Internet of Things | Paul Wallbank - Communications Professional

GE’s Predix predicament – an industrial giant finds software is hard

GE’s IoT predicament illustrates just how complex the engineering and management challenges of the Internet of Things really are.

Industrial giant General Electric is finding software is hard, reports Business Insider.

The company, which former CEO Jeff Immelt declared was a ‘digital industrial company’ is finding its Predix software system and associated cloud services are far more complex and difficult to manage than expected.

Back in 2015, I toured the head office of GE Software outside of Silicon Valley and interviewed the division’s boss, Bill Ruh.

Ruh was upbeat about the internet of things – or Industrial Internet in GE’s terminology – with an estimate the IoT was worth $14 billion to the company as it found new efficiencies and markets.

Today that vision’s looking a little tarnished as the company struggles with a 25% share price drop and a self imposed ‘time out’ on Predix’s development.

GE’s IoT predicament illustrates just how complex the engineering and management challenges of the Internet of Things really are.

The software needs of a sensor in a train brake pad are very different to that of fuel pump in a jet engine or the blade controllers of wind turbine.

Added to that is the challenge of organising, storing and securing the information these devices collect. This is the main reason why GE is moving its data management services to AWS and Microsoft Azure.

That a company with the resources and top level commitment of GE is struggling with this underscores the complexity of the internet of things. That complexity is something every IoT advocate and connected device vendor fails to consider at their, and their customer’s, peril.

Securing the future workspace

HPI’s Secure the Future Workspace event focused on the risks of enterprise printing, but the discussion applies to all of the Internet of Things

This post is part of a corporate blogging assignment for HPI and IDC covering their Secure the Future Workplace event.

Security is probably the Internet of Things’ greatest weakness and probably the first devices to illustrate the weakness were networked office printers.

For HPI, the devolved printer and hardware arm of Hewlett-Packard, those IoT weaknesses is an opportunity to showcase their products. However the security of printers is only the tip of a frightening iceberg of technology risks facing businesses and homes.

Security starts at the top

The first keynote for the morning was Simon Piff, Vice President of IDC Asia/Pacific’s IT Security Practice Business.

Simon gave an overview of the challenge of digital transformation and the risks involved.

To Simon, digital transformation has five different aspects within an organisation – Leadership, omni-experience, information, operating model and workforce transformations – all of which have different demands upon management.

One thing he sought to emphasise during his keynote is an organisation’s IT security is a top down process. “If your CEO doesn’t care about cyber-security then how are you going to execute?” He asks.

For printers he makes an important point. “They are essentially a single function server.” He says, “this is another server.”

“There haven’t been headlines about printer hacks but we are about to hear about them.”

Simon’s points about enterprise security and networked printers are something that all computer users, be they in home or business, understand – almost every connected device can be a network server. Being hacked is a real risk for everyone.

Death of the perimeter

“Don’t accept complacency,” is the key message from the second keynote speaker, Edmund Wingate.

Edmund, HP’s Vice President and General Manager of the company’s JetAdvantage Solutions division, described how securing a company’s networking perimeter and relying on firewalls was “backward looking.”

In the printer world, that the typical office device has over 250 settings alone creates risks for network administrators and security officers.

Compounding that problem is the use of proprietary software in these devices. A plethora of custom operating systems, many of them based on outdated Linux distributions, opens opportunities for an infinite range of exploits.

It’s better for the industry and vendors like HP to be open about the systems they are using and any vulnerabilities they find as otherwise governments will be forced to step into the space, warns Edmund. “The absence of standards lets things percolate too long.”

Edmund’s point about proprietary and old software are important aspects in the entire Internet of Things security discussion. That there will be billions of devices ranging from network printers to traffic cameras and connected kettles running antiquated software is a problem the entire IT industry will have to manage.

When your networked is hacked

The day’s final session was a panel featuring Simon Piff, Managing Director ANZ for IDC; Carl Woerndle, Executive Director of Elevate Security; Hugh Ujhazy, Associate Vice President, IoT Practice Lead, IDC APeJ and Edmund Wingate.

Carl was the proprietor of Distributed IT, an Australian domain registrar that was spectacularly hacked in 2011. The damage done to the business was so debilitating that it eventually forced the company out of business.

The alleged perpetrator turned out to be an unemployed Australian truck driver with no formal IT qualifications who had 700 other companies targeted. It’s a sobering lesson on how businesses are vulnerable.

Random attackers are the norm, Hugh Ujhazy pointed out, and ransomware is another factor which wasn’t widespread when Distributed IT was hacked.

Ujhazy sees Blockchain as the opportunity to rethink security. “We are on the cusp of changing the way we deal with devices and applications,” he says.

The consensus from the panel was all enterprise networks are vulnerable to inside threats – whether they are IoT devices like network printers, disaffected individuals, malware or hackers. For executives and boards, that’s an important message on how critical security is in the modern organisation.

Juicing innovation

The Juicero’s expense, built in obsolescence and unnecessary waste is emblematic of everything that’s wrong with the current Silicon Valley culture.

Every tech boom has its excesses and it’s hard to go past the Juicero as the most egregious of today’s mania.

A number of high profile investors, including Google’s venture capital arm, have poured $120 million dollars into the internet connected device that squeezes juice from pre-prepared pouches of pulped fruit and vegetables.

Bloomberg found the devices don’t a great deal as the juice can be squeezed out of the packs by hand, which is just as well given the microchipped pulp containers can be disabled by the manufacturer.

While the Juicero aims to be the juicer equivalent of the Keurig coffee capsule, the device’s expense, built in obsolescence and unnecessary waste is emblematic of everything that’s wrong with the current Silicon Valley culture.

The fundamental question of any business idea is ‘what problem does this solve?’ It’s hard to think of anything the Juicero fixes.

Mining for jobs in an automated future

Increasingly automated mines show how the jobs of the future don’t lie in old industries.

While politicians clamour to ‘bring jobs home’, automation is increasingly taking those jobs away with the mining industry being the best example.

In 2015, McKinsey looked at the effects of automation in various US industries and found the production component of mining could lose over 80% of its jobs in coming years.

In a piece for Diginomica this week, I looked at a case study featuring Western Australia’s Fortescue Metal Group (FMG) from the recent AWS Summit in Sydney.

Slashing costs

When Fortescue planned their Solomon groups of iron ore mines in the Pilbara region of North-Western Australia in 2010, they estimated 75 manned trucks would be needed. As it turned out they only needed 49 robotic vehicles.

The savings, both in capital expenditure and operational costs was substantial and the entire operation saw its costs nearly halved.

It’s not just trucks becoming autonomous, functions like drilling and explosives laying are also being automated reducing costs and risks even further.

Dashed hopes

So mining communities like those in the United States hoping Donald Trump will bring back prosperity or Australians who believe a billion dollar subsidy to an Indian coal mining company will guarantee jobs are doomed to disappointment.

A modern mine is likely to employ more workers in an office thousands of miles away than on the site itself. Where once the surrounding region would get hundreds of jobs from a large mine, today it’s only going to be a handful.

It isn’t just the mine workers themselves though, McKinsey’s study also forecast the mining industry’s administrative workforce could see 90% of jobs going while senior management had the potential of being 99% automated.

Beyond blue collar roles

That this wave of automation will affect ‘white collar’ jobs as much as trades or unskilled workers isn’t new – this piece in 2015 for The Australian described how many of the ‘knowledge economy’ jobs will soon be done by robots or artificial intelligence.

Mining is a good indicator of where technology and employment is heading. We, and our political leaders, are going to have to think carefully where the future jobs are coming from as they aren’t going to be found in resurrecting old industries.

Hacking the connected vehicle

American farmers hacking their tractors with Ukrainian software are a taste of what’s to come in the connected economy.

What happens when a vehicle manufacturer locks down their products’ software? John Deere’s customers are finding out as American farmers turn to Ukrainian software vendors for software to maintain their tractors.

John Deere’s behaviour is extreme as almost every component of a modern tractor has a software component which leaves farmers at the mercy of the company’s dealers and authorised mechanics.

So understandably the farmers are finding ways to hack their equipment to reduce downtime and costs, something permitted in the US after an exemption to the Digital Millennium Copyright Act (DCMA) was granted to vehicle software.

Vendor control over connected vehicles is a bigger problem for consumers than just maintaining the software, as the information collected from these devices becomes more valuable who controls that data becomes more important.

With global supply chains, increased regulatory requirements and demanding markets, the agricultural industries are probably leading the world in applying the Internet of Things and Big Data, so the challenges faced by farmers are things which will affect us all.

As everything from toasters to motor cars become connected and dependent upon code, the conflict between proprietary software, open markets and user rights is going to grow.

Consumers and the free market can only do so much to control the flows of data and who owns them. It’s hard to see how governments can’t become involved in how information is owned, traded and stored.

Deeper in data and debt

Data tools are getting more powerful as the information collected about us grows. It presents us with some important choices

Data collection agency Experian’s deal with Finicity to collect and process borrower information is an example of the how Big Data is being used by the financial services sector.

Recently I wrote a piece for Fairfax Media on the Science of Money which included some quotes from Experian’s Australian managers. They were quite explicit about their use of data.

That a company like Experian is adopting more advanced analytics isn’t surprising given the power of the tools available. What’s also driving the adoption is the proliferation of devices available to track people.

Notable among those devices are personal assistants, as David Pogue writes in Scientific American, household technologies like Amazon Alexa, Google Home and Apple Siri are vacuuming up huge amounts of data on our behaviour, likes and dislikes.

Increasingly all of this is being fed into machines that determine our suitability for marketing campaigns, credit and financial services.

For companies like Experian this is a massive opportunity although the focus on credit suitability betrays a mindset more suited to the 1980s finance boom than the more complex times of the early 21st century.

It’s hard though not to think that given a choice the finance sector will happily use these tools to take us into another subprime lending crisis which would be a shame as these technologies’ potential for allowing us to make better decisions is immense.

How we use these tools will define our businesses, economies and communities over the next thirty years. We need to be careful about some of the choices we make.

The science of money and data mining

The use of data mining by private and government agencies is widespread and only going to become more so. Do we care about the consequences?

Last week I wrote a piece for Fairfax Metro – the Sydney Morning Herald and Melbourne Age – looking at how government agencies and private credit companies are mining data.

That story sparked a range of interest with my doing a twenty minute segment on ABC Brisbane today on the topic which morphed into a deeper discussion on surveillance, particularly with the Australian government’s ‘metadata’ laws.

I’ll also be talking on ABC Radio Perth on Monday, March 6 about this story at 6.15am local time (9.15am Sydney and Melbourne).

In the wake of the Australian government’s Centrelink scandal – a national disgrace that is only getting worse – it’s worthwhile discussing exactly what data is being gathered and how it is being used.

The answer is almost everything with commercial operators like Experian pulling in data from sources ranging from credit card applications to social media services although store loyalty cards remain the richest information source.

As the Australian Tax Office spokesperson pointed out, none of this is particularly new as they have been collecting bank deposit data since the Federal government introduced income taxes in the 1930s.

The arrival of computers in 1960s changed the scale and scope of tax offices’ abilities to track citizens’ finances and gave rise to the major commercial credit bureaus.

With the explosion of personal electronics and internet connected devices in recent years along with increased surveillance powers being granted to government and private agencies, that monitoring is only going to grow.

The best citizens can expect is to have their data protected and respected with financial providers only using what is ethical and relevant in determining our access to banking and insurance products.

Politically the only way to ensure that is to make it clear through the ballot box, the question is do we care enough?

Bringing the IoT to Australia’s far north

James Cook University in the Northern Australian city of Cairns hopes to become a leader in internet of things research

In the tropical north of Australia, one university is looking at using the Internet of Things to expand the reach of its research and open new opportunities for the local economy.

On Monday James Cook University opened Australia’s first university IoT lab in Australia.

Based at the Cairns campus in Far North Queensland, the lab is part of the university’s new Internet of Things engineering degree and is supported by Chinese telco vendor Huawei.

The university, which also has campuses in Townsville and Singapore, boasts expertise in areas such as marine sciences, tropical ecology and tropical medicine, all of which are relevant to the IoT and made more relevant by Cairns being the main service centre for much of Australia’s remote Top End and the Torres Strait.

Part of a central mission

“The Internet of Things is based on something that is central to our mission in the Tropics: building greater connectivity between people, place and technology,” said the university’s Vice Chancellor Professor Sandra Harding.

JCU’s IoT degree, the first of its kind in Australia, combines the study of electronic engineering with internet technologies, wireless communications, sensor device, industrial design and cloud computing.

Currently the IoT faculty has 57 first year students, which the university hopes to grow to over 200. The head of the IoT faculty, Professor Wei Xiang, explained why the university decided to offer this course.

Economic drivers

“Primarily it’s driven by the economy, Australia is transitioning from a mining boom to a knowledge and innovation driven economy. So in the middle of 2015, JCU decided to offer an engineering degree in Cairns.”

“The IoT places nicely into traditional strengths at JCU in fields like marine science, marine biology and remote medicine, for example we can use the IoT for reef condition monitoring and our Daintree Rainforest project.”

An electronics Engineer himself, Professor Xiang sees the IoT as the future of industry and leapt at the chance to lead a course when the opportunity arose.

“In the middle of 2015 I thought, ‘this is what I want to do as this is where the future is.'”

Smartcity opportunities

Along with the remote health, marine science and agricultural aspects the City of Cairns itself offers smartcity opportunities. As a moderate sized town of 142,000 relatively isolated from the rest of Australia, Cairns has large tourist traffic coupled with weather extremes – the city gets nearly two meters (80 inches) of rain every summer. Making it a good test bed for new city technologies.

“Cairns Regional Council is very interested in smartcities, I’ve been working very closely with the city council and its innovation team,” says Professor Xiang. “We are also rolling out our smart campus.”

Part of the smart campus initiative is the university installing a NarrowBand-IoT base station provided by its program supporter, Chinese telecoms giant Huawei.

Along with supporting the IoT lab, Huawei also plans to offer JCU IoT students the opportunity to travel to Huawei’s global headquarters in China and its Australian headquarters in Sydney as part of its Seeds for the Future program.

“It gives our students and staff an experimental platform that conforms to the latest IoT international standard,” Professor Xiang said. “It means that as we design devices and sensor networks we can test and configure them using that standard.”

The university’s Vice Chancellor, Sandra Harding shares Professor Xiang’s enthusiasm. “From designing smarter cities, to growing precision agricultural systems, monitoring natural environments in real-time, and creating clever health solutions that work in remote communities,” she says. “We don’t want to be just a part of that future, we want to lead it.”

Paul travelled to James Cook University’s Cairns campus as a guest of Huawei.

Rethinking artificial intelligence and the smarthome

Facebook founder and CEO Mark Zuckerberg spent 2016 experimenting with artificial intelligence in his smarthome and came to some interesting conclusions about AI and machine learning

What happens when the founder and CEO of one of the world’s biggest tech companies decides to create a genuinely smart home? Facebook’s Mark Zuckerberg spend 2016 finding out.

“My goal was to learn about the state of artificial intelligence — where we’re further along than people realize and where we’re still a long ways off,” Zuckerberg writes in a blog post.

The immediate problem Zuckerberg faced in creating his home made Jarvis automation system was many household appliances are not network ready and for those that are, the proliferation of standards makes tying them together difficult.

For assistants like Jarvis to be able to control everything in homes for more people, we need more devices to be connected and the industry needs to develop common APIs and standards for the devices to talk to each other.

Having jerry rigged a number of workarounds, including a cannon to fire his favourite t-shirts from the wardrobe and retrofitting a 1950s toaster to make his breakfast, Zuckerberg then faced another problem – the user interface.

While voice is presumed to be the main way people will control the smart homes of the future, it turns out that text is a much less obtrusive way to communicate with the system.

One thing that surprised me about my communication with Jarvis is that when I have the choice of either speaking or texting, I text much more than I would have expected. This is for a number of reasons, but mostly it feels less disturbing to people around me. If I’m doing something that relates to them, like playing music for all of us, then speaking feels fine, but most of the time text feels more appropriate. Similarly, when Jarvis communicates with me, I’d much rather receive that over text message than voice. That’s because voice can be disruptive and text gives you more control of when you want to look at it.

Given the lead companies like Amazon, Microsoft, Google and Apple have over Facebook in voice recognition, it’s easy to dismiss Zuckerberg’s emphasis on text, but his view does feel correct. Having a HAL type voice booming through house isn’t optimal when you have a sleeping partner, children or house guests.

Zuckerberg’s view also overlooks other control methods, Microsoft and Apple have been doing much in the realm of touch interfaces while wearables offer a range of possibilities for people to communicate with systems.

The bigger problem Zuckerberg identifies is with Artificial Intelligence itself. At this stage of its development AI struggles to understand context and machine learning is far from mature.

Another interesting limitation of speech recognition systems — and machine learning systems more generally — is that they are more optimized for specific problems than most people realize. For example, understanding a person talking to a computer is subtly different problem from understanding a person talking to another person.

Ultimately Zuckerberg concludes that we have a long way to go with Artificial Intelligence and while there’s many things we’re going to be able to do in the near term, the real challenge lies in understanding the learning process itself, not to mention the concept of intelligence.

In a way, AI is both closer and farther off than we imagine. AI is closer to being able to do more powerful things than most people expect — driving cars, curing diseases, discovering planets, understanding media. Those will each have a great impact on the world, but we’re still figuring out what real intelligence is.

Perhaps we’re looking at the what intelligence and learning from a human perspective. Maybe we to approach artificial intelligence and machine learning from the computer’s perspective – what does intelligence look like to a machine?

Computing on the edge

Amazon announced another range of services and products at their annual Las Vegas conference, but are they becoming too powerful?

As with every vendor conference, this year’s AWS Re:Invent convention in Las Vegas bombarded the audience with new product announcements and releases.

One of the interesting aspects for the Internet of Things was the announcement of Amazon Greengrass, a service that stores machine data on remote equipment which combines the company’s Lambda serverless computing and IoT services.

Further pushing Amazon’s move into the IoT space was CEO Andy Jassy’s announcement that chip makers such as Qualcomm and Intel will be building Lambda functions into their chipsets, further embedding AWS into the ecosystem.

Jassy also touted the company’s new Snowball Edge, a slimmed down version of their Snowball data transfer unit that also include some processing features, that is aimed at storing machine data at remote or moving locations such as ships, aircraft, farms or oil rigs.

That latter function ties into one of the key aspects about the Internet of Things – that most data doesn’t have to, or can’t, be transmitted over the internet. This is something companies like Cisco have focused on in their edge computing strategies.

With AWS dominating the cloud computing industry – Gartner estimates the company is ten times bigger than the next 14 companies combined – the worry for customers and regulators will be how much control the organisation has of the world’s data.

It’s hard though not to be impressed at the range of products the company has, and the speed they get them to market, the onus is on companies like Microsoft, Google and Facebook to allocate the resources and talent to match AWS in the marketplace.

Time to rethink IT security

Last weekend’s webcam launched cyber attacks are a warning that we need to take security seriously

Last weekend a cyberattack launched from compromised webcams crippled a number of high profile services. In response, the Chinese manufacturer has withdrawn the devices from the market.

That dodgy webcams should have been used to launch a massive DDOS doesn’t surprise anyone who’s spent any time in the home automation field. These problems are endemic in the Internet of Things.

In the early 2000s I became involved in a home automation company through my IT support business. Basically we were kitting out Sydney’s harbourfront mansions with state of the art technology.

Very quickly I realised something was wrong. Almost all the home automation and CCTV systems were running on outdated, insecure software. The leading brand of home security systems used servers running on an old version of Windows 2000 at a time when malware was exploding.

It wasn’t a matter of if, but when, these systems would become hopelessly compromised given the networks they were running on were shared with the home users.

The real concern though was when I raised this with the vendors, installers and designers – no one cared. It was clear security wasn’t a concern for the market and the industry.

We could have patched the systems and boosted their security policies but given the shoddy software being used – mainly DOS batch files – and the assumed file permissions we’d have completely broken the systems and it would up to us to fix it given the attitudes of vendors and clients.

After realising this problem was industry wide I pulled the pin on that business venture as I wasn’t prepared to carry the legal risk and moral obligation of helping install dangerous equipment into people’s homes or businesses.

I’ve since watched as the Internet of Things has become fashionable with the knowledge that the industry’s cavalier attitude towards customer security hasn’t changed.

Now we’re at the stage where script kiddies can launch massive attacks from compromised webcams – God knows what the serious bad guys like state sponsored actors, criminal organisations and commercial spies are up to with these things – which shows the industry’s robotic chickens have come home to roost.

What last weekend’s events show is we have to demand better security from our technology suppliers. That though comes at a cost – we’ll pay more, we’ll have to sacrifice some convenience and we’ll have to spend time maintaining systems.

Are we prepared to wear those costs? Is the tech industry prepared to move beyond it’s ‘good enough’ attitude toward security? Are governments prepared to legislate and enforce proper design rules?

We may not have a choice if we want to enjoy the benefits of technology.

Trust, security and the internet of things

It may prove impossible to secure the Internet of Things. If so, we’re going to have to develop new trust mechanisms.

I’ve spent the last week in Las Vegas attending the Black Hat and DefCon security conferences. Among much of the discussion about protecting oneself against the misuse of technology, one thing that stood out was the focus on the Internet of Things.

Listening to some of the discussions and speaking to various people, it’s increasingly clear the consensus is the IoT is effectively unsecurable – the range of devices connected to the internet is just too great to be protected.

Compounding the problem are the plethora of poorly designed devices where security is, at best, a vague afterthought along with an older generation of equipment that was never intended to be connected to the public facing internet.

Given many of these devices are going to be critical to business and individual lifestyles, their reliability and quality of the data gathered by them is going to increasingly come into question and the systems that rely upon them are going to need ways to validate the information they receive.

Perhaps this is where machine learning and artificial intelligence are going to be valuable in watching for anomalies in the information and flagging where problems are happening within networks.

As those networks become more essential to society, we’re going to have build more redundancy and robustness into our systems, the key component though may be trust.