1. Block chain
The block chain is the heart of digital currencies like Bitcoin. What most don’t realise yet is that the block chain will be used for managing everything from domain names, artist royalties, escrow contracts, auctions, lotteries, etc. You can do away with middlemen whose only reason of being is making sure they keep on getting a large cut in the value chain. Unless a middlemen or governmental institution adds real value, they are in danger of being block chained into the past.
2. Biometric security
A good example is the Nymi, a wearable that listens to your unique heart beat patterns and creates a unique identity. Even if people steal your Nymi, it is of no use since they need your heart to go with it.
3. Deep belief networks
Deep belief networks are the reason why Google’s voice recognition is surprisingly accurate, Facebook can tag photos automagically, self-driven cars, etc.
4. Smart labels
They are 1 to 3 millimetres small. They harvest electricity from their environment. They can detect people approaching within half a metre, sometimes even identify them and each product you will buy. Your microwave will not longer have to be told how to warm up a frozen meal.
A $35 Raspberry Pi 2 or Odroid is many multiples more powerful than the first Google server but the size of a credit card. Parallella is $99, same size, and almost ten times more coresP then the first Google server.
6. Apps and App Stores for Smart Devices
Snappy Ubuntu Core allows developers to create apps like mobile apps but to put them on any smart device from robots & drones to wifi, hubs, industrial gateways, switches, dishwashers, sprinkler controls, etc. Software developers will be able to innovate faster and hardware can be totally repurposed in seconds. A switch can become a robot controller.
7. Edge/proximity/fog clouds
Public clouds often have too much latency for certain use cases. Often connectivity loss is not tolerable. Think about security cameras. In a world where 4K quality IP cameras will become extremely cheap, you want machine learning imagine recognition to be done locally and not on the other side of the world.
8. Containers and micro-services orchestration
Docker is not new but orchestrating millions of containers and handling super small micro services is still on the bleeding edge.
9. Cheap personalised robots and drones
£35 buys you a robot arm in Maplin in the UK. Not really useful for major things except for educating the next generation robot makers. Robots and drones will have apps (point 6) for which personalised robots and drones are happening this year.
10. Smart watches and hubs
Smart hubs know who is in the house, where they are (if you wear a phone, health wearable or smart watch), what their physical state is (heartbeat via smart watch), what your face looks like and your voice. Your smart watch will know more about you then you want relatives to know. Today Google knows a husband is getting a divorce before they do [wife searches and uses google maps]. Tomorrow your smart watch will know you are going to have a divorce before you do [heart jumped when you looked at that girl, her heartbeat went wild when you came closer].
A couple of weeks ago we launched the open source solution to put apps and app stores on any smart device. So this is a perfect moment to talk about what the future of the Internet of Things will look like.
Hardware and Software Acceleration
Up till now you had to be a hardware and software expert to innovate in IoT. Sony is an example of a big company that is a hardware innovator but struggled to make the transition to software-driven TVs. Amazon is the example of the opposite. By separating hardware from software, the IoT revolution will accelerate and walled garden solutions that are not cutting edge in both software and hardware will suffer.
Micro-servers are the size of a credit card but at a price of a good restaurant meal and 5 to 20 times better than the first Google server. Imagine their prices dropping to $5 or even $1 at scale. Now imagine having thousands of apps for each device that is powered by a micro-server. Finally imagine this smart device talking to thousands of other devices and proximity clouds as well a public clouds. These smart devices can have gesture control, voice control, virtual reality screens, 3D vision, 4k cameras, thermal sensing, GPS, body sensors, and lots of other sensors. Backed by a virtually unlimited cloud store that can do real-time big data predictive analytics and machine learning in a distributed fashion. Thanks to Bitcoin’s block chain, distributed solutions that are not centrally controlled are possible. Docker and containers allow cloud-based IoT solutions to be continuously deployed. 3D printing will accelerate customized solutions and over time lower production costs. So enough innovations to keep everybody busy.
IoT and business innovations
Lots of companies I speak to belief that platforms and hardware will make money. The bad news is that only Foxconn type of companies will be able to make money by producing extremely large quantities at ridiculously small margins each. Platforms will be open source so only a small number will get enough adoption to make money. So how can you make money with IoT?
For now consultancy but this will fade when the market matures. An obvious alternative model is apps and app stores. The cloud offers SaaS and pay for use software models that are likely going to be successful in IoT. However the big market opportunity is about substituting obsolete reactive maintenance businesses by proactive predictive maintenance, long tail B2B and B2C service marketplaces, broker models, pay per use service models, p2p/crowd models, etc.
Lots of traditional industrial companies have business models in which machinery is sold with a medium to low margin but maintenance and optional services have extremely high margins. These margins are protected through proprietary technology. In an industrial IoT market existing infrastructure will unlikely be substituted, a.k.a brown field market. Nimble competitors will offer ways around traditional models by creating translations between proprietary systems and general purpose IoT micro-servers that can be controlled remotely.
Future use cases
Home automation will be the most visible and trendy but industrial IoT will be the money maker. Telecom operators will present lots of sim-based use cases but unless they change their way of rolling out new services, success is doubtful for most. The connected car will likely use your mobile unless data contracts become extremely cheap. Health will see lots of solutions. A new market of over-the-top health solutions will emerge in which people will get health services from medical staff that can be on the other side of the world or even provided by a computer. Security and surveillance will be one of the most widespread IoT solutions given that the price of IP cameras has come down dramatically and security solutions have become easier to use.
Drawbacks of IoT
Standards are not important. Adoption will decide what is the standard. Not a group of pseudo-experts. However unless use cases don’t have enough widespread adoption across industries, you are likely to find islands of competing standards. Making global role-outs harder.
Security is key. Nobody wants to be the company that killed through IoT. Unfortunately it will happen in the next 24-36 months because security is extremely complex and somebody will cut corners.
Privacy is becoming critical. Google knows you are getting a divorce before you. But with IoT, your smart watch and big data analytics will know about your chances of starting an affair before you even talked to the other person.
Legally there are many areas of IoT that will be extreme challenges. Bad people are good innovators because they need to stay a step before others not to get caught. Also IoT conflicts will become extremely challenging to solve when services and solutions are used from the other side of the world.
Substitution of people by machines is a worry. Lots of people are in obsolete jobs but inertia is no longer a salvation because technology commoditises very successfully. However the Internet and mobiles created millions of new jobs. It is easier to see obsolete jobs than to predict new job roles. Who would have thought that data scientists would be the sexiest job!!!
Large IT and telecom companies are starting to get in trouble because they can’t keep up with the pace of innovation. Nokia lost out for missing the smartphone revolution. EMC/VMWare, Dell, HP, Vodafone, Sony, etc. are in danger of not keeping up. Why is it that large well managed companies go under? Christensen’s innovator dilemma explains that disruptive innovation is one of the causes. However there is no longer one specific innovation that these companies aren’t following. There seems to be an innovation tsunami going on at this moment: cloud, big data, IoT, bit coins, mobile, machine learning, 3d printing, Bluetooth, NFC, Arduino, super computers the size of credit cards a.k.a. micro-servers, etc. It feels like an army of innovators from 2100 have been transported to 2015. Big companies seem like native indians defending their land against armies with tanks, drones, machine guns, etc.
However what happens if we look deeper inside big companies and compare them to successful dotcoms? There is a striking difference in how both bring products to market. In small dotcoms designers, product managers, developers, BD/sales experts, marketing experts, business experts and domain knowledge experts are allowed to work together and to bring their skills together. In large organizations everything is structured around functions, i.e. marketing, sales, R&D, etc. Between each department there is a queue. Often glorified in some nice process to request something from the other departments. How many large companies can have a firewall port opened in less than two days at a request from marketing? Look at dotcoms and Google and co! They put new changes in production every day, hour, minute and even second. They can’t live with two days to open a firewall port. Why do companies belief that hiring an army of middle managers putting ridiculous processes in place is productive?
Does it actually work? Henry Ford told the world that specialists, put in production lines, are the most optimized way of working. We have been believing it ever since. However anybody that followed a training on lean will know that folding paper planes is faster if each person focuses on their plane than if they each specialise in one step. Toyota designed the Lexus by bringing experts from different parts of the company into one team. Amazon has pizza teams that are end to end responsible for a cloud service and get split when they can’t eat from two pizzas any more. It is time to restructure companies around bringing innovative products to market, growing market share and milking cash cows. No longer is there room for R&D, sales, finance, legal, etc. to hide behind obsolete processes. We need to see more innovation in large companies. We need multinational innovators or multivators. Lots of large companies are in danger of becoming obsolete. Only those IT companies that have consistently created internal competition and have known when to sell obsolete businesses have survived different innovation waves. Just compare IBM vs. HP. IBM sold its x86 server business, while it still could, in a clear signal to its employees that they better come up with some other innovation to fill the revenue gap. HP on the other hand keeps on milking their printer ink and x86 server business without a clear substitute on the horizon. Digital was bought by Compaq, Compaq by HP. Who is going to buy HP? Unless some Chinese IT vendor is still hungry, HP would do better in creating small tiger teams to find new revenue streams quickly…
A new revolution is in the making: the micro – server revolution. When Google started, its first server was four to five times less powerful then an Odroid-C1. The Odroid is just one of many small boards that retail for $35 and host a gigabyte of RAM and a 1Ghz processor and are no larger than a credit card. The $99 Parallella even has 18 cores on a credit card sized board. This combined with the new Snappy Ubuntu Core allows makers to create super smart devices that fit in the palm of your hand and developers to make millions of apps for them. Kickstarter and Indiegogo are likely going to see an avalanche of new smart devices and apps for them. Imagine your vacuum cleaner with apps. Your WiFi with apps. Your alarm, HVAC, coffee maker, sprinkler, set top box, etc. will all be app enabled. Now let’s look further to what new type of devices and apps are likely to come? In the health industry there are lots of doctor visits that could be diagnosed remotely. If people could buy some kind of $99 appliance that could measure all type of regular things like heart beat, oxygen level, temperature, sugar level, look in ears and mouth, etc. Connect this device to a tablet and any health care professional could see lots more patients each day and involve doctors and patients that live in remote areas. An app example could be investment banking. Flood sensors, wind sensors, rain sensors, seismic sensors, etc. can all predict disasters minutes or seconds before they happen. Micro – seconds high frequency trading could go global and make use of billions of sensor data to make trades just before problems occur and warn the rest of the world seconds or minutes earlier than before. There are many more devices and apps possible, just make sure you check out crowdfunding websites regularly…
Canonical, the company behind Ubuntu, just announced the biggest IoT innovation in history: SnApp Stores for any THINGS. Any THING can run apps from an associated Snapp Store. It is just like having apps on a mobile phone but instead apps run on any THING.
What does this mean?
Developers will be able to create apps with Snappy Ubuntu Core – Snappy Apps or Snapps – and run them on any THING. The list of THINGS is only limited by people’s imagination. It can be vacuum cleaners, fridges, dishwashers, coffee machines, alarm systems, robots, drones, set top boxes, HVAC, WiFi, switches, routers, telecom mobile base stations, agricultural irrigation controllers, swimming pool controllers, industrial appliances, medical equipment, digital signage, POS, ATMs, smart energy meters, cars, radios, TVs, IP cameras, clouds, 3D printers, virtual reality wearables, smart hubs and any next-generation device that can run Ubuntu Core and still needs to be invented. If it has an ARMv7 or X86 chip and 256MB or better then you can put a Snapp Store on it.
Apps made mobile phones go from stupid calling devices to personalised smart super computers many of us would not be able to live without. New industries were born. Complete industries revolutionized. The app revolution is about to be repeated but this time any THING is a target.
Imagine what will happen if all devices in your home, at work, in your city, on holidays, etc. go from stupid to smart and personalised. Your house will know if you are stressed before you enter the door. It will play the music it knows relaxes you, the coffee smell you prefer, the ideal temperature & light intensity, block calls you don’t want, have the house cleaned, your favourite food just minutes away from being delivered, grocery shopping done, that interesting TV series just waiting to entertain you, etc. Your energy bill will be lower, your car will adapt to you, your hover will collaborate with the alarm system, your pet will be fed the right diet, your children will have personalised parental control, your mail packages delivered where you are, etc.
Snapps will only be limited by your imagination so start dreaming now about what the Snapp Store should bring you an make your dreams come true at ubuntu.com/things.
It is easy to see how logistics, home automation, healthcare, automotive, energy, etc. have mind-blowing IoT use cases. However what about IoT and financial services? Since I live in the banking capital of the world – i.e. London – there must be something useful the City can do with IoT!
Personal insurance and IoT is easy
If a sensor can tell your insurance company when, where and how you drive then your car insurance will be able to offer insurance for actual usage and risk. If you are willing to wear sensors on your body then life and health insurance can be personalized. Share your mobile location with your insurance and travel insurance can be made into a dynamic one click service. House insurance can also go far better if sensors would measure risks, e.g. water damage can be reduced if your alarm system and your water meter would talk to one another.
Business insurance and IoT
What works for personal insurance also applies to business insurance. Logistics should pay for actual risk coverage. Health and travel insurance for employees can be tracked via sensors as well.
Linking insurance data to investment opportunities
If insurance companies anonymize and aggregate data then investment banks would benefit enormously. Delays in transatlantic shipping will delay sales and will impact stock markets. Knowing how many trucks left a car manufacturer’s plant will give you an excellent indicator of stock levels and future revenues. If lots of employees of Zara need travel insurance for some new countries, it is easy to predict investment in expansion is likely to happen in Inditex. Some use cases will require insurance customers to agree with data being shared. Nothing like a discount to accelerate this.
Other sensors and investment banking
Investment banking should invest in knowing weather and other easily measurable things milliseconds before others. High-frequency trading should not only happen inside black pools but could include storms that will delay ships, air traffic, etc. Banks that warn populations minutes or seconds earlier of a tornado, tsunami or earthquake will be seen as doing something good. That they will put their investments into safety or make some extra investments milli-seconds before the rest will be lost in the details.
IoT and retail banking
Retail banks always want to attract more savings and provide more credit. Knowing that your washing machine will break down in the next three weeks will allow them to offer a good credit deal first. Collaboration with home appliance and car manufacturers would be beneficial in this aspect. Also being able to predict how many appliances will need maintenance means that extending business loans to small businesses becomes a lot less risky.
IoT and other innovations
Adding block chain, machine learning, big data, cloud, etc. in the mix would open even a lot more use cases but let’s deal with those in another post…