The Internet of Things (IoT) is bringing about a new era of connectivity in the digital age, say analysts Frost & Sullivan. It is connecting critical business sectors through a network of secure data flow, analytics, and management. It is also bringing numerous opportunities for sensor participants through security technologies required for remote services and enhanced accessibility of devices.
The total sensors market in security and surveillance applications was worth $6,267.9 million (€5112.16 million) in 2016, with image sensors holding the largest market share at 23%. The market is expected to reach $12,012.1 million (€9797.19 million) by 2023.
North America and EMEA dominate the market, driven by aging infrastructures, but APAC is the fastest growing due to rapid infrastructure development, strong economic growth, and favourable government regulations. However, challenges for sensor manufacturers and suppliers include increased competition, leading to pricing pressures, lack of product differentiation, and lack of common global standards.
The growth of IoT is contributing to rapidly evolving security requirements, with the areas of robotics and biometric and RFID sensors offering the greatest opportunities. Robotics is expected to be the future of security and surveillance, with considerable investments in research and development in this space. In addition, the demand for drones and AGVs remains strong, especially in defense, commercial, and institutional spaces.
Frost & Sullivan’s recent analysis report, Sensors in Security & Surveillance, Global Forecast to 2023, covers global trends for sensors used in security and surveillance applications across industries such as industrial, commercial, institutional, building automation, infrastructure, and security and defence. The analysis also explores the impact of the Internet of Things (IoT) and Industrial Internet of Things (IIoT) on security and surveillance.
“In commercial and residential applications, biometric recognition used in access control systems is also witnessing a gradual increase in interest,” said Ram Ravi. “In addition, cloud networking, a revolutionary two-way interactive service delivery platform, is expected to create a technological explosion in the homes and buildings services market, particularly in commercial and residential security applications. This will enable homes and buildings participants to adopt new business models to provide attractive cloud-based services through a secured network.”
Three big predictions for sensors in the global security and surveillance market:
Internet of Things (IoT) is paving the way for industry convergence and enabling machine-to-machine (M2M) communications for better business decisions. Sensors form the physical layer of the IoT architecture;
Development of new communication protocols will ensure interoperability and provide standardisation, particularly in applications for perimeter security, intrusion detection, and access control systems; and
Retail, healthcare, and finance are all expected to offer considerable growth opportunities for sensors in biometrics.
Sensors in Security & Surveillance, Global Forecast to 2023, is a part of Frost & Sullivan’s Measurement & Instrumentation Growth Partnership Service programme.
For more information on this analysis, please click here.
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LOS ANGELES – 18 January 2018 – The Internet Corporation for Assigned Name and Numbers (ICANN) published the results of an annual survey that measures the perception of satisfaction among Internet Assigned Numbers Authority (IANA) functions customers regarding the services they receive. This survey is the first completed since the ICANN organization affiliate Public Technical Identifiers (PTI) started performing IANA functions on behalf of the ICANN org and accounts for transactions completed between September 2016 and August 2017.
The IANA Services Customer Survey measured satisfaction in relation to documentation quality, process quality, transparency, timeliness, accuracy, reporting, and courtesy. In the 2017 survey, customers identified accuracy as the most important measure of performance for the fifth consecutive year. Notably, 94 percent of respondents reported being satisfied with the accuracy of their transactions. Timeliness and process quality, were identified as the second and third most important measures by customers, both stayed consistent with the previous year with 89 percent satisfaction.
View the IANA Services Customer Satisfaction Survey Report [PDF, 1.33 MB].
While the results of the survey are generally positive, the ICANN org continues to explore opportunities for improvement, including on the survey format and methodology. In response to conversations with key stakeholders within the community, an option to select “not applicable” was added to each question in the survey and open-ended questions were introduced to better capture feedback. There were also improvements to capture the geographical location of the IANA functions customers, and to further segment the top-level domain (TLD) operators.
“Over the years we have refined our approach to surveying our customers, and we’ve received increasing feedback that it can be difficult to recall the details of their PTI interactions up to a year later. This feedback has prompted us to start planning to survey our customers shortly after our interactions, to obtain more timely and actionable feedback,” said Kim Davies, Vice President of IANA and President, PTI.
The ICANN org commissioned Ebiquity, a leading independent marketing and media consultancy, to administer the survey, analyze the results and compile an independent third-party report, to keep with PTI’s goal to improve transparency in its processes. This year, Ebiquity issued 4,070 invitations during the survey period to IANA functions customers — top-level domain operators, regional Internet registries, RFC authors and other protocol parameter registrants, Internet Engineering Steering Group members, DNSSEC KSK trusted community representatives, and .INT domain registrants — and 7 percent responded.
ICANN’s mission is to help ensure a stable, secure, and unified global Internet. To reach another person on the Internet, you need to type an address – a name or a number – into your computer or other device. That address must be unique so computers know where to find each other. ICANN helps coordinate and support these unique identifiers across the world. ICANN was formed in 1998 as a not-for-profit public-benefit corporation with a community of participants from all over the world.
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Nitesh Arora, the head of marketing at Cloudleaf, reveals the benefits of the divide and conquer approach to digitally transforming complex enterprise operations
Global adoption of industrial IoT hardware, connectivity and services is soaring. In fact, over the next few years, investment in IoT technologies will experience a whopping 15.6% CAGR worldwide, reaching projected spending of US$1.29tn by 2020. Nowhere is this more true than in the manufacturing sector, where the IoT is helping enterprises to digitally transform their legacy plant operations. The potential benefits are compelling, including near-zero downtime operations, sixsigma certified product quality, and streamlined asset maintenance. To put things in perspective, manufacturing related IoT spending alone, accounted for US$178bn in 2016 – more than spending in transportation and utilities, combined.
It’s understandable, therefore, that the manufacturing sector is keen to embrace IoT in order to take advantage of obvious benefits. These include addressing the challenges of total cost of ownership (TCO), competition, complexity and risk, but increasingly, early-movers are also using it as a vehicle for generating growth and as a hedge against increasing global competitive pressures. According to Vernon Turner, an IoT research fellow and senior vice president at IDC: “investments by China and the United States in IoT solutions is driving these two countries to account for double-digit annual growth rates and over half of the IoT spending.”
On paper, this all seems perfectly reasonable and straightforward, but in practice, manufacturers are finding that adoption is a relative and loaded concept. Implementing IoT across the enterprise ecosystem in one fell swoop is a tricky business and better left to larger, well diversified outfits able to absorb front-loaded costs and risks. Instead the trend is in smaller compartmentalised industrial IoT (IIoT) implementations that solve a narrow set of business challenges, rather than trying to boil all oceans at once. By adopting a disciplined implement, measure, optimise and replicate approach, manufacturers are able to take short manageable sprints towards solving industrial process automation challenges in a scalable and purposeful way.
The promise of IoT to provide powerful cross-boundary visibility, real-time monitoring and granular control across the entire manufacturing value-chain of people, assets and workflows, is generally well understood. But the real challenges are the next step: How do manufacturers choose an IoT provider? How do they execute? And how do they measure success, scale growth and replicate their gains? Cloudleaf was founded to specifically answer these questions and provide solutions that elegantly solve real-world business problems in manufacturing and distribution, pharma and life sciences, and other process automation industries. Our solutions are designed to simplify the manufacturing processes and solve emerging asset and workflow challenges in a measurable, value-added and sustainable way.
Increasingly, we are finding that manufacturers are investing in IoT technologies that bolster their manufacturing operations management (MOM), enterprise asset management (EAM) and predictive maintenance (PdM) capabilities. In fact the push right now is to get a better understanding of all the assets, processes and skilled labour in play on the plant-floor and at the operational level of the enterprise. […]
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The Automotive & Industrial Systems Company of Panasonic Corporation is challenging to develop new businesses and services in the IoT field, in cooperation with Silicon Valley startups. Panasonic is advancing the development of new IoT services and solutions by combining leading UI/UX(*1) technology with its strong HMI (human machine interface) design technology, which has been […]
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By Alex Woodie
We’ve grown accustomed to interacting with computers through a visual interface. But thanks to big gains in the accuracy of speech recognition, that’s changing, and among the applications being targeted for voice-enablement are business intelligence and analytics.
It wasn’t long ago that trying to interact with a computer through voice commands was an exercise in frustration. The computer could correctly pick out a few words here and there, but the number of mistakes made the whole process unfeasible. The reason was simple: The algorithms simply were not good enough to be able to accurately determine what a person is saying, at least without extensive training to learn the nuances of a single person’s voice.
But speech recognition has improved vastly over the past few years. Thanks to powerful neural network algorithms and a huge corpus of voice data to train on, the Web giants have made big strides in creating computers that one can talk to without feeling like you want to throw it out the window.
We’ve seen the biggest impact of this new AI-powered service at home. Anybody who has used Amazon Alexa, Apple Siri, Microsoft Cortana, or Google Home device can tell you that the systems are accurate enough to be worth using for a set of tasks, like playing a song, checking the weather, or ordering pizza. Consumers, being the fickle creatures they are, would simply move on to something else if the home assistants were too frustrating, inaccurate, or cumbersome to use.
That’s not to say that the devices are perfect. A year ago, Google CEO Sundar Pichai announced that Google has improved its speech recognition technology accuracy to about a 5% error rate, which means one out of every 20 words is missed. While there’s room for improvement, that’s a big step up from 2015, when the error rate was 8%, and a giant leap from 2013, when it was an unusable 23%. (For the record, Microsoft has announced similar improvements in its speech recognition tech.)
Amazon’s Echo leads the AI-powered home assistant race at the moment (Roman Tiraspolsky/Shutterstock)
As a result of this new capability, the Web giants have turned to voice as an input for many of their consumer products. “Our word error rate continues to improve even in very noisy environments,” Pichai said at the 2017 Google I/O event. “This is why if you speak to Google on your phone or Google Home, we can pick up your voice accurately.”
When you pair speech recognition’s newfound capabilities with another computing trend — the rise of the Internet of Things (IoT) and the proliferation of network-connected smart devices – you quickly realize that we’re on the cusp of a whole new world of voice-driven control.
That jibes with Amazon’s vision, which is to give customers access to Alexa “whenever and wherever they want,” Steve Rabuchin, VP of Amazon Alexa, recently told Adweek. “That means customers may be able to talk to their cars, refrigerators, thermostats, lamps, and all kinds of devices in and outside their homes.”
Today, this trend manifests with the specter of voice search, which sees people speaking into an Amazon Echo or a smartphone app and expecting to hear a verbalized response (the text-to-speech part of the equation is a much easier problem to solve). In fact, voice search is getting so big that media analytics company comScore predicts that it will account for 50 percent of all searches by 2020. The popularity of voice-enabled trend shows up in the numbers. According to eMarketer, there are 45 million voice-assisted devices in the United States, a number that’s projected to increase to 67 million by next year.
But the AI-powered technology is projected to quickly move beyond voice search and into a whole new realm of personalized, voice-enabled services. Nobody knows what the Web giants are working on behind closed doors, but it’s likely going to demand a lot of attention when it’s ready.
That’s not stopping businesses from utilizing the tech that’s already available to help things run smoother in the office. Zach Holmquist, Chief of Workplace Experience for Teem, says the automated office is closer at hand than many realize.
Thanks to improvements in speech recognition, users can now interact with enterprise systems via voice (chombosan/Shutterstock)
“Virtual home assistants like Alexa and beacons have entered the workplace, resulting in more personalized interactions, voice- and sensor-activated meeting scheduling, and sensors automatically adjusting temperature, meeting check-ins or anticipating lunch requests,” he says.
The improved speech recognition is also showing up in new analytics and business intelligence solutions that allow workers to query databases using nothing but their voices. One company on the cutting edge of this trend is iOLAP, a San Francisco-based analytics company that’s working with Amazon and other Web giants to turn their speech recognition tech into the new user interface for enterprise systems.
“Think of it as voice-enabling your corporate dashboard,” says Chris Jordan, the CEO and managing director of iOLAP. “Think of it as an executive walk into his office and wants his daily briefing, and it’s a rundown of main KPIs that he’s interested in.”
While algorithms from Amazon and Microsoft handle the speech recognition bit, iOLAP is building all the other stuff that’s needed to make the whole system work, including turning text payloads into SQL and submitting them to a database, working with APIs, and handling the necessary user access and security controls required in the corporate environment.
iOLAP’s enterprise voice technology can work with analytics and transactional applications. In the analytics space, it’s more about setting up pre-built access paths to data. “It can be anything, as long as we know somewhat ahead of time,” Jordan says. “It’s definitely not data exploration. The queries are pre-defined with variables, and the variable can be data elements.”
For example, if the CEO of a retailer wants to be able to query sales results across 1,000 stores over time, those columns in the database will need to be set up ahead of time. “But I don’t have to know what all the possible dates or what the possible stores are,” Jordan says. “We’re querying the database to get those responses.”
Owing to the nature of a voice-enabled interaction, one must be careful not to tread too deeply into the data waters. There’s only a certain amount of data that can be transmitted verbally, so customers are wise to pick and choose their use cases carefully.
“You don’t want to sit and listen to Alexa read a Tableau report for you,” Jordan says. “You probably want to ask a more specific question that come up with a more finite answer.”
iOLAP’s voice analytics solution has seen action at several real-world customers, including at Dallas Fort Worth International Airport, where the solution is used to give air traffic controllers a way to verbally query and track the overall flow of airplanes; at the Dickey’s Barbeque Pit chain, where it’s used to help employees more efficiently track the temperatures of meat; and at Pioneer Natural Resources, where it’s used to voice-enable an enterprise dashboard.
The timing is right for voice-enabled analytics apps to enter our lives, Jordan says. “People are getting more and more used to interacting with their system via voice, in their consumer life, and we believe that will be drawn into the enterprise as well,” he says.
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