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Surprise! Operations and IT aren't getting along when it comes to IoT.

451 Research announced new survey results that show operational technology (OT) and IT stakeholders are not aligned on IoT projects. Sure will be harder to drive business results if this doesn't get fixed. Here are some key findings:

Research shows that IT and OT personnel are not well aligned on IoT initiatives, and they need to cross that divide for those enterprise IoT projects to prove viable.

  • Only one-third of OT respondents (34%) said they ‘cooperate closely with IT’ on IoT projects from conception to operations.
  • A relatively small group of respondents said they were in ‘active conflict’ with IT over IoT, OT professionals are four times more likely to characterize their relationship with IT that way.  
  • More than half (55%) of the OT survey respondents currently deploy IoT within their organization, and 44% have successfully moved those projects from proof of concept to full-scale deployment.
  • New operational efficiencies and data-analytics capabilities are driving successful projects; however, many IoT projects face roadblocks in the trial stage due to the IT and OT divide and budget, staff, and ROI concerns. 

Additional details in the graphic below. Want the full findings? 451 Research will happily sell it to you.

 

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IoT Developer Trends 2017 Edition

Guest post by Ian Skerrett

For the last 3 years we have been tracking the trends of the IoT developer community through the IoT Developer Survey [2015] [2016]. Today, we released the third edition of the IoT Developer Survey 2017. As in previous years, the report provides some interesting insights into what IoT developers are thinking and using to build IoT solutions. Below are some of the key trends we identified in the results.

The survey is the results of a collaboration between the Eclipse IoT Working GroupIEEEAgile-IoT EU and the IoT Council. Each partner promoted the survey to their respective communities. A total of 713 individuals participated in the survey. The complete report is available for everyone and we also make available the detailed data [xlsodf].

As with any survey of this type, I always caution people to see these results as one data point that should be compared to other industry reports. All of these surveys have inherent biases so identifying trends that span surveys is important.

Key Trends from 2017 Survey

 1. Expanding Industry Adoption of IoT

The 2017 survey participants appear to be involved in a more diverse set of industries. IoT Platform and Home Automation industries continue to lead but industries such as Industrial Automation, Smart Cities, Energy Management experience significant growth between 2016 to 2017.

industries

2. Security is the key concern but….

Security continues to be the main concern IoT developers with 46.7% respondents indicating it was a concern. Interoperability (24.4%) and Connectivity (21.4%) are the next most popular concerns mentioned. It would appear that Interoperability is on a downward trend for 2015 (30.7%) and 2016 (29.4%) potentially indicating the work on standards and IoT middleware are lessening this concern.

concerns2017

This year we asked what security-related technologies were being used for IoT solutions. The top two security technologies selected were the existing software technologies, ie. Communication Security (TLS, DTLS) (48.3%) and Data Encryption (43.2%). Hardware oriented security solutions were less popular, ex. Trusted Platform Modules (10%) and Hardware Security Modules (10.6%). Even Over the Air Update was only being used by 18.5% of the respondents. Security may be a key concern but it certainly seems like the adoption of security technology is lagging.

security

3. Top IoT Programming Language Depends…

Java and C are the primary IoT programming languages, along with significant usage of C++, Python and JavaScript. New this year we asked in the survey, language usage by IoT categories: Constrained Devices, IoT Gateway and IoT Cloud Platform. Broken down by these categories it is apparent that language usage depends on the target destination for the developed software:

  • On constrained devices, C (56.4%) and C++ (38.3%) and the dominant languages being used. Java (21.2%) and Python (20.8%) have some usage but JavaScript (10.3%) is minimal.
  • On IoT Gateways, the language of choice is more diverse, Java (40.8%), C (30.4%), Python (29.9%) and C++ (28.1%) are all being used. JavaScript and Node.js have some use.
  • On IoT Cloud Platforms, Java (46.3%) emerges as the dominant language. JavaScript (33.6%), Node.js (26.3%) and Python (26.2%) have some usage. Not surprisingly, C (7.3%) and C++ (11.6%) usage drops off significantly.

Overall, it is clear IoT solution development requires a diverse set of language programming skills. The specific language of choice really depends on the target destination.

4. Linux is key OS; Raspbian and Ubuntu top IoT Linux distros

Linux continues to be the main operating system for IoT. This year we asked to identify OS by the categories: Constrained Device and IoT Gateway. On Constrained Devices, Linux (44.1%) is the most popular OS but the second most popular is No OS/ Bar Metal (27.6%). On IoT Gateway, Linux (66.9%) becomes even more popular and Windows (20.5%) becomes the second choice.

The survey also asked which Linux distro is being used. Raspbian (45.5%) and Ubuntu (44.%) are the two top distros for IoT.

linuxdistros

If Linux is the dominant operating system for IoT, how are the alternative IoT operating systems doing? In 2017, Windows definitely experienced a big jump from previous years. It also seems like FreeRTOS and Contiki are experiencing growth in their usage.

 5. Amazon, MS and Google Top IoT Cloud Platforms

Amazon (42.7%) continues to be the leading IoT Cloud Platform followed by MS Azure (26.7%) and Google Cloud Platform (20.4%). A significant change this year has been the drop of Private / On-premise cloud usage, from 34.9% in 2016 to 18.4% in 2017. This might be an indication that IoT Cloud Platforms are now more mature and developers are ready to embrace them.

cloud

6. Bluetooth, LPWAN protocols and 6LowPAN trending up; Thread sees little adoption

For the last 3 years we have asked what connectivity protocols developers use for IoT solutions. The main response has been TCP/IP and Wi-Fi. However, there are a number of connectivity standards and technologies that are being developed for IoT so it has been interesting to track their adoption within the IoT developer community. Based on the 2017 data, it would appear Bluetooth/Bluetooth Smart (48.2%), LPWAN technologies (ex LoRa, Sigfox, LTE-M) (22.4%) and 6LoWPAN (21.4%) are being adopted by the IoT developer community. However, it would appear Thread (6.4%) is still having limited success with developer adoption.

connectivity2017

Summary

Overall, the survey results are showing some common patterns for IoT developers. The report also looks at common IoT hardware architecture, IDE usage, perceptions of IoT Consortiums, adoption of IoT standards, open source participation in IoT and lots more. I hope the report provides useful information source to the wider IoT industry.

Next week we will be doing a webinar to go through the details of the results. Please join us on April 26 at 10:30amET/16:30pmCET.

2017 IoT Survey - webinar 2

Thank you to everyone who participated in the survey, the individual input is what makes these surveys useful. Also, thank you to our co-sponsors Eclipse IoT Working GroupIEEEAgile IoT and the IoT Council. It is great to be able to collaborate with other successful IoT communities.

We will plan to do another survey next year. Feel free to leave any comments or thoughts on how we can improve it.

This post originally appeared here.

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Guest post by Evan Birkhead.

A new IDC FutureScape offers top 10 predictions for the Worldwide IoT in 2017.  The research evaluates 10 emerging trends and ranks them in terms of their likely impact across the enterprise and the time it will take each prediction to go mainstream (meaning the middle of bellcurve of adoption). 

We took a close look and found that the list provides an excellent starting point for enterprises – particular industrials - that are steadily getting pulled toward the Industrial Internet and need to learn more.  Let’s break it down.

The diagram shows IDC’s 10 predictions. The size of the bubble provides a rough indicator of the complexity and/or cost that an enterprise will incur when acting on the prediction.  The X axis shows the time until a trend becomes mainstream; the Y axis shows the impact on the enterprise organization, with the upper tier showing company-wide impact.  So, for example, #10 IoT Analytics presents the most costly and complex technology issue for organizations and its departmental impact is limited, so its mainstream acceptance won’t occur for a couple more years.

Excerpts of IDC FutureScape: Worldwide IoT 2017 Predictions 

Prediction 1: Open Data Platforms Emerge

By 2018, IDC says the "Open Data Platform" will emerge as the next frontier in platform discussions. We are already seeing this with organizations such as the Industrial Internet Consortium and the OpenFog Consortium, who are specifying open frameworks for IoT computing and communications. While this may cause confusion for early adopters, open platforms will pave the way for mainstream acceptance.

Prediction 2:  LPWAN Conflict

Despite hype on the benefits of Low-Power Wide Area Networks (LoRa, Sigfox, etc.), IDC predicts organizations won’t begin to adopt it for another year due to a lack of QoS – and then only for non-critical applications.  Keep an eye on this space though, as low-power WiFi for IoT sensor-based networks will make sense across many industries.

Prediction 3: Cycle Time Improvements

This one is farthest off in the future but could be the most important because it unlocks one of the key values of the Industrial Internet – more efficient production of products and services. According to IDC, by next year investments in operational sensing through IoT and situational awareness via analytics will deliver 30% in critical process cycle times.

Prediction 4: Blockchain Realized

By unifying data logs for a variety of industries, blockchained services, which typically leverage the cloud, promise to increase productivity and reduce downtime.  For example, manufacturers will be able to share production logs with OEMs and regulators, reducing the time to find information, resolve disputes, verify transactions and expedite deliveries.

Prediction 5: Security Evolves

As we at Bayshore know, industrial enterprises are now addressing the cultural divide between IT and OT. This will lead to a necessary investment in capabilities to protect their production processes and data from cyber attack and privacy breaches. IDC says that in two years more than 75% of device manufacturers will have improved their security and privacy capabilities.

Excerpts of IDC FutureScape: Worldwide IoT 2017 Predictions 

Prediction 6: Industry Growth

IDC puts the initial worldwide IoT industry growth at the end of 2017.  Will that be the beginning of the “hockey stick?”  The initial markets driving the growth will be connected vehicles, insurance telematics, personal wellness, and smart buildings, accounting for $96 billion in spending.

Prediction 7: IoT/IT Services

As adoption of IoT grows, IDC predicts that 75% of IoT adopters will turn to outside firms for help in strategy, planning, development, implementation, and/or management of these initiatives.  Again, this is a trend we can verify from our experience at Bayshore.  We are seeing an increased customer reliance on carriers, cloud providers, systems integrators, machine vendors, and an emerging class of Industrial IoT architectural experts.

Prediction 8: The Edge

While we are still looking for a universally accepted definition of edge computing, there is consensus on its importance in the success of IoT.  IDC says that in two years at least 40% of IoT-created data will be stored, processed, analyzed and acted upon close to, or at, the edge of the network.

Prediction 9: Smart City Assets

At Bayshore, we are seeing the same thing. Metropolitan areas, paced by progressive CIOs in places as diverse as Barcelona, Chicago, and San Diego, are already reaping the benefits of sensor consolidation and analytics.  Look for more and more success stories in areas such as building automation, utilities, traffic management, and data center management. According to IDC, 40% of local and regional governments “will use IoT to turn infrastructure into assets Instead of liabilities” by 2019.

Prediction 10: Analytics and IoT Collide

We agree that this is the mother of all trends. While analytics is the most complex technical and cultural issue, it is clearly the #1 reason to move to the Industrial Internet.  IDC predicts that by 2019, all effective IoT efforts will merge streaming analytics with machine learning trained on data lakes, data marts, and content stores, accelerated by discrete or integrated processors.

Excerpts of IDC FutureScape: Worldwide IoT 2017 Predictions

The Bayshore IT/OT Gateway is used by industrial enterprises to provide IT with visibility into big OT data and to provide OT with access to applications such as advanced IT analytics. Transformation of OT data (Modbus TCP, DNP3, Ethernet/IP, and so on), into formats that can be interpreted by IT analytics programs (JSON, https, http, etc.) will be crucial to this adoption.

This post originally appeared here

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Editors Note: Members of IoT Central are encouraged to participate in Ventana Research's study. The author of the blog shares details below.

The emerging Internet of Things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any device can generate and transmit data about its operations – data to which analytics can be applied to facilitate monitoring and a range of automatic functions. To do these tasks IoT requires what Ventana Research calls operational intelligence (OI), a discipline that has evolved from the capture and analysis of instrumentation, networking and machine-to-machine interactions of many types. We define operational intelligence as a set of event-centered information and analytic processes operating across an organization that enable people to use that event information to take effective actions and make optimal decisions. Ventana Research first began covering operational intelligence over a decade ago.

In many industries, organizations can gain competitive advantage if they reduce the elapsed time between an event occurring and actions taken or decisions made in response to it. Existing business intelligence (BI) tools provide useful analysis of and reporting on data drawn from previously recorded transactions, but to improve competitiveness and maximize efficiencies organizations are concluding that employees and processes in IT, business operations and front-line customer sales, service and support also need to be able to detect and respond to events as they happen.

Both business objectives and regulations are driving demand for new operational intelligence technology and practices. By using them many activities can be managed better, among them manufacturing, customer engagement processes, algorithmic trading, dynamic pricing, yield management, risk management, security, fraud detection, surveillance, supply chain and call center optimization, online commerce and gaming. Success in efforts to combat money laundering, terrorism or other criminal behavior also depends on reducing information latency through the application of new techniques.

The evolution of operational intelligence, especially in conjunction with IoT, is encouraging companies to revisit their priorities and spending for information technology and application management. However, sorting out the range of options poses a challenge for both business and IT leaders. Some see potential value in expanding their network infrastructure to support OI. Others are implementing event processing (EP) systems that employ new technology to detect meaningful patterns, anomalies and relationships among events. Increasingly, organizations are using dashboards, visualization and modeling to notify nontechnical people of events and enable them to understand their significance and take appropriate and immediate action.

As with any innovation, using OI for IoT may require substantial changes to organizations. These are among the challenges they face as they consider adopting this evolving operational intelligence:

  • They find it difficult to evaluate the business value of enabling real-time sensing of data and event streams using radio frequency identification (RFID) tags, agents and other systems embedded not only in physical locations like warehouses but also in business processes, networks, mobile devices, data appliances and other technologies.
  • They lack an IT architecture that can support and integrate these systems as the volume, variety and frequency of information increase. In addition, our previous operational intelligence research shows that these data sources are incomplete or inadequate in nearly two out of five organizations.
  • They are uncertain how to set reasonable business and IT expectations, priorities and implementation plans for important technologies that may conflict or overlap. These can include BI, event processing, business process management, rules management, network upgrades, and new or modified applications and databases.
  • They don’t understand how to create a personalized user experience that enables nontechnical employees in different roles to monitor data or event streams, identify significant changes, quickly understand the correlation between events and develop a context adequate to enable determining the right decisions or actions to take.

Today’s fast-paced, 24-by-7 world has forced organizations to reduce the latency between when transactions and other data are recorded and when applications and BI systems are made aware of them and thus can take action. Furthermore, the introduction of low-cost sensors and the instrumentation of devices ranging from appliances and airline engines to crop management and animal feeding systems creates opportunities that have never before existed. Technological developments such as smart utility meters, RFID and embedded computing devices for environmental monitoring, surveillance and other tasks also are creating demand for tools that can provide insights in real time from continuous streams of event data.

As organizations expand business intelligence to serve operational needs by deploying dashboards and other portals, they are recognizing the need to implement technology and develop practices that collect events, correlate them into meaningful patterns and use workflow, rules and analytics to guide how employees and automated processes should react. In financial services, online commerce and other industries, for example, some organizations have built proprietary systems or have gone offshore to employ large teams of technicians at outsourcing providers to monitor transactions and event streams for specific patterns and anomalies. To reduce the cost, complexity and imperfections in these procedures, organizations now are seeking technology that can standardize and automate event processing and notify appropriate personnel of significant events in real time.

Conventional database systems are geared to manage discrete sets of data for standard BI queries, but event streams from sources such as sensing devices typically are continuous, and their analysis requires tools designed to enable users to understand causality, patterns, time relationships and other factors. These requirements have led to innovation in event stream processing, event modeling, visualization and analytics. More recently the advent of open source and Hadoop-related big data technologies such as Flume, Kafka, Spark and Storm are enabling a new foundation for operational intelligence. Innovation in the past few years has occurred in both the open source community and proprietary implementations.

Many of the early adopters of operational intelligence technologies were in financial services and intelligence, online services and security. However, as organizations across a range of other industries seek new competitive advantages from information or require real-time insight for risk management and regulatory compliance, demand is increasing broadly for OI technologies. Organizations are considering how to incorporate event-driven architectures, monitor network activity for significant event patterns and bring event notification and insight to users through both existing and new dashboards and portals.

To help understand how organizations are tackling these changes Ventana Research is conducting benchmark research on The Internet of Things and Operational Intelligence. The research will explore how organizations are aligning themselves to take advantage of trends in operational intelligence and IoT. Such alignment involves not just information and technology, but people andprocesses as well. For instance, IoT can have a major impact on business processes, but only if organizations can realign IT systems to a discover-and-adapt rather than a model-and-apply paradigm. For instance, business processes are often outlined in PDF documents or through business process systems. However, these processes are often carried out in an uneven fashion different from the way the model was conceived. As more process flows are directly instrumented and some processes carried out by machines, the ability to model directly based on the discovery of those event flows and to adapt to them (either through human learning or machine learning) becomes key to successful organizational processes.

By determining how organizations are addressing the challenges of implementing these technologies and aligning them with business priorities, this research will explore a number of key issues, the following among them:

  • What is the nature of the evolving market opportunity? What industries and LOBs are most likely to adopt OI for IoT?
  • What is the current thinking of business and IT management about the potential of improving processes, practices and people resources through implementation of these technologies?
  • How far along are organizations in articulating operational intelligence and IoT objectives and implementing technologies, including event processing?
  • Compared to IT management, what influence do various business functions, including finance and operations management, have on the process of acquiring and deploying these event-centered technologies?
  • What suppliers are organizations evaluating to support operational intelligence and IoT, including for complex event processing, event modeling, visualization, activity monitoring, and workflow, process and rules management?
  • Who are the key decision-makers and influencers within organizations?

Please join us in this research. Fill out the survey to share your organization’s existing and planned investments in the Internet of Things and operational intelligence. Watch this space for a report of the findings when the research is completed.

Regards,

David Menninger

SVP & Research Director

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Guest blog by Ian Skerrett. It originally appeared here.

Today we release the results of our second annual IoT Developer Survey. Like last year it provides an interesting insight into how developers are building IoT solutions.

This year the Eclipse IoT Working Group partnered with IEEE IoT and the AGILE-IoT research project to expand the scope and respondent pool for the survey. Thanks to this partnership, we had 528 participants in the survey, up from 392 last year. The partnership also allowed us to analyze the data to look for any significant difference between the different IoT communities.

As with any surveys of this nature, I encourage readers to see these results as one data point that should be compared with other data and industry trends. These results will have certain biases but I do believe these results identify some interesting trends in the IoT industry.

Key Trends for IoT developers

  1.  Companies are shipping IoT solutions today. 46% of the respondents claim their company develops and deploys an IoT solution today. Another 29% plan to do so in the next 6 months. This is a clear indication the industry is maturing quickly.

iotplans

  1. Security continues to be a key concern. It’s not a big surprise that security continues to be the top concern in IoT. Interoperability is the second key concern. I do believe we are on the way to solving some of the interoperability issues with projects like Eclipse HonoEclipse Smarthome and Eclipse Kura. I also think some of the work the AGILE-IoT project is doing will address these issues. However, it still seems the IoT industry still needs to focus on security. It is a difficult issue that needs to be solved.For companies that have deployed a solution today, performance is rising to the third key concern. It is not clear what the performance issues are, but it is something that warrants more investigation.

concerns

  1. Top IoT programming languages: Java, C, JavaScript, Python.  Not surprising to see these languages as being the most popular for developers. I do find some people question the use of Java in IoT. The Eclipse IoT community has a number of Java projects, so there is some bias in the results toward Java. However, even when removing the respondents from the Eclipse IoT community, the top 3 languages are C, Python and Java.

languages

  1. MQTT and HTTP are the dominant message protocols.Without a doubt MQTT has become a pervasive and widely used protocol for IoT. HTTP being the other protocol.
    The other messaging protocol supported in the Eclipse IoT community is CoAP. It did not receive as much support, but it does appear to have support in certain industries. For instance, the use of CoAP increases if the respondent is in the IoT Platforms or Smart Cities industry. The fact IoT Platforms are supporting CoAP is expected and a good thing. It does seem Smart Cities industry is using CoAP but I am not sure where or how. If anyone has details, please leave a comment.As an aside, the success of MQTT is a testament to IBM’s strategy to standardize MQTT at OASIS and start the Eclipse Paho project. It really is a perfect case study for using open source and open standards to gain broad industry adoption. For example, 1) MQTT is now supported by IBM Bluemix, Amazon AWS IoT, MS Azure IoT, plus every other  IoT middleware platform in the market, 2) the new Arduino board is also using MQTT to communicate with their cloud, and 3) Eclipse Paho and Eclipse Mosquitto are some of the most popular and active projects at Eclipse. MQTT is everywhere. Well done IBM.

protocols

  1. Linux is the dominant IoT operating system. Over 70% of the respondents claimed they use Linux for their IoT operating system. The next more popular section at 23% was No OS/Bare metal. In the last number of years, a number of new IoT operating systems have been introduced (ex. ARM mbed, Contiki, RIOT, Zephyr) but the adoption still hasn’t materialized. It seems many companies are using Yocto to create their own Linux distro for their IoT solution. It will be interesting to watch how these other operating systems grow in comparison to Linux.

os

  1. Amazon leads in IoT cloud services. Not terribly surprising Amazon came out on top as the top cloud service provider. However, Private/On premise was a close second so I think this is an indication that IoT cloud services is still in its infancy. What did surprise me was that Microsoft Azure was number 3 in the survey and does even better when a company has a deployed solution. This seems to reflect MS Azure’s heavy emphasis on IoT use cases.

cloud

  1. Open source is pervasive in IoT. I strongly believe open source is critical to the success of the IoT industry. Therefore, I was encouraged to see 58% of the respondents are actively engaged with open source. I think it is a great statement on the work we have been doing at Eclipse IoT to create an open source community for the IoT industry.

 

Trends between 2015 and 2016

This is the second year we have done this type of survey so I was curious what has changed between 2015 and 2016. Interestingly enough, not a lot has changed. Many of the trends and highlights mentioned above are consistent with the 2015 results. This consistency would appear to confirm that the results are a good reflection of how developers are building IoT solutions.

Thank you to everyone who participated in the survey. We definitely appreciate your input. The complete results are available on slideshareand the raw data in xls and ods format. Feel free to leave a comment or contact me if you have any questions.

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IoT practitioners are at the forefront of their company's digital initiatives. But is the rest of your company ready for its digital moment? The expectations are high in the C-Suite for digital transformations, but there's still more talk than action for many companies.

New research by McKinsey Institute suggests only 17% of corporate boards are participating in strategy for big data or digital initiatives. The good news is almost half of big companies have managed to get their CEOs personally involved, up from 23 percent in 2012.

Other findings from the survey include:

  • The most common hurdle to meeting digital priorities, executives say, is insufficient talent or leadership.

  • Across the C-Suite, 71% expect that over the next three years, digital trends and initiatives will result in greater top-line revenues for their business, and large shares expect their profitability will grow.

  • More than half of executives say that, in response to digital, their companies have adapted products, services, and touchpoints to better address customer needs.

  • Executives most often cite analytics and data science as the area where their organizations have the most pressing needs for digital talent, followed by mobile development and user experience.

  • Executives who report ample organizational support for adopting risky digital initiatives are twice as likely to work for a high-performing company as executives reporting resistance to risky initiatives due to fear of failure.

  • Forty-seven percent say cutting-edge digital work helps them attract and retain digital talent.

  • Companies’ priorities vary across industries, reflecting key sources of value in each sector: big data is a top priority in healthcare, for example, while automation is a greater focus in manufacturing (see graphic below).

 

The digital interconnection of billions of devices is today’s most dynamic business opportunity and at present, the Internet of Things remains a wide-open playing field for enterprises and digital strategy. According to the study, buy-in from the C-Suite and aligning with corporate culture and objectives is key to digital success.

You can read the complete survey here.

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