By: John Gonsalves
According to Gartner, more than $440 billion will be spent on Internet of Things initiatives by 2020. Yet networking company Cisco recently found that only 26% of organizations so far have completed an IoT initiative they consider a success. That percentage isn’t pretty. And companies don’t have much time to climb a steep learning curve and thus avoid costly failures.
So what is preventing companies from getting IoT right? Much of the challenge derives from focusing on implementing technologies without a comprehensive, holistic plan. Sensors? Smart devices? Data analytics? Cloud-based processing? All necessary and helpful. But how will they operate together? How will they collectively transform data into usable information – delivered in time to act in real time? That takes thought. And the thinking must be in the C-suite.
Today’s IoT industry is maturing from stand-alone point applications to integrated systems that capture and process data to derive business insights and even quality of life outcomes. Smart parking solutions, for example, now leverage IoT to analyze parking inventory and guide drivers to available spaces, an outcome with great potential value projected to save hours, miles and even gallons of gas.
A more complex IoT “system of systems,” however, might integrate that parking platform with other IoT-enabled systems, exchanging data that leads to actionable insights. An owner/operator of parking structures could then optimize lighting use in different spaces, control climate for peak and off-peak times and temperatures, assess risks and security needs, respond to staffing shortfalls quickly, and even adjust prices for a particular facility based on volume, previous usage patterns, scheduled local events and consumers’ real-time needs.
An optimal pace to value
Companies have been slow to take their IoT solutions to this next level because they face genuine challenges. How to quantify the potential value to justify the investment? How to stay ahead of security risks? How to understand and leverage multiple complex technologies? Or identify physical installation and support services? Or aggregate, synthesize, store, analyze, act on and monetize their data?
To many, the feasibility of bringing partners and service providers together to create an end-to-end ecosystem is not yet clear. There is the pressure to anticipate integration points and ensure components and people work together. as well as understand and plan for the potential disruptive impact on the organization, customers and business models.
Nevertheless, developing an integrated IoT constellation of devices, sensors, actuators, gateways and network and cloud service providers, a new breed of IoT platform providers, along with analytics, specialty visualization and integration with enterprise applications – all designed to work together – is the best way to optimize results.
The IoT Value Chain
Components of the IoT value chain should include:
- Data capture. Data originates from sensors, actuators, controllers, devices and hardware in the field, but companies quickly learn that implementing a transformational IoT solution involves far more than adding sensors to their packaging, products and the machines that manufacture, deliver and service them. Sensors must collect data spatially (i.e., throughout a space) and temporally (i.e., across time), and be instrumented in such a way that vital signs can be signaled, collected and analyzed for downstream action. Such massive amounts of data must be cloud- and network-agnostic to ensure compatibility with various platforms.
- Data communication and storage. To maximize their value, cloud and network services platforms need to deliver operational insights by working with devices at the edge – that is, where the data is gathered. They must be multilingual (able to talk to any sensors using any communications protocol) and hardware agnostic, so that data can be integrated, synthesized and stored, making it available for future context-aware analysis.
- Data analysis and insights. Making sense of vast amounts of data and taking action is key to unleashing the power of IoT. Predictive analytics providers identify patterns, network effects or anomalies so undesirable outcomes can be anticipated and prevented. Such analytics prompt prescriptive action: Companies can course-correct on the fly – replacing a part or stopping an engine from overheating, for example – to optimize operational efficiency through improved asset performance and employee productivity. World-class algorithms must be domain-sensitive and industry-aware so they can be meaningfully applied to unique use cases; advanced visualization of data may be required in certain situations.
- Infrastructure & security. Beyond cloud and network service providers, IoT solutions at scale need end-to-end security from device to edge to the cloud (and the apps), distributed device management and distributed data management.
- Coordination between IoT components and systems of engagement. Systems of engagement may vary from mobile devices to advanced augmented/virtual reality (AR/VR), mixed-reality or other user interfaces. The focus of IoT solutions is now migrating beyond operations optimization to enable new business models (e.g., pay per use), imagine new products and services (e.g., software-based services), monetize data, etc. Indeed, the opportunities are massive as we develop and benefit from “system of systems.”
- Partners. The variety and range of technologies for the IoT is enormous, yet still immature. Each participant would do well to understand its role in the IoT ecosystem and get to know adjacent players to partner with to deliver smart, connected IoT solutions at scale. Scale implementations need physical deployment of sensors (and device instrumentation), the operations technology and the digital value chain. And they require a skilled system integrator that also knows the associated IT and heritage systems, to develop and orchestrate the combined ecosystem and, thereby, realize business value.
How to get started
A good systems integrator will start by asking the question, “What business problem do you want to solve?” From there, the company can help to create the business case for an IoT solution by articulating its value, be it cost reduction, revenue enhancement, asset optimization, customer experience transformation or increased safety.
Then it’s on to the heart of the engagement: defining new operational processes, recommending IoT-enabling information and operational technologies, identifying and classifying the right ecosystem players in the IoT value chain, and assembling and integrating them based on who plays best where.
Challenges certainly remain, but the opportunities for new revenue streams, increased operational efficiency and improved customer engagement have never been greater for companies that leverage end-to-end IoT solutions in consumer, commercial or industrial settings.
This article originally appeared on the Digitally Cognizant Blog
Cognizant (Nasdaq: CTSH) is dedicated to helping the world’s leading companies build stronger businesses — helping them go from doing digital to being digital.
New research predicts six key trends in the consumer IoT market
Smart home IoT company Viomi Technology and the International Data Corporation have jointly issued a white paper that identifies key consumer trends for the Internet of Things and the smart home.
With the smart home, connected services and the Internet of Things overall gaining greater acceptance it is important for businesses to understand where the technology is heading next. Focusing on the home market, smart home Internet of Things company Viomi Technology, in collaboration with the market intelligence company International Data Corporation (IDC), has issued a white paper that signals the key consumer trends that are set to shape the home IoT market over the next few years.
- Computing capabilities of consumer IoT devices will increase rapidly. For this, artificial intelligence is vital to the future development of consumer IoT. The main developments will be with sensing technology, data acquisition capability and decision-making intelligence.
- Different network protocols will work together as a hybrid network. The aim here is to provide consumers with stable and fast connection anywhere and anytime. This will be enhanced by 5G, and increased consumer expectations for connection anywhere and anytime.
- Edge computing and local storage will be widely used on smart devices. This move will improve computing efficiency and personal privacy.
- Consumer IoT devices will have more open integration in terms of technology. Interoperability should be achieved by breaking the boundaries between products, platforms, and applications.
- Human-device interaction will be more user-friendly and feel more natural. This will be seen with applications like voice-, image-, face-, and touch-based interaction.
- Smart devices will soon move into the stage of proliferation. The main growth area, the report suggests, will probably be in China.
The research will be presented by Viomi at the Appliances & Electronics World Expo in Shanghai, China on March 13, 2019.
At the same time, a separate report from market research firm Grand View Research predicts that the global smart home automation market will hit $130 billion by 2025, compared to $46.15 billion in 2016.
The cloud strategy that Microsoft is leading and that Google and Amazon are betting on is growing, report says
- According to Flexera’s RightScale 2019 State of the Cloud Report, the amount of large companies with a hybrid cloud strategy, or combining public clouds and data centers to store workloads, has risen from 51% to 58%.
- Microsoft is the leader in hybrid cloud, as it introduced its hybrid cloud Azure Stack in 2017.
- Google Cloud and Amazon Web Services have also announced hybrid cloud offerings in the past year.
For a long time, Microsoft has been touting hybrid cloud, or a mix of on-premises and public cloud services.
And in the past year, both Amazon Web Services and Google Cloud have followed suit, making major announcements around hybrid cloud. Companies often choose to keep some of their work on data centers due to regulations, especially in industries like health or finance, and analysts say this will not change anytime soon.
Indeed, 58% of companies with more than 1,000 employees are now pursuing a hybrid cloud strategy, up from 51% last year, Flexera’s RightScale 2019 State of the Cloud Report says.
What’s more, 84% of those companies have a multi-cloud strategy, which means that they store workloads on multiple public clouds, hybrid clouds or data centers. This rose from 81% last year.
Microsoft launched its hybrid cloud Azure Stack in 2017, and currently, Microsoft is the only company out of the top three cloud providers that has a generally available hybrid cloud.
Last November, Amazon announced a hybrid cloud offering calledAWS Outposts, and it will be available later this year. And in February, Google Cloud announced that it will make its hybrid cloud offering Cloud Services Platform available as a beta for customers, a move that company officials say is a part of its strategy to attract more enterprise customers.
Now, 45% of enterprises see hybrid cloud or a balanced approach being using public clouds and data centers as their top priority in their cloud strategy, the survey found. In comparison, 31% of enterprises see public cloud as their biggest focus.
The Flexera RightScale survey polled 786 respondents, 58% of which were large, 1,000+ employee corporations and 42% of which were small businesses.
This article was originally published on Business Insider. Copyright 2019.
Who will control the data from autonomous vehicles?
Self-driving cars, like many inventions of the data-driven age, collect huge volumes of data, relating to the performance of the car and geospatial information. Who will, and who should, own this data? A new study assesses the importance.
Researchers from Dartmouth College have questioned the ownership of data in relation to autonomous vehicle technology. As self-driving cars advance, there will be a vast quantity of data amassed from navigational technologies. This leads to important questions that need to be asked about data privacy, ownership, cybersecurity and public safety. This is in the context of the mapping data being collected and analysed by the companies that manufacture the navigation technology.
One use that companies will make of the collected geospatial data is to develop and design new maps. These are produced through sophisticated and proprietary combinations of sensing and mapping technologies. These technologies feature continuous, multimodal and extensive data collection and processing.
Such maps will be able to identify the spaces within which people live and travel. While this can help to promote technological innovation, it raises privacy questions. The researchers are calling on the developers of the ‘black boxes’ that will be integral to autonomous cars to be more open as to what happens with the data and for the navigation devices themselves to have greater transparency.
“Self-driving cars have the potential to transform our transportation network and society at large. This carries enormous consequences given that the data and technology are likely to fundamentally reshape the way our cities and communities operate.”
The new research paper proposes that governments should enact legislation that allows future autonomous cars users to unlock the ‘black box’ and understand what data is being used for and why. As León states: “oversight of the self-driving car industry cannot be left to the manufacturers themselves.” The paper also calls for developers to use open-source software, which will enable an understanding of what is happening with the data.
There is also a call for greater understanding of security risks and the extent that data can be taken from car navigation systems.
The discussion has been developed in a paper published in the journal Cartographic Perspectives. The research paper is titled “Counter-Mapping the Spaces of Autonomous Driving.”
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