How is your organization putting efforts to know your customers in digital age?
First of all, I will explain the reason for the post title. For those who have not seen the films, I summarize: "A group of four illusionists win year after year to the public with their incredible magic shows and even mocking the FBI.
GSMA is a great illusionist and MWC is their principal magic show. We are invited year after year to visit an event with unique keynote speakers, an enormous list of exhibitors, amazing performances and a great LinkedInplace where we can meet in person some of our social media contacts. What else can we ask for?
I know that it is very ruthless to compare the GSMA with illusionists and the MWC as their greatest magic show, but at least I see quite a few reasonable resemblances, you don´t.
My fears and my wishes for MWC17
If in 2015 I wrote " MWC 2015: Everything Connected, Tapas and Jamon", and I argued as one the reasons to attend MWC was the fact it was celebrated in Barcelona. In 2016, in my post “GSMA need to think how to reinvent MWC” I justify the reasons why the MWC needed to reinvent itself.
One thing has become clear to me after many years attending MWCs, this is the world's biggest phone and mobile networks show, with manufacturers set to unveil a raft of new phone handsets and new technology. However, the GSMA had insisted on introducing more and more distractions like Internet of Things (IoT), Connected Living, Connected Car, AR/ VR, Robots. Maybe the reason is because Telecom operators do not have the DNA to change. Still, many telecom operators take a dim view of some of the aggressive moves being made by these peers, especially when it comes to business models based on commercializing customer data.
“I expected to see less hype and a dose of common sense”
Starting by the announcement of Spain’s Telefonica to introduce a broad plan “4th Platform” to help both consumer and business customers keep greater control over their data rather than giving it away to web giants Google, Facebook and Amazon.
“I expected to see more applications where IoT will become a lot less exciting, but more useful and profitable. The real world.”
But I also feel like Scott Bicheno that “Mobile World Congress is disconnected from reality”.
The Top 5 tricks of illusionism this year
5G, Network Slicing and their associated Business Models
5G will undoubtedly be the next big thing in mobile wireless networks. For Niall Norton: fact, fiction, MWC – and strangers dancing in the dark, the most over-hyped technology or trend this year will be 5G in spite he thinks 5G is still miles away and therefore we have to wait for augmented reality, virtual reality, driverless cars and the like. It is a big ask for investors to keep piling money in.
For Phil Laidler, Network slicing is essentially an extension of policy control, virtualisation, NFV and SDN, and their orchestration; the move towards software-centric, flexible end-to-end networks. At MWC this year he is looking forward to seeing more "proof of concepts" for network-slicing and the associated business models, in addition to any insights into how slicing will work in practice.
Nokia’s big 5G announcement on ‘day 0’ of the event was overshadowed by a large consortium of operators and vendors calling for just the ‘new radio’ part of the 5G standard to be accelerated, despite the fact that it will lack the backhaul, cloud infrastructure, software platforms, etc needed to make the 5G dream viable. If anything highlights the wishful-thinking folly of much of the talk at this year’s show it’s that.
IoT has been a hot topic at MWC for the last few years, but, operators do not succeed with new business models beyond managed connectivity. Strategic alliances with IoT vendors has shown no results yet.
The battle between connectivity technologies remains fierce, cellular IoT Chip Battle Escalates at MWC ARM, Sequans and Altair to compete on NB-IoT solutions, but vendors and operators are now looking for more innovative ways to overcome the problem. This might just be the year of Low-Power Wide Area Networks (LPWAN). Although LoRa and Sigfox are currently dominant in the LPWA market, cellular IoT proponents had steal the show.
For example, Telefonica - who is working on NB-IoT with Huawei - recently announced a global partnership with Sigfox. In addition, Nokia launched its worldwide IoT network grid ('WING') a few weeks ago, which it describes as "a 'one-stop-shop', full service model offering seamless IoT connectivity across technologies and geographical borders."
For Operators, the real value from IoT will be created when they can start combining data sets from different areas and different connectivity technologies. For example, smart cities, healthcare or Food & Beverage, retail, transportation and logistics to improve the cold chain supply management processes.
I hope that at MWC18 we will be looking out for examples of operators and vendors developing IoT use-cases that do just that.
“The Internet of Things is in MWC to stay for a few more years, but If your focus is Internet of Things (IoT) then your money probably will have more ROI in other IoT events”
Blockchain has become one of the latest buzz words in telecoms, IT and IoT , thanks to a rapid increase in start-ups using it for new use-cases beyond its original application in financial services. Despite the excitement around blockchain the technology is still poorly understood by many, so operators need to explore the practical applications of blockchain and investigate whether developing these capabilities would be beneficial and understand what will be their role telcos in this field.
Machine learning, Artificial Intelligence (AI), Robots
Not many people in the Operators and in general in the Telco sector can explain what will be the practical potential of AI and machine learning in this sector. Other industry sectors are starting to apply machine learning models to their business. And as the technology and algorithms become more refined, early adopters expect to see huge cost savings. But at what cost?
I expect to see real use cases for AI, machine learning and Robots to make the eternal promise of Customer Experience happen.
Will Telcos someday use machine learning and AI to learn about customer’s habits so that their services and product features can emulate a human behaviour more accurately?. This is a huge opportunity for both vendors and operators.
The wandering souls network
The first time I visited MWC as CEO of OIES, that is to say, as an independent consultant, I feel like a walking dead. Without a clear agenda, without scheduled meetings. I walk through hundreds of exhibitor booths looking for friend’s faces that can spend a couple of minutes to tell them my history.
The Telco sector (Operators, Large Vendors) and the IT sector is being very cruel with employees over 45 years old. This year I have had the opportunity to spend some time with some of ex-colleagues, friends and also LinkedIn contacts that wanted to tell me their history and asked me for advice about the new “El Dorado world of IoT”.
There is a lot of talent out there. Do not exclude this extraordinary wandering network because you believe they are overqualified and you can not manage them.
See you next year at MWC18
I've been saying the same thing for years when I come exhausted from MWC “No more tricks, no more illusions, this has been my last year". But will be this time the real one. Do I need a sabbatical MWC?.
“Whether you passed 1 day, 3 days or a whole week of your life in the MWC17 illusionism, ask yourself: Was it worth it? “
Now you see me or not @MWC18.
Thanks for your Comments and Likes
Big data is the collection of data that is part of our daily lives. It is the hundreds of million e-mails, likes on Facebook, and tweets we post online. It is the hundreds of thousands of photographs that go live on the internet each day. The industry itself is one that is growing at a breakneck pace. In 2013 big data accounted for a $10.2 billion industry, but is estimated to reach an astonishing $54.3 million this year.
Big data does not necessarily focus on the amount of data that is used though. On the contrary, it can refer to what organizations do with this data. It is the analysis of this data, processing information to make more informed decisions, and reviewing trends to make better execute strategic business moves.
The concept behind big data isn’t a new one either. While you’ve likely just started to hear the term, the process of gathering information and storing it has been around for decades. It wasn’t until Doug Laney who is a renowned industry analyst touched on the volume of data, the velocity of data, and the variety of data that we had a vision closer to our modern trend. Expanding on his statement, we also note that there are other essential factors like complexity of data and variability that are a critical part of the analytical process.
In our modern world, the data that is around is always growing. There is currently no end in sight to where this big data will go and we will continue to discover and create new ways to store and analyze the data that is there. Perhaps most surprising is that despite the sheer amount of data that is out there, only a small percentage of it is regularly analyzed. That means that there is still a world of information out there that can be processed and the statistics from it can be used to further propel the understanding of data that is there.
What is important to note is that big data isn’t about the vast amount of data is there. It’s true the numbers are staggering, but there is much more to this. But when someone talks about big data, the focus is on what they can take and pull from the information. It is the analysis of the different aspects of it. This information will allow businesses to determine how information can be better processed so they can reduce their standard operating costs, reduce processing time, and discover new ways to optimize the data that they are collecting. Over a period of time, this will also allow individuals to make better decisions and to avoid failures and other problematic concerns that may be faced along the way.
Big data will remain a pivotal part of the future. It impacts the buying habits of our customers, determining the risk doing business with individuals and companies out there, and avoiding fraud before it happens. All while reviewing data that potentially helps us to further expand our reach and success for years to come.
About Bill McCabe/ Internet of Things Recruiting - Executive Search/ Retained Search for the Internet of Things/ Machine 2 Machine/ Big Data Markets
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Top 50 IOT Authority on Twitter - per IoT Central
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It was a matter of time to end up writing an article to talk about the connection between Internet of Things (IoT) and the technology (arguably still in the infancy of its development) that may have the greatest power to transform our world, Blockchain.
In a future planet interconnected not just by devices, but by the events taking place across it, with billions of devices talking to one another in real time, the Internet of Things will require a secure and efficient way to track all interactions, transactions, and activities of every “thing” in the network.
Blockchain’s role could be a coordination layer across devices and the enabler of the IoT to securely facilitate interactions and transactions between devices, and may also support certain processes related to architecture scalability, data sharing, and advancements in encryption and private key technology, enhanced security, and potentially even privacy.
With blockchain, the Achilles’ heel of the IoT of heterogeneous OEM devices world now becomes viable. I wonder however, if is feasible that this decentralized IoT network may co-exist IoT sub-networks or centralized cloud based IoT models.
But let's face it, blockchain is still a nascent and controversial technology (experts estimate that it might take 5 -10 years for the mainstream adoption of blockchain technologies). Therefore, we must consider that blockchain’s applications within the Internet of Things is still a matter of conjecture and trial, and that it will take more time to determine whether and how blockchain might be implemented to secure IoT ecosystems.
What is Blockchain?
Blockchain, the technology that constitutes the backbone of the famous bitcoin, is a database that maintains a continuously growing set of data records. It is distributed in nature, meaning that there is no master computer holding the entire chain. Rather, the participating nodes have a copy of the chain. It’s also ever-growing — data records are only added to the chain.
A blockchain consists of two types of elements:
- Transactions are the actions created by the participants in the system.
- Blocks record these transactions and make sure they are in the correct sequence and have not been tampered with. Blocks also record a time stamp when the transactions were added.
If you want to know more about blockchain you can read:
Fascinating opportunities ahead with IoT and Blockchain
The possibilities of IoT are virtually countless, especially when the power of IoT is combined with that of other technologies, such as machine learning. But some major hurdles will surface as billions of smart devices will want to interact among themselves and with their owners.
While these challenges cannot be met with the current models that are supporting IoT communications, tech firms and researchers are hoping to deal with them through blockchain.
Applying the blockchain concept to the world of IoT offers fascinating possibilities. Is yet to be seen if blockchain is bound to expedite the revolution, simply by being the backbone for most of the future IoT systems.
An example - Right from the time a product completes final assembly, it can be registered by the manufacturer into a universal blockchain representing its beginning of life. Once sold, a dealer or end customer can register it to a regional blockchain (a community, city or state). But, this is only the beginning for the blockchain and Internet of Things (IoT). A washing machine could become a semi-autonomous device capable of managing its own consumables supply. It can perform self-service and maintenance, and even negotiating with other peer devices.
Challenges of Blockchain and IoT ecosystems
The chaotic growth of IoT will introduce several challenges, including identifying, connecting, securing, and managing so many devices. It will be very challenging for the current infrastructure and architecture underlying the Internet and online services to support huge IoT ecosystems of the future.
Forrester analyst Martha Bennett in the report “Disentangle Hype From Reality: Blockchain’s Potential For IoT Solutions“ defines three categories of challenges that Internet of Things and blockchain ecosystems participants must address: Technology, Operational challenges and Legal and compliance issues.
According with the report, the result of multiple surveys indicates that what the IoT requires more than any technological or architectural advancement is trust: trust between stakeholders and the devices interacting with them, their customers, or on their behalf.
“As technology and commercial firms look for ways to deploy and secure Internet of Things technologies at scale, blockchain has emerged as a clear favorite for managing issues like identity and transaction security”
Blockchain, a strategic ally to Democratize the IoT
The big advantage of blockchain is that it’s public, so there is no single authority that can approve the transactions or set specific rules to have transactions accepted. Thus, the primary utility the blockchain is a censorship resistant way to exchange value without intermediaries.
Will blockchain disrupt the disrupters?. In my post “Is it possible to democratize the Internet of Things? How to avoid that a handful of companies can dominate the IoT” I already suggested the use of blockchain to avoid that data-hungry businesses and governments collect data on the behaviour of people and the performance of objects. Blockchain could avoid that Multinational and governments deepening tracking and control of citizen behaviour and attitudes.
Are IoT Business Models at risks with Blockchain?
IoT Service Providers hope not. There is a risk that the combo of blockchain and the sharing economy trashes some new IoT business models. Same way that, successful or not as successful platform, companies like Uber and Airbnb, are worried today.
Just think, the success of these and some other platform companies is largely due to people trading assets they own and are paid for, but from which new value could be derived, And they release this value by using platforms to match up sellers of the extra capacity – whatever it may be – with buyers. Further, they collect data about transactions “for further commercial gain”.
Indeed, arguably many of new IoT companies’ main line of business will be data, but, what if blockchain enabled buyers and sellers to work peer-to-peer and cut out the middleman/data aggregator and seller? In that case the secure connectivity could be king not the data.
A question for IoT Platform vendors, if we have a secure, foolproof decentralized system, why do I need your IoT Platform if I and all the communities I belong to can do it for ourselves, without anybody collecting, analyzing and selling data about me?
The convergence of Blockchain and the Internet of Things closer
In my post “Will we be able to build the Internet of Things?” I warned about the Babel tower of Alliance & Consortiums in the Internet of Things.
A blockchain technology industry consortium is emerging from the meeting, New Horizons: Blockchain x IoT Summit, with the objective of defining the scope and implementation of a smart contracts protocol layer across several major blockchain systems.
In December 2016, representatives from a group of industry-leading startups and innovative Fortune 500 companies met in Berkeley, CA to discuss the challenges facing blockchain and IoT innovation and the potential for a collective effort to address them. The meeting was the first step towards a collaborative effort to explore and build a shared blockchain-based Internet of Things protocol. Participants in the discussions included blockchain companies Ambisafe, BitSE, Chronicled, ConsenSys, Distributed, Filament, Hashed Health, Ledger, Skuchain, and Slock.it, along with Fortune 500 corporations BNY Mellon, Bosch, Cisco, Gemalto, and Foxconn.
Who is using Blockchain in IoT
The IoT and blockchain combination is already gaining momentum, and is being endorsed by both startups and tech giants. Several companies are already putting blockchain to use to power IoT networks.
Filament, a startup that provides IoT hardware and software for industrial applications such as agriculture, manufacturing, and oil and gas industries. Filament’s wireless sensors, called Taps, create low-power autonomous mesh networks that enable enterprise companies to manage physical mining operations or water flows over agricultural fields without relying on centralized cloud alternatives. Device identification and intercommunication is secured by a bitcoin blockchain that holds the unique identity of each participating node in the network.
Telstra, Australian telecommunication giant Telstra is another company leveraging blockchain technology to secure smart home IoT ecosystems. Cryptographic hashes of device firmware are stored on a private blockchain to minimize verification time and obtain real-time tamper resistance and tamper detection. Since most smart home devices are controlled through mobile apps, Telstra further expands the model and adds user biometric information to the blockchain hashes in order to tie in user identity and prevent compromised mobile devices from taking over the network. This way, the blockchain will be able to verify both the identity of IoT devices and the identity of the people interacting with those devices.
IBM, allows to extend (private) blockchain into cognitive Internet of Things. To illustrate the benefits of blockchain and Internet of Things convergence, IBM gives the example of complex trade lanes and logistics whereby smart contracts can follow (and via blockchain technology register), everything that has happened to individual items and packages. The benefits: audit trails, accountability, new forms of contracts and speed, to name a few.
IBM and Samsung introduced their proof-of-concept system, ADEPT, which uses blockchain to support next-generation IoT ecosystems that will generate hundreds of billions of transactions per day.
Onename are creating the infrastructure for blockchain based identities that can be used for humans and machines. This means the blockchain can act like a phone book that lets machines find each other.
Tierion is being used to collect data from industrial medical devices to build a verifiable record of their usage and maintenance history. Tierion is thrilled to be the first partner to join Philips' Blockchain Lab. Together they are exploring how blockchain technology can be used in healthcare.
ConsenSys working with Innogy (a subsidiary of German utility RWE) are exploring how to enable an energy marketplace fed by distributed solar and other electricity-generating devices, which are run using a decentralized power grid.
21.co, Microsoft, Slock.it, and others are working directly with adopters in manufacturing, supply chain management, energy and utilities, agriculture, and construction; distributed ledgers may further automate, secure, and drive new services for these industries.
Blockchain is not the unique silver bullet for IoT security
Given the importance that Security has to fulfil the promise of the Internet of Things (IoT), I wrote “Do not stop asking for security in IoT” although I did not talk about how blockchain can help secure the Internet of Things. Now with this post, I hope I have corrected that gap.
The existing security technologies will play a role in mitigating IoT risks but they are not enough. Cryptographic algorithms used by blockchain technologies could perhaps be a silver bullet needed by the IoT industry to create a more resilient ecosystem for devices to run on and to make consumer data more private. But blockchain should not be viewed as the unique silver bullet to all IoT security issues considering that today’s blockchain space is even more nascent than the IoT.
Manufacturers, legislators, IoT hardware and software vendors, IoT Service Providers, System Integrators, analyst, and end users, must be aware of the IoT security challenges and focus on increase security efforts to reduce the risk inherent to the fragmented Internet of Things so among all we can accelerate adoption.
In the long term, we should keep dreaming in a fully decentralized and secure IoT using a standardized secure communication model. We must trust this dream will be possible, if worldwide, engineering talent, startups, large companies, and governments increase the investment in time, energy, and money to innovate in solutions that address the IoT’s and blockchain’s shared problems.
The Internet of Things is slated to be one of the most disruptive technologies we’ve ever seen. It’s going to change a great deal - including how we look at and use the cloud.
Software-defined cars. Internet-connected ‘smart’ fridges, coffee machines, and televisions. Wearable technology like smartwatches and smartglasses. The Internet of Things is going to change everything from how we work to how we drive to how we live our lives. And as it does so, it’s also going to change the cloud.
It already is, actually.
Enter fog computing. It’s an extension of the cloud, born out of the fact that there are more Internet-connected devices in the world than ever before (by 2020, Gartner predicts that there will be 6.4 billion.) Given this influx, the traditional, centralized model of the cloud is no longer viable.
“Today, there might be hundreds of connected devices in an office or data center,” writes Ahmed Banafa of Thoughts On Cloud. “In just a few years, that number could explode to thousands or tens of thousands, all connected and communicating. Most of the buzz around fog has a direct correlation with IoT. The fact that everything from cars to thermostats are gaining web intelligence means that direct user-end computing and communication may soon be more important than ever.”
It makes a lot more sense to move the real computing and processing closer to client devices. To carry out analysis at the network’s edge. See, the thing about the Internet of Things is that it depends on managing data over very short timeframes. Even a slight delay introduced as a result of bandwidth is unacceptable.
Consider the following examples:
A self-driving car is communicating with the vehicles and traffic infrastructure around it, and analyzing traffic and weather conditions. While it may communicate with a central server, it needs to be able to analyze and aggregate data immediately, lest it cause an accident.
Autonomous tunneling and boring machines at a mining site ensure workers don’t have to subject themselves to hazardous underground conditions. These machines must be capable of analyzing and storing terabytes of data, as network connectivity hundreds of feet underground is near-impossible. They also must be able to communicate with other mining infrastructure, as well as a central server, uploading processed data to the cloud when mining is finished.
Sensors at an oil well must connect to a cloud server to provide headquarters with a real-time vision of the facility. These sensors, however, must be capable of analyzing data on-site before it is uploaded.
In each of the examples above, distributed computing works together with a more traditional cloud model to better-enable connected equipment and sensors. And that’s where the cloud slots in with IoT. It’s still the cloud - but it’s changed in order to adapt to new workflows, business processes, and an entirely new world.
“With the increase in data and cloud services utilization, fog computing will play a key role in helping reduce latency and improve the user experience” writes Data Center Knowledge’s Bill Kleyman. “We are now truly distributing the data plane and pushing advanced services to the edge. By doing so, administrators are able to bring rich content to the user faster, more efficiently, and - very importantly - more economically.”
Photo credit: Mr. & Mrs. Gray
About the Author:
Tim Mullahy is the General Manager at Liberty Center One. Liberty Center One is a new breed of data center located in Royal Oak, MI. Liberty can host any customer solution regardless of space, power, or networking/bandwidth requirements.
The IoT market has changed in many ways throughout the years, and since it’s a growing industry, there’s an estimated 32.6% CAGR increase in the next five years.
As an industry predicted to spend trillions in solutions, IoT’s trends need to be carefully observed and examined in order for implications and applications to be future-proofed.
How do you go about doing this? By simply analyzing how IoT is being used, as well as identifying which sectors are showing potential growth. Right now, a lot of focus is given to consumer applications such as Amazon’s dash buttons and smart home appliances. However, there are many opportunities in remote IoT. This covers industries like industrial, transportation, healthcare, etc.
One challenge that needs to be dealt with is how connectivity is approached right now. As more IoT and M2M devices would be deployed in rural areas and places with limited connectivity, applications and machines would need an improved infrastructure in order to carry out their purpose in areas with little connectivity.
Additionally, the increase of transportation and emergency-related applications would require not only ways to deals with low connectivity but also call for a system that can access multiple networks depending on availability and location.
Another challenge is how current devices will handle the developments in IoT and M2M technologies in the next five years. The 2G sunset is just one-way communication companies are affecting the industry.
Don’t fret, though, as there are several ways to resolve this and many opportunities left to explore to get ready for IoT’s evolution in the coming years.
Want to learn more about the possibilities remote IoT connectivity presents and how you can prepare for them? Check out the following infographic from Communications Solutions Company, Podsystem, and start future-proofing your IoT and M2M applications.
- Freemium model : Basic products/services are provided free but users are charged for advance features. E.g. Coursera, LinkedIn, Spotify, Dropbox, Skype
- Pay as you go or Subscription Model : Pay only for services which are used. E.g. Netflix, Kindle, New York Times, Safari Books online
- Customer experience model : provide the customer experience never before e.g. Tesla, Disney Land, Apple
- On-Demand model : provide customer service on demand with speed. E.g. Uber, cloud services from Amazon, Microsoft
- Marketplace model : provide a platform for buyer and seller interact with each other directly e.g. ebay, Alibaba
- Free model : provide the typical services to users free and sell their behavior data to different businesses e.g. Google, Facebook, Patientslikeme
- Crowd-sourcing model : receive money for engaging crowd for common goal, innovation, problem solving. E.g. Kaggle, CrowdAnalytix
- Bundling model : selling similar products or services together. E.g. Microsoft Office
- Gamification model : use of game like feature to simplify the interaction. E.g Mint.com, Khan Academy, Nike +
Was this all available to us 20 years before? Ali Baba’s “Open Sesame” was a story of childhood, but Digital Transformation is reality – and from now on nothing will be same again.
What will this market bring us in the next few years? Are there reasons for optimism?
During the last three years, I have had the opportunity to discover, know and analyse more than 50 Spanish companies in the exciting sector of the Internet of Things (IoT).
Some of these companies are globally recognized as pioneers of IoT. Others less known but very innovative, with great talent in their ranks. All of them have been weathering the storm and far from being discouraged, because the reality is being tougher than all the hype announced by analysts, are more excited than ever before future expectations.
As I wrote in my post “5 PROVERBS TO SAVE MY STARTUP”, nobody is a prophet in their land, but even so, I can not resist providing a few tips that I believe can help us use IoT as an enabler that drives the ICT sector. Would not it be fantastic if we finally met our desire to have a strong, dynamic, competitive and innovative ICT sector in our society?
And the stark reality is: "Spain is not a technological country, it is a service country". I think that the lapidary expression of Miguel de Unamuno, that “they invent it”, also applies to the IoT. But it is one thing not to invent and another is to become sellers of products, solutions or services of multinationals by all known.
We must use our ingenuity, talent, creativity, and customer orientation to design and develop quality, easy-to-use global IoT solutions.
If we are good sellers of foreign products, the language should be the problem. Our objective market should not be our City, our Community or our Country, our market must be the world.
Focus, Focus and Focus
I have insisted on many forums that in Spain we can not do everything on IoT. For example, we can be leaders in Smart Cities, but we will have little chance of success in Connected Cars, we must fight to find a gap in Industry 4.0 (also known as Industrial Internet or IIOT) but I fear we will not be number 1 in Wearables, although we could be innovative in Health services.
We must analyse our strengths and weaknesses to recognize where our opportunities are and what our threats are. Let us be references in our focus areas.
We know that there is not a single company in the world that can do everything in IoT, much less leading the IoT, so it is obvious that our companies and Startups have no other choice than to create or be part of reliable ecosystems and Collaborative projects in the focus areas to meet the challenges posed by IoT projects.
We must design new sustainable business models with our local partners, it is time to trust if we want to survive in this competitive and fragmented sector until the magic 2020.
It's time to real collaboration, put a logo on our presentations and our website is absurd if there is something else behind.
Given the size of IoT Spanish companies it is not possible to do everything and get it right.
We must specialize, whether manufacturing specific hardware, developing software or offering services in our focus areas.
To succeed in IoT, Spanish companies must be able to offer global and scalable solutions. We will need startup talent to focus on companies of a larger size than without giving up innovation and agility, being able to cope with large national and international IoT projects.
Expect to be outsourced by other subcontractors of a company that works for an end customer is not acceptable if we really want to change. It is a pending subject of our business model not only in technology, it is a deep-seated problem of corporate culture.
We should be able to have at least one unicorn in IoT. And I'm not talking about Telefonica, Banco Santander, BBVA, Iberdrola, Inditex, ACS, Ferrovial or Indra, but a company that provides a new IoTaaS model based on our strengths (which all or almost all know) Services and HW / SW IoT products from Spanish manufacturers. That is, we must think about having our Uber, Airbnb or why not our Spanish Tesla.
We must look for concentration of companies in the focus areas to achieve the size that allows the scalability that the IoT business needs.
Invest in Education and Training
The IoT is complex, although many try to make it simple. We will need many types of profiles and not just theoretical knowledge.
It is vital at both, the private and public levels, that the Public Administrations and Companies dedicate funds to continuously educate students and train employees in the IoT technologies.
“Investing now in IoT training will be key to ensuring a sustainable future for our companies, our country and our professionals.”
This advice goes to both Enterprises and Public Administrations.
In the case of Enterprises, it would be highly desirable to lose for once the fear of being the first to implement technology solutions. You must consider IoT a key element in the digitization process of your company.
Public Administrations, stop using your budgets as always, and think about investing in a more sustainable, intelligent and connected citizen.
To conclude, pulling on the proverb I think:
"We have the wicker, so we must have confidence that we can make a great basket in IoT".
You can read the Spanish version here.
Thanks in advance for your Likes and Shares
Thoughts ? Comments ?
Guest blog post by Olga Kolesnichenko
What is Big Data: data, process of analysis or concept? There are many definitions that describe Big Data as big amount of data or as some methods of analytics of big amount of data. But more applicable is the approach that Big Data is the concept that includes: data with specific characteristics (V3 - volume, velocity, variety, or V5 - plus value and veracity), methods of analytics (the number of different software is growing), and devices, infrastructure, and most important - the ideas how to configurate all into needed solution.
Another concept is the Internet of Things that based on Big Data Analytics. There are some established configurations of IoT: Smart Home, Smart Health, Smart Manufacturing, Smart City, Smart Mobility, Smart Energy, Smart Farming, Smart Earth & Ocean, Smart Circular Economy.
Smart Health or Internet of Health (or any IoT configuration) has the human in core of concept. I should point out that more easy to accept the medical approaches for different configurations of IoT than accept IoT approaches for Health Care. Why I can insist on this statement? My statement leans on long-term period of complexity of accepting biorhythmology and gravitational biology in medicine.
But biorhythmology and gravitational biology have the direct application for Internet of Health or IoT. The person controls own different medical data day by day during everyday life. And this new situation should be viewed as medical data collecting under gravitational forces and natural biorhythms influences to person.
Three sections of multifactorial regulation of human body should be mentioned: environmental, behavioral and homeostatic. Environmental section includes circannual rhythm (annual) and circadian rhythm (daily). Behavioral section includes body orientation towards gravitational forces (lying down, standing, sitting); active movement (walking, jogging, exercises); passive movement (lift and transport) with influence of acceleration forces; as well as sleep, emotional reactions, eating. Homeostatic section includes the processes of neurohumoral regulation of the body. This section consists of functional systems of the body, described by Russian scientist K.V. Sudakov and his following.
Thus creating Internet of Health configuration and implementing Big Data Analytics the medical data should be considered in terms of three sections of multifactorial regulation of human body.
In the recent Cricket world cup, every team had its own team of Data Analysts. They used various technologies like Cloud Platform and visualizations to predict scores, player performance, player profiles and more. Around 40 years’ worth of Cricket World Cup data is being mined to produce insights that enhances the viewer's experience.
- What would be the most profitable food served at the concession stand?
- What would be the best prices to sell game day tickets?
- Determine which player on the team is the most productive?
- Which players in the draft will become all-stars, and which ones will be considered role players?
- Understand the fans behavior at the stadium via their app and push relevant information accordingly.
The potential of big data just keeps growing. For taking full advantage, companies need to incorporate analytics into their strategic objectives.
A research report from McKinsey Global Institute (MGI), suggests that the opportunity and applications continue to expand in the data-driven world.
With rapid technological transformation, the question for businesses arises on how to position themselves uniquely in the world leveraging analytics. Over 2.5 quintillion bytes of data is generated every day. As information pours in via various digital platforms, VR application, and mobile phones the need for data storage capacity has increased.
The transformational potential
The recent progress shows the potential of big data and analytics in more than five distinct domains. However, transforming to a data-driven decision-making organisation is not always simple.
The first challenge is to incorporate data and analytics along with business objectives into a core strategic vision. Secondly, the lack of talent in the adoption of analytics. New reports denote that despite training programs, the talent is not enough to match the demand. The next step is to develop the right business process and framework which includes data infrastructure.
Simply combining technology systems along with the existing business operations isn't enough. For ensuring a successful transformation, all aspects of business activity need to be evaluated and combined to realize the full potential of data analytics.
Incorporating data analytics
The next generation of analytic tools will unleash even bigger opportunities. With new machine-learning, deep-learning and artificial-intelligence capabilities, an enormous variety of applications can be enabled which provide customer service, manage logistics and analyze data.
Technology and productivity gains seem an advantage, but also carry the risk of people losing jobs. A case of automation is the AI software developed by Bridgewater Associates, the world's largest hedge fund to improve efficiency.
With Data and analytics shaking up every industry, the effects will only become more noticeable as adoption reaches the masses.
As machines gain unprecedented capabilities to solve complex problems, organizations can harness these capabilities to create their unique value proposition and solve problems.
- Very small, targeted in scope and functionality
- Gives developers the freedom to independently develop and deploy services
- Loosely coupled & can communicate with other services on industry wide standards like HTTP and JSON
- API based connectivity
- Every service can be coded in different programming language
- Easily deployable and disposable makes releases possible even multiple times a day
- New Digital technology can be easily adopted for a service
- Allows to change services as required by business, without a massive cost
- Testing and releases easier for individual components
- Better fault tolerance and scale up
- Incur a cost of the testing at system integration level
- Need to configure monitoring and alerting and similar services for each microservice
- Service calls to one another, so tracing the path and debugging can be difficult
- Each service communicates through API/remote calls, which have more overhead
- Each service generates a log, so there is no central log monitoring.
Many industry experts and consumers are pointing the Internet of Things (IoT) as an upcoming Industrial Revolution or an upcoming Internet.
Why this? Simple, because IoT will consist of the future form of interaction of businesses, governments and consumers with the physical world.
The most recent studies indicate that in 2020 more than 34 billion devices will be connected to the internet, in many sectors (Industrial, Agriculture, Transportation, Wearable Devices, Smart Cities, Smart Houses, etc).
Of these 34 billion, the IoT will be responsible for 23 billion devices, the others 11 billion will be represented by the regular devices, such as, smartphones, tablets, smartwatches, etc.Source: BI Intelligence
The business sector will be responsible for the biggest use part of this devices, since the IoT can reduce the Operational Costs, Increase the Production, expand the business for new market niches.
Government will take the second biggest part of the devices connected, in smart cities, fasting up the public process, increasing the quality life of the citizens.
At last but not less important, the home user, will have a lot of IoT Devices, Smart Houses, Wearable Devices.
So the future we can really specify in some words: "The future is Data".
Now is the time to move beyond just collecting, storing & managing the data to take rapid actions on the continuous streaming data – Real-Time!!
Originally posted by Vincent Granville
It's time again to share your predictions for 2017. I did my homework and came with these 10 predictions. I invite you to post your predictions in the comment section, or write a blog about it. Ramon Chen's predictions are posted here, while you can read Tableau's prediction here. Top programming languages for 2017 can be found here. Gil Press' top 10 hot data science technologies is also worth reading. For those interested, here were the predictions for 2016. Finally, MariaDB discusses the future of analytics and data warehousing in their Dec 20 webinar.
- Data science and machine learning will become more mainstream, especially in the following industries: energy, finance (banking, insurance), agriculture (precision farming), transportation, urban planning, healthcare (customized treatments), even government.
- Some, with no familiarity with data science, will want to create a legal framework about how data can be analyzed, how the algorithms should behave, and to force public disclosure of algorithm secrets. I believe that they will fail, though Obamacare is an example where predictive algorithms were required to ignore metrics such as gender or age, to compute premiums, resulting in more expensive premiums for everyone.
- The rise of sensor data - that is, IoT - will create data inflation. Data quality, data relevancy, and security will continue to be of critical importance.
- With the rise of IoT, more processes will be automated (piloting, medical diagnosis and treatment) using machine-to-machine or device-to-device communications powered by algorithms relying on artificial intelligence (AI), deep learning, and automated data science. I am currently writing an article that describes the differences between machine learning, IoT, AI, deep learning and data science. You can sign-up on DSC to make sure that you won't miss it.
- The frontier between AI, IoT, data science, machine learning, deep learning and operations research will become more fuzzy. Statistical engineering will be present in more and more applications, be it machine learning, AI or data science.
- Many systems will continue to not work properly. The solution will have to be found not in algorithms, but in people. Read my article Why so many Machine Learning Implementations Fail. An example is Google analytics, which fails to catch huge amounts of robotic traffic that is so rudimentary and so obvious, you don't need any statistical or data science knowledge to filter it or block it. People publish elementary solutions to address these issues, yet it continues unabated. Fake reviews, fake news, undetected hate speech on Twitter, undetected plagiarism by Google search, are in the same category. Eventually it leaves room for new players to jump in and build a system that will actually work.
- Reliance on public data and public news will come with bigger scrutiny. Some say that the failure to predict the elections is a data science failure. In my opinion, it is a different type of failure: it is the failure to recognize that the media are biased (they publish whatever predictions that fit with their agenda) and maybe even those doing the surveys are biased or incompetent (there are lies, damn lies, and statistics as the saying goes). It is also a failure to recognize the very high volatility in these elections, and the fact that day-to-day variations were huge. Anyone able to compute sound confidence intervals that incorporates historical data, would have said that the results were not reliably predictable. Finally, I always thought that the winner would be the one best able at manipulation and playing tricks, be it hacking or paying the media.
- More and more data cleaning, pre-processing, and exploratory data analysis will be automated. We will also face more unstructured data, with powerful ways to structure them. Multiple algorithms and models will be more and more blended together to provide the best pattern recognition and predictive systems, and boost accuracy.
- Data science education will evolve, with perhaps a come back of strong university curricula run by leading practitioners, and fewer people finding a job through data science camps only, as many of these camps do not train you to become a data scientist, but instead a Python / R / SQL coder with classic, elementary, even outdated and dangerous statistical knowledge. Or data camps will have to evolve, or otherwise risk becoming another kind of Phoenix university.
- Attacks against data-dependent infrastructure will switch from stealing or erasing data, to modifying data. Some will be launched from IoT devices if security holes are not fixed.
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