Sengled is partnering with leading AI company, Baidu, to introduce the Sengled Smart Lamp Speaker, a new voice-enabled lighting concept. Both companies will showcase Sengled Smart Lamp Speaker at the annual CES in Las Vegas, NV, January 9-12, 2018, with the official reveal commencing at the Baidu World @ Las Vegas on January 8, 2018. The […]
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CesKicking the new year off with a bang, the Taiwan External Trade Development Council (TAITRA), Taiwan’s foremost trade promotion organization, will provide a first look at brand new “smart” innovations from ITRI, AEON Motor, GEOSAT, Robotelf, and Taiwan Main Orthopedics at a January 8 press conference at CES 2018. The companies will showcase products poised […]
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It happens at the worst of times – late for a meeting, on the way to the rugby and even when you’re desperate for the bathroom. When your car breaks down, you can moan in retrospect, acknowledging the signs that it needed urgent maintenance. Thanks to technology, more specifically the evolution and application of cognitive learning, these frustrating occurrences will become a thing of the past.
Connecting the things
Analyst house Gartner forecasts that there will be 20.8 billion connected ‘things’ worldwide by 2020. Enterprises that stick to an old ‘preventive’ data methodology, says Mark Armstrong, managing director and vice-president International Operations, EMEA & APJ at Progress, are going to be left behind, as this approach accounts for a mere 20% of failures.
Predictive maintenance brings a proactive and resource saving opportunity. Predictive software can alert the manufacturer or user when equipment failure is imminent, but also carry out the maintenance process automatically ahead of time. This is calculated based on real time data, via metrics including pressure, noise, temperature, lubrication and corrosion to name a few.
Considering degradation patterns to illustrate the wear and tear of the vehicle in question, the production process is not subject to as high levels of interruption without the technology. By monitoring systems ‘as live’, breakdowns can be avoided prior to them happening.
It’s no longer a technological fantasy. Due to data in cars being collected for decades, researchers and manufacturers can gather insights that could be used to prepare predictive analytics. This will assist in predicting which individual cars will break down and need maintenance.
Now that the Internet of Things (IoT) is a reality, car manufacturers can use this information to offer timely and relevant additional customer services based on sophisticated software that can truly interrogate, interpret and use data. So who is going to be responsible for taking advantage of this technology?
Bolts and screws
Key management figures in the transport industry must commit to a maintenance management approach to implement a long-term technological solution. As described by R.Mobley, run-to-failure management sees an organisation refrain from spending money in advance, only reacting to machine or system failure. This reactive method may result in high overtime labour costs, high machine downtime and low productivity.
Similarly reactive, preventive maintenance monitors the mean-time-to-failure (MTTF), based on the principle that new equipment will be at its most vulnerable during the first few weeks of operation, as well as the longer it is used for. This can manifest itself in various guises, such as engine lubrication or major structural adjustments. However, predicting the time frame in which a machine will need to be reconditioned may be unnecessary and costly.
As an alternative option, predictive maintenance allows proactivity, ensuring lengthier time between scheduled repairs, whilst reducing the significant amount of crises that will have to be addressed due to mechanical faults. With a cognitive predictive model, meaning applications are able to teach themselves as they function, organisations will be able to foresee exactly why and when a machine will break down, allowing them to act […]
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By A.R. Guess
by Angela Guess According to a recent press release, “A new LogicMonitor® survey of nearly 300 industry influencers predicts that enterprises will migrate the majority of their IT workloads from the data center to the cloud by 2020. Fueling this transition will be the 20.8 billion IoT devices Gartner predicts will come online, and the […]
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Apple’s iPhone X has given us a glimpse into the future of personal data security. By 2020 we’ll see billions of smart devices being used as mobile face authentication systems, albeit with varying degrees of security. The stuff of science fiction for years, face recognition will surpass other legacy biometric login solutions,such as fingerprint and iris scans, because of a new generation of AI-driven algorithms, says Kevin Alan Tussy, CEO of FaceTec.
The face recognition space had never received more attention than after the launch of Face ID, but with the internet now home to dozens of spoof videos fooling Face ID with twins, relatives and even olives for eyes, the expensive hardware solution has left many questioning if this is just another missed opportunity to replace passwords.
Face Recognition is a biometric method of identifying an authorised user by comparing the user’s face to the biometric data stored in the original enrolment. Once a positive match is made and the user’s liveness is confirmed the system grants account access.
A step up in security, Face Authentication (Identification + Liveness Detection), offers important and distinct security benefits: no PIN or password memorisation is required, there is no shared secret that can be stolen from a server, and the certainty the correct user is logging in is very high.
Apple’s embrace of Face ID has elevated face recognition into the public consciousness, and when compared to mobile fingerprint recognition, face recognition is far superior in terms of accuracy. According to Apple, their new face scanning technology is 20-times more secure than the fingerprint recognition currently used in the iPhone 8 (Touch ID) and Samsung S8. Using your face to unlock your phone is, of course, a great step forward, but is that all a face biometric can do? Not by a long shot.
While the goal of every new biometric has been to replace passwords, none have succeeded because most rely on special hardware that lacks liveness detection. Liveness detection, the key attribute of Authentication, verifies the correct user is actually present and alive at the time of login.
True 3D face authentication requires: identity verification plus depth sensing plus liveness detection. This means photos or videos cannot spoof the system, nor animated images like those created by CrazyTalk; and even 3D representations of a user like projections on foam heads, custom masks, and wax figures are rebuffed.
With the average price of a smartphone hovering around £150 (€170.58), expensive hardware-based solutions, no matter how good they get, won’t ever see widespread adoption. For a face authentication solution to be universally adopted it must be a 100% software solution that runs on the billions of devices with standard cameras that are already in use, and it must be be more secure than current legacy options (like fingerprint and 2D face).
A software solution like ZoOm from FaceTec can be quickly and easily integrated into nearly any app on just about any existing smart device. ZoOm can be deployed to millions of mobile users literally overnight, and provides […]
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