Davra Storms MQ
Derek Collins is a Vice-Chairman of the Chamber of Commerce of Hong Kong who’s adding to this interview incredible industry insights. Great reading for everyone inside and outside the Internet of Things industry.
Thank you for participating Derek.
I am Technology Consultant with 20 plus years of senior management experience, living in Hong Kong for nearly three years now. Before coming to Hong Kong I garnered ICT, telecommunications, mobile & M2M technology experience in Europe, Asia and the Americas. Most recently, I have spent time analysing, as a consultant, The Hong Kong Mobile Market, SME Base, Smart Utilities, Connected Shipping, and Asia Pacific Cloud Computing Players and their strategies. I have ICT experience that I gained with leading organisations in Financial Services & Manufacturing Sectors, working with the likes of Ericsson, BT Global Services, Nortel, CityReach, Telindus & Prime Computers Inc.
I am a Board Director of The European Chamber of Commerce in Hong Kong and of The Irish Chamber of Commerce in Hong Kong & Macau. I am passionate about social media technologies, innovation, start-ups, independent movie making and research into ‘The History of The Irish in Hong Kong’. I have been working with the Hong Kong Film Festival Board & The Irish Film Board to launch an Irish Film Festival in Hong Kong.
Build a profitable business – can your organization make money? Or afford to invest?
Launch your connected service.
Once you have identified a business model that leverages the power of The Internet of Things (IoT) for your business, you should think about:
• Enable devices to connect to the wireless Internet.
• Integrate into mobile operator networks, anywhere and everywhere in the world.
• Define use cases and map out business and operational requirements for every stage of your product lifecycle.
• Integrate your new Internet of Things business with your existing infrastructure.
• Configure application programming interfaces (APIs) to meet your unique business needs and the requirements of each and every mobile operator you work with.
• Deliver the new applications and services to the market.
Manage your connected service.
To actually run this Internet of Things business you’ve launched, you’ll need to think about:
• Monitoring your connected devices in real-time, tracking data usage, connectivity, etc.
• Run diagnostics to identify and troubleshoot issues on any device, anywhere at any time.
• Define the events that trigger each device’s activation and deactivation.
• Set up real-time controls that give you visibility into every deployed device and let you manage data usage.
Monetize your connected service.
Monetizing your connected service and ensuring that it is profitable also involves getting a handle on a complex range of moving parts. You should also think about:
• Set rates for each type and level of service you offer and define how those plans will be managed over time (free trial periods, introductory discounts, subscriptions of different lengths, renewal plans, split billing, etc.)
• Handle billing, charges, and payments to and from customers, operators, OEMs, partners, suppliers, etc.
• Establish data usage thresholds and cost controls.
• Gather intelligence from all the data you’re now gathering and use it to create new revenue streams, optimize processes, build new products, and improve existing ones.
• Analyze and optimize your supplier costs in real-time.
• Automate every stage of the billing process.
Web 3.0 is the designation generally associated with the evolution to an “intelligent web.” It’s anticipated that the intelligent web will address the lack of structure and organization in Web 2.0 by linking information from disparate sources and systems to make the web even easier to use, more efficient, and more valuable to its users. Web 3.0 is also referred to as the “semantic web” because it will use semantics—the study of meanings behind words and information—to interpret searchable content and thus deliver more appropriate and relevant content to end-users.
Try to Find Opportunities
Take inventory of the systems in your enterprise that will most likely evolve from proprietary platforms to more open access and standards-based applications; these are probably systems that you are considering moving to the cloud today. During your inventory process, identify usage scenarios that could elevate levels of agility, competitiveness, and business performance if the systems were more integrated, automated, and aware.
During your evaluation, look in particular for areas in your business where lack of information is a problem, or where your current methods for using vital information are limited. According to Forrester Research, “By focusing on business pains arising from a lack of information, application development professionals can identify areas where semantic technology might help.”
Begin & Try to Adapt Enterprise Data
Companies can take numerous, tangible steps now to prepare their enterprise data for the Web 3.0 and IoT environment. Here are some possible challenges:
• Try and Initiate a master data management project to establish consistency across all data sets in the enterprise.
• Try to Incorporate semantic technologies into enterprise search.
• Lead cross-functional efforts to develop taxonomies and ontologies of enterprise information. (People often refer to a taxonomy as a “tree”, and extending that analogy I’d say that an Ontology is often more of a “forest”)
Try and Conduct Pilot Projects
Begin experimenting. Give your developers opportunities to work on special projects to see if a semantic technology is feasible and suitable for your company. If an idea proves feasible, expand it into a pilot project. Your developers will gain skills and experience and your organization will gather qualitative and quantitative insights into the possibilities the technologies might bring to your business, and make IoT bugger that Web 3.0
Try and Focus on the Customer
Because IoT or IT As a Service will find their earliest uses among consumer-facing applications, now is the time to understand how customers might want to pull and use data from your organisation in a Web 3.0 environment. Consider how your customers’ access to readily-available and automated intelligence will affect your industry and how your business can adapt to seismic disruptions to core business models.
Try to Examine the customer experience you provide for your customers today. Keep in mind that IoT will be driven by data containing user identity, profile, and preference information, including location and behavior patterns. Consider how your company could try to change the customer experience if existing technology barriers were removed and the company could gain access to previously unavailable customer data to develop insight into their past, current, and future behaviors.
What does the internet of things really means in terms of bringing real value for companies and people?
There are lots of talk about, Connected Logistics, Smart Grid/Metering/City, Connected Shipping, Connected Car (eCall), and your fridge ordering new milk. M-Health in emerging markets could be key and a life-saver. Blood samples taken and information transmitted via 4G/LTE to a Clinic for analysis.
The eCall – 112 Project in Europe could save 1000’s of lives if cars involved in a crash automatically dial the emergency services with Geo Location information, via embedded SIMS – Cloud Platform – and dispatching ambulance/helicopter services where drivers are incapacitated to make a 999/112 Call.
Companies can get real-time data and save costs. British Gas are installing Smart Meters across the UK. Real-Time accuracy across the Mobile Network into their back-office. No more Man-in-a-Van and consumers can a two-way relationship with their supplier.
One Simple example of a major cost-saving relative to The IoT. In January of 2017, the National Highway Traffic Safety Administration issued recalls for two vehicle models. One was for a pickup truck from a major auto manufacturer with around 370,000 units on the road. Another was for Tesla’s Model S sedan, 29,000 Both recalls were intended to reduce the risk of fire during an accident. Both required a software update to be installed.
Even though a software update sounds relatively simple, recalls of this kind have historically been a tremendous pain for everyone. For the car manufacturers and the dealerships that support them, it means contacting all the affected car owners, paying for mechanics, and suffering blowback to the brand. For car owners, themselves, it means making the time to bring the car in and waiting for it to get repaired.
This is exactly what happened to the large manufacturer: it had to recall 370,000 trucks to their dealerships and pay all the associated costs. Given Tesla’s smaller size and its status as an upstart, a full-on recall of 29,000 Model S cars could have done real damage.
But for Tesla, whose Model S sedans are connected to the wireless network at all times, it was a completely different story. Instead of recalling 29,000 cars to Tesla’s repair shops, Tesla prepared the software update and pushed it out to every single one of its Model S cars. The whole thing happened while the cars were turned off. When their owners turned them back on, a notification about the update was waiting for them on the Model S’s dashboard touchscreen. Thanks to Tesla’s connected cars, what could have been a small disaster turned into a potent demonstration of Tesla’s position as one of the most forward-thinking car makers in the game.
Derek M2M connectivity is not a new concept. In fact, the roots of M2M extend back over several decades and include basic fleet management solutions and SCADA (supervisory control and data acquisition) solutions. Traditionally, M2M solutions have been conceived and deployed as ‘stovepipe’ (or standalone) solutions with the aim of improving (or enabling) a specific process, and without consideration of how these solutions might one day be integrated into a wider business context. In the case of some early fleet management solutions, the need was to improve the monitoring of high-value shipments (particularly deliveries of cash), often for the purposes of driver security.
An early M2M developer would have had probably only to contend with maybe three key elements of an overall M2M solution:
Devices: Consideration of the capabilities of an individual device, in terms of the operating environment, use cases, sensing, actuating, processing and human interface capabilities.
M2M application environment: Including a diverse range of considerations and restrictions relating to any applicable operating systems, carrier communication requirements and the applicable capabilities of any potential M2M middleware providers.
M2M application logic: As the element of the overall solution that actually solves the developer’s problem, this is the piece the application developer would have actually wanted to build, although the functionality and flexibility of any specific application would have been hindered by the need to reflect any desired application capabilities through the application environment described above.
The potential key areas in which an IoT Application Platform differs from the more ‘traditional’ M2M platform environment could include:
• Carrier and communications integration. A successful IoT Application Platform must develop ‘meta-APIs’ that allow IoT application developers to integrate to multiple carriers (and multiple connectivity support platforms) using a single API.
• Device management. A successful IoT Application Platform must build a wide-ranging library of cross-industry drivers and not rely exclusively on VPNs to local gateways to control local devices.
• Application Development. IoT Application Platforms should offer sophisticated tools to create business rules and integrate into business processes. Crucially, IoT Application Platforms must offer support for Big Data analytics and complex event processing, necessitating a tightly and robustly defined data model.
• Application Management. Maybe an IoT Application Platform should offer both software and firmware updates, whether on the M2M connected device or on a gateway (if any). IoT Applications must be updateable to appropriately integrate with any updated operating environment.
• Operations Environment. One of the most materially different aspects of IoT Application Platforms, when compared to more traditional M2M platforms, is the management of user authorization. The presence of multiple information sources from multiple applications forces the adoption of a robust user and identity management system. Additional considerations of the sensitivity (privacy) of user data for various analytical processes must also be taken into account, with the IoT Application Platform essentially taking on the role of a trusted third party with regard to data privacy.
• Scalability. IoT Application Platforms potentially could be highly scalable, and able to handle huge volumes of any (and all) of: users, event volumes and backend processing events. Many event management tasks will be real-time (or so near real-time as to be more efficiently processed as if they were), and so code produced by IoT Application Platforms must be highly efficient.
I live in Hong Kong, a Vertical City of 7 million people. Smart Metering or Connected Buses are not an issue, very few drive a car, so OTT Players sending targeted messages to my i-Drive in my BMW 7 Series is not a benefit or a reality. People are concerned about Pollution, Food & Water Security, Health of their families and an aging population. So This Society here, a very smartphone tech-savvy society wants a healthier future. I feel that Hong Kong is a great testbed and barometer to try and develop new M2M/IoT Platforms and solutions.
One example of a future demand: IoT M2M technology for Urban Agriculture in the US
Although we see in some cities how urban farms are popping up on every corner of the street, many of us probably have always doubted the genuineness of all those small farming initiatives that are left behind after one season of fun. Nevertheless, some developments in this ongoing hype are interesting to mention because the urban agriculture scene seems to become mature.
Aerofarms was one of the first pioneers who wagered for using technology in Urban Farming.
With all the media boom that is taking IoT and wearable’s is not surprising that we find many entrepreneurs and investors working or looking for solutions addressing emerging urban agriculture. Some companies with successful crowdfunding projects to look at: Plant Link, HarvestGeek and GrowCube.
AquaSpy helps you increase your yield and save water, energy and chemical. Each crop has different needs for water and nutrients during its specific growth cycle. AquaSpy data lets you give your crops exactly what they need precisely when they need it.
The company Agricultural Food Systems sells a device that measures the tenderness of beef. TenderID is a handheld device with three blades that are stuck into a beef carcass at the processing plant
You could have a glass of orange juice made with oranges picked by a robot. Energid Technologies is testing a prototype robotic picker in a Fort Myers (Fla.) A truck-mounted arm with several pneumatic tubes guided by a camera locates the oranges for picking.
Great question indeed. We certainly have created a ‘buzz-word’ or some form of ‘Hype’, reminds me of many years ago when IP Telephony was going to be the panacea of telecom costs. We talked it up for years or Y2K! Hardware vendors made lots of money from upgrades to Y2K Readiness.
As more data becomes available from an abundance of sources both within and outside, organizations are seeking to use those abundant resources to increase innovation, retain customers, and increase operational efficiency. At the same time, organizations are challenged by their end-users, who are demanding greater capability and integration to mine and analyze burgeoning new sources of information.
Big Data provides opportunities for business users to ask questions they never were able to ask before. How can a financial organization find better ways to detect fraud? How can an insurance company gain a deeper insight into its customers to see who may be the least economical to insure? How does a software company find its most at-risk customers—those who are about to deploy a competitive product? They need to integrate Big Data techniques with their current enterprise data to gain that competitive advantage.
When I was consulting with Ericsson in Hong Kong last year, and investigating the Connected Ship ‘Maersk Story’, where Ericsson has successfully connected the refrigerated containers to a satellite service, to monitor the conditions of the engine, bunker, crew-welfare, etc., I found the Analytics of this Data to be the ‘secret sauce’.
One Major Challenge: The abundance of information was enormous but having the right tools to decipher the right data in order to have the right conversation with a ship captain was the ‘Killer App’.
Another Challenge: There are multiple ways to measure Big Data—which can be based on volume, variety, velocity, and value. While managing all this data is one thing, another key consideration with these growing volumes and the variety of data is its criticality to the business. Keeping data highly available and secure is an ongoing challenge for data managers. How much data presented re infrastructure and database systems can be lost without repercussions to the organization? For example, can the business afford the loss of a store of unstructured data, such as graphics files, such as videos or weblogs?
While many organizations are still struggling to understand the business value of Big Data, most consider it to be extremely or very important to their business. The greatest opportunities Big Data offers are in competing more effectively and growing business revenue streams. Most Big Data initiatives currently come out of the IT department, but the first business applications are being seen in marketing and sales—an area typically already comfortable with data analytics. This could be a solution to new initiatives.
Getting the attention and support of the C-suite for such efforts often can be challenging. What are the main barriers to using Big Data within companies? The leading issue is lack of budget, Big Data simply is not yet a business management priority. Technology issues also get in the way, Often, organizations attempting to manage Big Data have diverse environments in which it is difficult to take advantage of Big Data. Data may be highly distributed, requiring a Big Data strategy that is built on a combination of different storage devices and different databases that store structured data.
With today’s new workloads come large amounts of data, such as log records as well as transaction-related information. Big Data may offer significant opportunities for analysis and insights on a scale never seen before in business, but, some do not feel their existing data infrastructure is ready for the job. The success of Big Data analytical efforts depends on how well organisations can store, manage and render actionable information from data that is streaming in from users and systems from both within and outside.
The question is, will companies turn to cloud technologies to address these challenges? The public cloud is not yet playing a major role in Big Data initiatives. Very few currently use a cloud provider to support Big Data initiatives. Some are considering taking such steps, however.
However, some are using or implementing ‘Hadoop’ are far more likely to be embracing both public and private cloud networks. The connection between cloud adoption and Big Data isn’t clear-cut yet. How do companies support open source tools within their organizations? For the most part, some pursue measures most commonly associated with the open-source world – pulling resources from the web. Some rely on ad hoc internal resources and community support.
Develop a business case
Big Data may be a headache at times for data professionals, but for the business, it represents Big Opportunities. Never before have decision-makers had access to insights from so many parts of the business at once. However, data managers and professionals need to help business decision-makers “filter” through the massive amounts of data, and noise, to identify key nuggets of pertinent information. This requires working with end-users to identify what types of data will have the greatest impact.
Get business buy-in and support
Big Data analytics only deliver value if they have the support and input of the business. The business needs to determine what data needs to be made available to analytic platforms, and what data isn’t as essential. In the survey, many respondents see this as a way to strengthen the relationship between IT and the business.
Develop an integration strategy between unstructured and traditional enterprise data
The levels of unstructured data flowing into enterprises are growing rapidly, and businesses are seeking ways to develop insights from this data. Today’s generation of solutions provide platforms to bring both unstructured and structured transactional data together into
a common environment.
Develop an integrated information management lifecycle strategy
Some data needs to reside online and be quickly accessible to end-users, while other forms of data can be less accessible and stored in an archive or backup systems. More Big Data flowing into organizations may place greater stress on current infrastructure, affecting application performance and availability. Data should be moved to tiered storage systems as part of an organization’s entire information management lifecycle processes.
Smart guess? In 5 years, Enterprise Consumers or Business Customers on a day-2-day basis will probably take for granted SMART Technologies and what IoT will give them on Savings, Opex, Control, and contribution their organisation’s ‘Green Foot Print’ for example. Governments and Green Lobbies may have strict ‘Carrot & Stick’ mechanisms for Smart Buildings as part of a bigger Smart Living Smart City Eco System.
In 10 years, Business Customers should enjoy full Public Cloud Offerings, Full Knowledge access of the Right Information when required, and wearables in-conjunction with Smart M-Health should enable a better Work-Life Balance of employees which will, in turn, have an impact on the day-2-day of the Enterprise Consumer.
When I look around Hong Kong and the little activity in this space, with the Mega-City Plans for The Great Pearl River Delta, with 20 million-plus inhabitants in this region, it is a daunting future, where GREEN agendas will be the Norm. (hopefully).
At the end of 2013, there were around 200 million cellular M2M devices in active use, and this number is expected to grow 3–4 times by 2019. Average M2M device penetration is around 2 percent of data subscriptions among measured networks, while it can reach 20 percent for those operators that focus on M2M. So, amazing possibilities ahead in the arena of Video, Sensors, Health, Knowledge, Security, Smart Living, Food Production, Appliances,
Various pilot programs are underway in the field of Smart Energy in the United States. This industry continues to work on the data traffic “aggregation” model, where the cellular connectivity may or may not extend directly all the way to the endpoint (or device) that is being monitored or controlled.
Remote monitoring of assets in the agriculture and energy sectors including oil and gas are also some major application areas for M2M in the Utilities and Industrial market. In 5 years this may be the norm. Mobile operators, such as AT&T, continue to work with strategic partners to bring complete remote monitoring, home automation, and smart grid and utility solutions to the market.
For example, AT&T’s Digital Life is a web-based remote monitoring and automation platform that is targeted at the home automation and home security market. Mobile operators believe that Connected Home solutions can help them increase their ARPU anywhere between $3 and $10 per connected home. Mobile operators clearly believe that their strategic assets, such as cloud platforms, help them to serve the needs of this high-value segment and thereby expand their offerings beyond voice, video, and data to Connected Home services.
Discussions have also been held over allowing utility companies to leverage the nationwide public safety LTE network to provide Smart Grid services. However, the final outcome of these initiatives remains unclear.
The Utilities and Industrial market are projected to have one of the highest, if not the highest, number of direct M2M connections. For example, out of approximately 150 million electricity meters presently deployed in the United States, even a 10 percent penetration of cellular connectivity to meters will result in more than 15 million meters being connected.
The term Advanced Metering Infrastructure (AMI) is also used to refer to these types of deployments. However, AMI is a subset of the overall smart utility framework that envisions digital communication overlays and interfaces with the utility networks. Within the utility segment, various short-range technologies will continue to co-exist with the cellular networks( that are used to provide long-range backhaul services).
The Internet of things and the technology ecosystem surrounding it are expected to be a $8.9 trillion market in 2020, according to IDC. In a nutshell, the Internet of things is the product of sensors, technology and networking all coming together to allow buildings, infrastructure and other resources to swap information. Today, the Internet of things and machine-to-machine data falls under the big data umbrella with projects just beginning.
IDC said the installed base of things connected will be 212 billion by the end of 2020, including 30.1 billion connected autonomous things. Intelligent systems will be installed and collecting data by this point.
According to IDC, the Internet of things will change everything and be “a new construct in the information and communications technology world.” IDC put the Internet of things technology and services spending at $4.8 trillion in 2012 and expects the market to be $8.9 trillion in 2020 and have a compound annual growth rate of 7.9 percent. Wow!
Thank you again for a brilliant interview, this is the start of something massive and we are super excited to be a part of it.
For more great industry insights follow @dcollinshk on Twitter.
Follow @Davra_IoT on Twitter for more great blog posts like this one.
Davra Storms MQ
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