Things, objects have their own IP address, meaning that sensors connected to the web can send data to the cloud on just about anything: how much traffic is rolling through a stoplight, how much water you’re using, or how full a trash dumpster is.

Cities are discovering how they can use these new technologies — and the data they generate — to be more efficient and cost effective in many different ways. And it’s a good thing, too; some estimates suggest that 66 percent of the world’s population will live in urban areas by the year 2050.

These are cutting edge ideas, but here are some of the most fascinating ways Smart Cities are using big data and the Internet of Things to improve quality of life for their residents:

  • The city of Long Beach, California is using smart water meters to detect illegal watering in real time and have been used to help some homeowners cut their water usage by as much as 80 percent. That’s vital when the state is going through its worst drought in recorded history and the governor has enacted the first-ever state-wide water restrictions.
  • Los Angeles uses data from magnetic road sensors and traffic cameras to control traffic lights and thus the flow (or congestion) of traffic around the city. The computerized system controls 4,500 traffic signals around the city and has reduced traffic congestion by an estimated 16 percent.  
  • Xcel Energy initiated one of the first ever tests of a “smart grid” in Boulder, Colorado, installing smart meters on customers’ homes that would allow them to log into a website and see their energy usage in real time. The smart grid would also theoretically allow power companies to predict usage in order to plan for future infrastructure needs and prevent brown out scenarios.
  • A tech startup called Veniam is testing a new way to create mobile wi-fi hotspots all over the city in Porto, Portugal. More than 600 city buses and taxis have been equipped with wifi transmitters, creating the largest free wi-fi hotspot in the world. Veniam sells the routers and service to the city, which in turn provides the wi-fi free to citizens, like a public utility. In exchange, the city gets an enormous amount of data — with the idea being that the data can be used to offset the cost of the wi-fi in other areas. For example, in Porto, sensors tell the city’s waste management department when dumpsters are full, so they don’t waste time, man hours, or fuel emptying containers that are only partly full.
  • New York City is creating the world’s first “quantified community” where nearly everything about the environment and residents will be tracked. The community will be able to monitor pedestrian traffic flow, how much of the solid waste collected is recyclable or food waste, and air quality. The project will even collect data on residents’ health and activity levels through an opt-in mobile app.
  • Songdo, South Korea has been conceived and built as the ultimate Smart City — a city of the future. Trash collection in the city is completely automated, through pipes connected to every building. The solid waste is sorted then recycled, buried, or burned for fuel. The city is partnering with Cisco to test other technologies, including home appliances and utilities controlled by your smartphone, and even a tracking system for children (using microchips implanted in bracelets).

This is just the beginning of the integration of big data and the Internet of Things into daily life, but it is by no means the end. As our cities get smarter and begin collecting and sending more and more data, new uses will emerge that may revolutionize the way we live in urban areas.

Of course, more technology can also mean more opportunities for hackers and terrorists. (Anyone see Die Hard 4, where terrorists hacked the traffic control systems in Washington, D.C.?) The threat that a hacker could shut down a city’s power grid, traffic system, or water supply is real — mostly because the technology is so new that cities and providers are not taking the necessary steps to protect themselves.

Still, it would seem that the benefits will outweigh the risks with these new data-driven technologies for cities, so long as the municipalities are paying attention to security and protecting their assets and their customers.

What’s your opinion? Are you for or against more integrated technologies in cities? I’d love to hear your thoughts in the comments below.

I hope you found this post interesting. I am always keen to hear your views on the topic and invite you to comment with any thoughts you might have.

About : Bernard Marr is a globally recognized expert in analytics and big data. He helps companies manage, measure, analyze and improve performance using data.

His new book is: Big Data: Using Smart Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance You can read a free sample chapter here.


Originally posted on Data Science Central

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