Tag Archives: Future

How App Developers Can Leverage the iPhone 12 to Maximize Their Apps

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On October 23rd, four brand new iPhone 12 models were released to retailers. As the manufacturer of the most popular smartphone model in the world, whenever Apple delivers a new device its front-page news. Mobile app developers looking to capitalize on new devices must stay abreast of the latest technologies, how they empower applications, and what they signal about where the future of app development is headed.

With that in mind, here is everything app developers need to know about the latest iPhone models.

BIG DEVELOPMENTS FOR AUGMENTED REALITY

LiDAR is a method for measuring distances (ranging) by illuminating the target with laser light and measuring the reflection with a sensor
LiDAR is a method for measuring distances (ranging) by illuminating the target with laser light and measuring the reflection with a sensor

On a camera level, the iPhone 12 includes significant advancements. It is the first phone to record and edit Dolby Vision with HDR. What’s more, Apple has enhanced the iPhone’s LiDAR sensor capabilities with a third telephoto lens.

The opportunities for app developers are significant. For AR developers, this is a breakthrough—enhanced LiDAR on the iPhone 12 means a broad market will have access to enhanced depth perception, enabling smoother AR object placement. The LIDAR sensor produces a 6x increase in autofocus speed in low light settings.

The potential use cases are vast. An enterprise-level application could leverage the enhanced camera to show the inner workings of a complex machine and provide solutions. Dimly lit rooms can now house AR objects, such as Christmas decorations. The iPhone 12 provides a platform for AR developers to count on a growing market of app users to do much more with less light, and scan rooms with more detail.

The iPhone 12’s enhanced LiDAR Scanner will enable iOS app developers to employ Apple’s ARKit 4 to attain enhanced depth information through a brand-new Depth API. ARKit 4 also introduces location anchors, which enable developers to place AR experiences at a specific point in the world in their iPhone and iPad apps.

With iPhone 12, Apple sends a clear message to app developers: AR is on the rise.

ALL IPHONE 12 MODELS SUPPORT 5G

5G 2

The entire iPhone 12 family of devices supports 5G with both sub-6GHz and mmWave networks. When iPhone 12 devices leverage 5G with the Apple A14 bionic chip, it enables them to integrate with IoT devices, and perform on ML algorithms at a much higher level.

5G poses an endless array of possibilities for app developers—from enhanced UX, more accurate GPS, improved video apps, and more. 5G will reduce dependency on hardware as app data is stored in the cloud with faster transfer speeds. In addition, it will enable even more potential innovation for AR applications.

5G represents a new frontier for app developers, IoT, and much more. Major carriers have been rolling out 5G networks over the past few years, but access points remain primarily in major cities. Regardless, 5G will gradually become the norm over the course of the next few years and this will expand the playing field for app developers.

WHAT DOES IT MEAN?

Beyond the bells and whistles, the iPhone 12 sends a very clear message about what app developers can anticipate will have the biggest impact on the future of app development: AR and 5G. Applications employing these technologies will have massive potential to evolve as the iPhone 12 and its successors become the norm and older devices are phased out.

How Artificial Intuition Will Pave the Way for the Future of AI

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Artificial intelligence is one of the most powerful technologies in history, and a sector defined by rapid growth. While numerous major advances in AI have occurred over the past decade, in order for AI to be truly intelligent, it must learn to think on its own when faced with unfamiliar situations to predict both positive and negative potential outcomes.

One of the major gifts of human consciousness is intuition. Intuition differs from other cognitive processes because it has more to do with a gut feeling than intellectually driven decision-making. AI researchers around the globe have long thought that artificial intuition was impossible, but now major tech titans like Google, Amazon, and IBM are all working to develop solutions and incorporate it into their operational flow.

WHAT IS ARTIFICIAL INTUITION?

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Descriptive analytics inform the user of what happened, while diagnostic analytics address why it happened. Artificial intuition can be described as “predictive analytics,” an attempt to determine what may happen in the future based on what occurred in the past.

For example, Ronald Coifman, Phillips Professor of Mathematics at Yale University, and an innovator in the AI space, used artificial intuition to analyze millions of bank accounts in different countries to identify $1 billion worth of nominal money transfers that funded a well-known terrorist group.

Coifman deemed “computational intuition” the more accurate term for artificial intuition, since it analyzes relationships in data instead of merely analyzing data values. His team creates algorithms which identify previously undetected patterns, such as cybercrime. Artificial intuition has made waves in the financial services sector where global banks are increasingly using it to detect sophisticated financial cybercrime schemes, including: money laundering, fraud, and ATM hacking.

ALPHAGO

One of the major insights into artificial intuition was born out of Google’s DeepMind research in which a super computer used AI, called AlphaGo, to become a master in playing GO, an ancient Chinese board game that requires intuitive thinking as part of its strategy. AlphaGo evolved to beat the best human players in the world. Researchers then created a successor called AlphaGo Zero which defeated AlphaGo, developing its own strategy based on intuitive thinking. Within three days, AlphaGo Zero beat the 18—time world champion Lee Se-dol, 100 games to nil. After 40 days, it won 90% of matches against AlphaGo, making it arguably the best Go player in history at the time.

AlphaGo Zero represents a major advancement in the field of Reinforcement Learning or “Self Learning,” a subset of Deep Learning which is a subset of Machine Learning. Reinforcement learning uses advanced neural networks to leverage data into making decisions. AlphaGo Zero achieved “Self Play Reinforcement Learning,” playing Go millions of times without human intervention, creating a neural network of “artificial knowledge” reinforced by a sequence of actions that had both consequences and inception. AlphaGo Zero created knowledge itself from a blank slate without the constraints of human expertise.

ENHANCING RATHER THAN REPLACING HUMAN INTUITION

The goal of artificial intuition is not to replace human instinct, but as an additional tool to help improve performance. Rather than giving machines a mind of their own, these techniques enable them to acquire knowledge without proof or conscious reasoning, and identify opportunities or potential disasters, for seasoned analysts who will ultimately make decisions.

Many potential applications remain in development for Artificial Intuition. We expect to see autonomous cars harness it, processing vast amounts of data and coming to intuitive decisions designed to keep humans safe. Although its ultimate effects remain to be seen, many researchers anticipate Artificial Intuition will be the future of AI.

A Smarter World Part 4: Securing the Smart City and the Technology Within

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In the last installment of our blog series on smart cities, we examined how smart transportation will make for a more efficient society. This week, we’ll examine how urban security stands to evolve with the implementation of smart technology.

Smart security in the modern era is a controversial issue for informed citizens. Many science fiction stories have dramatized the evolution of technology, and how every advance increases the danger of reaching a totalitarian state—particularly when it comes to surveillance. However, as a society, it would be foolish to refrain from using the technical power afforded to us to protect our cities.

Here are the top applications for smart security in the smart cities of the future:

Surveillance

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Surveillance has been a political point of contention and paranoia since the Watergate scandal in the early 1970s. Whistleblower Edward Snowden became a martyr or traitor depending on your point of view when he exposed vast surveillance powers used by the NSA. As technology has rapidly evolved, the potential for governments to abuse their technological power has evolved with it.

Camera technology has evolved to the point where everyone has a tiny camera on them at all time via their phones. While monitoring entire cities with surveillance feeds is feasible, the amount of manpower necessary to monitor the footage and act in a timely manner rendered this mass surveillance ineffective. However, deep learning-driven AI video analytics tools can analyze real-time footage and identify anomalies, such as foreboding indicators of violence, and notify nearby law enforcement instantly.

In China, police forces use smart devices allied to a private broadband network to discover crimes. Huawei’s eLTE system allows officers to swap incident details securely and coordinate responses between central command and local patrols. In Shanghai, sophisticated security systems have seen crime rates drop by 30% and the amount of time for police to arrive at crime scenes drop to 3 minutes.

In Boston, to curb gun violence, the Boston police force has deployed an IoT sensor-based gunfire detection system that notifies officers to crime scenes within seconds.

Disaster Prevention

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One of the major applications of IoT-based security system involves disaster prevention and effective use of smart communication and alert systems.

When disasters strike, governments require a streamlined method of coordinating strategy, accessing data, and managing a skilled workforce to enact the response. IoT devices and smart alert systems work together to sense impending disasters and give advance warning to the public about evacuations and security lockdown alerts.

Cybersecurity

The more smart applications present in city infrastructure, the more a city becomes susceptible to cyber attack. Unsecured devices, gateways, and networks each represent a potential vulnerability for a data breach. The average cost of a data breach according to IBM and the Poneman Institute is estimated at $3.86 million dollars. Thus, one of the major components of securing the smart city is the ramping up of cybersecurity to prevent hacking.

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The Industrial Internet Consortium are helping establish frameworks across technologies to safely accelerate the Industrial Internet of Things (IIot) for transformational outcomes. GlobalSign works to move secure IoT deployments forward on a world-wide basis.

One of the first and most important steps toward cybersecurity is adopting standards and recommended guidelines to help address the smart city challenges of today. The Cybersecurity Framework is a voluntary framework consisting of standards, guidelines, and best practices to manage cybersecurity-related risk published by the National Institute of Standards and Technology (NIST), a non-regulatory agency in the US Department of Commerce. Gartner projects that 50% of U.S. businesses, critical infrastructure operators, and countries around the globe will use the framework as they develop and deploy smart city technology.

Conclusion

The Smart City will yield a technological revolution, begetting a bevy of potential applications in different fields, and with every application comes potential for hacker exploitation. Deployment of new technologies will require not only data standardization, but new security standardizations to ensure that these vulnerabilities are protected from cybersecurity threats. However, don’t expect cybersecurity to slow the evolution of the smart city too much as it’s expected to grow into a $135 billion dollar industry by 2021 according to TechRepublic.

This concludes our blog series on Smart Cities, we hope you enjoyed and learned from it! In case you missed it, check out our past entries for a full picture of the future of smart cities:

A Smarter World Part 1: How the Future of Smart Cities Will Change the World

A Smarter World Part 2: How Smart Infrastructure Will Reshape Your City

A Smarter World Part 3: How Smart Transportation Will Accelerate Your Business

A Smarter World Part 1: How the Future of Smart Cities Will Change the World

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Are you ready for smart cities of the future?  Over the next few weeks, we will be endeavoring on a series of blogs exploring what the big players are developing for smart cities and how they will shape our world.

When the world becomes smart, life will begin to look a lot more like THE JETSONS!
When the world becomes smart, life will begin to look a lot more like THE JETSONS!

Our cities will become smart when they are like living organisms: actively gathering data from various sources and processing it to generate intelligence to drive responsive action. IoT, 5G, and AI will all work together to enable the cities of the future. IoT devices with embedded sensors will gather vast amounts of data, transmit it via high-speed 5G networks, and process it in the cloud through AI-driven algorithms designed to come up with preventative action. From smart traffic to smart flooding control, the problems smart cities can potentially solve are endless.

Imagine a world where bridges are monitored by hundreds of tiny sensors that send information about the amount of pressure on different pressure points. The data from those sensors instantly transmits via high-speed internet networks to the cloud where an AI-driven algorithm calculates potential breaking points and dispatches a solution in seconds.

That is where we are headed—and we’re headed there sooner than you think. Two-thirds of cities globally are investing in smart city technology and spending is projected to reach $135 billion by 2021. Here are the three of the top applications leading the charge in the Smart Cities space.

Smart Infrastructure

SMART INFRASTRUCTURE

As our opening description of smart bridges implies, smart infrastructure will soon become a part of our daily lives. In New Zealand, installed sensors monitor water quality and issue real-time warnings to help swimmers know where it’s safe to swim.

In order to enable smart functionality, sensors will need to be embedded throughout the city to gather vital information in different forms. In order to process the abundance of data, high-volume data storage and high-speed communications powered by high-bandwidth technologies like 5G will all need to become the norm before smart infrastructure can receive mass adoption.

Stay tuned for our next blog where we’ll get more in-depth on the future of smart infrastructure.

Smart Cars

SMART TRANSPORTATION

From smart parking meters to smart traffic lights, from autonomous cars to scooters and electric car sharing services, transportation is in the midst of a technological revolution and many advanced applications are just on the cusp of realization.

Smart parking meters will soon make finding a parking space in the city and paying for it easy.  In the UK, local councils can now release parking data in the same format, solving one of the major obstacles facing smart cities: Data Standardization (more on that later).

Autonomous cars, powered by AI, IoT, and 5G, will interact with the smart roads on which they are driving, reducing traffic and accidents dramatically.

While there is a debate about the long-term effectiveness of electric motorized scooters as a mode of transportation, they’ve become very popular in major US cities like San Francisco, Oakland, Los Angeles, Salt Lake City and are soon to come in Brooklyn.

With the New York Subway system in shambles, it seems inevitable the biggest city in the world will receive a state-of-the-art smart technology to drastically improve public transit.

Surveillance State

SMART SECURITY

The more you look at potential applications for smart security, the more it feels like you are looking at the dystopian future of the novel 1984.

Potential applications include AI-enabled crowd monitoring to prevent potential threats. Digital cameras like Go-Pros have shrunk the size of surveillance equipment to smaller than an apple. Drones are available at a consumer level as well. While security cameras can be placed plentifully throughout a city, one major issue is cultivating the manpower required to analyze all of the footage being gathered for potential threats. AI-driven algorithms to analyze footage for threats will enable municipalities to analyze threats and respond accordingly.

However, policy has not caught up with technology. The unique ethical quandaries brought up by smart security and surveillance will play out litigiously and dictate to what degree smart security will become a part of the cities of the future.

CONCLUSION

We can see what the future may look like, but how we’ll get there remains a mystery. Before smart technologies can receive mass adoption, legislation will need to be passed by both local and national governments. In addition, as the UK Parking Meter issue shows, data standardization will be another major obstacle for smart technology manufacturers. When governments on both a local and a national level an get on the same page with regard to how to execute smart city technology and legislation, the possibilities for Smart Cities will be endless.

Stay tuned next week for our deep dive into the future applications of Smart Infrastructure!

Monetizing IoT: How the Internet of Things Builds Fortunes

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A man sits in a restaurant and orders “The John Candy Burger” (a double cheeseburger with four strips of bacon and a fried egg) through a touch screen embedded into the table. As he gives the waiter his order, his smartwatch vibrates. He checks a push notification which tells him he should not order “The John Candy Burger” based on information gathered from a sensor in his body which has been monitoring his blood pressure and cholesterol among other notable health measurements in a constant stream of data for 15 years with infallible predictive capabilities. It tells him this specific cheeseburger from this specific restaurant will increase his risk of a heart attack on his daily run by 8%. He doesn’t understand how, but he accepts it the way one accepts that the earth is round and the Great Pyramid of Giza existed in 2540 BC.

In the above fictional example, the Internet of Things took the man’s order, evaluated the average nutritional content of the burger based on data gathered through sensors embedded into a smart grill, and transmitted it to the smartwatch where it analyzed nutritional content in the context of over 15 years of health data gathered on the man to inform him on the potential risk of his decision. The Internet of Things is bigger than money. It’s a new world where planes don’t crash and  smartphones can tell their users the location of the nearest empty parking spot to minimize travel time and ensure the city is maintaining optimum functionality. A pregnant wife is gently guided through a safe 9-month path to the newest addition to her family. The edges of the world are being smoothed out by data. The Internet of Things is leading the human race toward new levels of efficiency, productivity and effectiveness.

“Show me the money”

As a major technological evolution takes place, many businesses are looking to monetize it. Although the world has yet to see the full impact of the Internet of Things, it has already revolutionized process improvement for everything from manufacturing to health care, product enhancement, and safety. For the developer eager to enter a burgeoning field with infinite possibilities, here are some of the common techniques for monetizing IoT applications.

ONE-TIME PAY + FREE APP

The most basic monetization method entails creating a simple product with everyday applications, like Jawbone and the Phillips Hue Connected Bulb for example, and offering the equipment for purchase which works in conjunction with a connected app for iOS & Android. This method is most effective for products where the manufacturing cost to market ratio is kept low.

SUBSCRIPTION-BASED

One of the major issues with the IoT is the amount of data generated regularly by their devices. The amount of data and possibilities are so staggering, it’s vital to understand and decide upon relevant metrics and analysis tactics. For developers, it means that the cost of maintaining many IoT apps calls for a constant stream of revenue. Companies like Audi offer a hotspot subscription, ranging from 6 to 30 months, for Audi Connect, their hotspot navigation system utilizing Google Earth and Voice to offer real-time alerts, weather and traffic. In some applications, data plans will likely emerge as a another way of tiering subscription-based purchases.

WHITE LABEL SERVICES

Perhaps the most profitable and complex option, monetizing IoT applications through white label services entails having the foresight to identify the future of the technology and the necessary human & financial resources to act upon it effectively through the creation of a template offering which businesses can rebrand as their own. Jasper Technologies created the Connected Car Cloud as a cloud-based turnkey solution for developing smart-cars with real-time diagnostics, safety, security, and more.

Acquired by Cisco for about $1.4 billion in March, Jasper is one of the big success stories of IoT monetization and a model for future innovators looking to capitalize on the business opportunities brought about by the Internet of Things.

Learn more about IoT through this awesome article with advice from early adopters via Computer World.