Tag Archives: Data

Stay Ahead of Your Competition with the Top Digital Marketing Trends of 2022

In an era of rapid technological acceleration, every year brings new avenues to market services and methods to boost sales. While the metaverse lurks on the horizon, it’s still in the developmental stage. Meanwhile, the current digital marketing landscape has evolved significantly within the past few years. Software developers and business owners must keep up on the latest trends in order to ensure that they don’t fall behind their competitors.

Here are some of the biggest trends in digital marketing today:

PERSONALIZATION

Success in digital marketing is increasingly dependent on how companies collect data and leverage it toward personalized ads. Studies show personalization can deliver five to eight times the ROI on marketing spend.

Personalization at its most basic level entails targeting users based on their demographic or location. For example, Guinness created a hyper-localized ad campaign which incorporated a unique Facebook ad for every Guinness venue in the UK and Ireland. Over 30,000 localized video ads for over 2,500 bars were updated dynamically based on the rugby matches playing at a given time.

Personalization relies on three tenets: data discovery, automated decision-making, and content distribution. Major corporations like Amazon leverage more extensive data with automated decision-making dictated by robust AI algorithms. Netflix’s complex viewing algorithms determine what users may like to view next based on their past viewing habits. The result is not only improved user experience, but a more personal relationship with the brand.

SOCIAL COMMERCE

Projections from Accenture show social commerce will reach $1.2 trillion globally by 2025—about 300% faster than traditional ecommerce. Gen Z and Millennials will be the biggest spenders, accounting for 62% of social revenue by 2025. Platforms are working behind the scenes to improve customer experience by creating payment methods without leaving social media apps. Two major social platforms to watch are TikTok and Youtube.

TikTok usage has risen rapidly and reached 1 billion users and counting. Engagement has been titanic with users in the United States spending up to 850 hours per month on the app. It was the top earning non-gaming app in 2021 with $110 million spent by users and its potential will only grow as influencers earn huge amounts through sponsorship deals. TikTok is not just for Gen Z, it’s a rapidly growing network and brands are taking advantage by offering influencers huge amounts of money for branded content.

As brands move their investment in traditional TV models toward streaming, one platform which stands to benefit is Youtube. Global revenue for the video streaming channel soared to $29 billion, a 46% increase from 2020. Youtube is beginning to attract more traditional TV advertisers and consequentially, their ad business is nearly matching Netflix in revenue. While revenue is ascending, there remains significant headroom for major brands to up their investment in Youtube advertising as traditional cable models phase out.

IN-GAME ADVERTISING

Just over 50% of global revenue in the gaming industry is driven by mobile games. With gaming reaching a growth rate higher than all other entertainment industries, brands are looking to in-game advertising as a way of reaching a larger audience.

The gaming demographic has recently reached a 50-50 split between men and women. Contrary to most preconceptions, in-game advertising will help you reach a wider audience of both men and women. In-game advertising not only reaches a wider audience, it makes it easy to track click-throughs and analytics. Extensive analytics enable brands to collect very precise data about their customers and foster a deeper understanding of their habits.

Playable ads have arisen as a major hallmark for brands to market their games. Playable ads are interactive and encourage the user to try a snippet of functionality from the game. Check out the examples in the video below by Vungle.

CONCLUSION

Brands need to move as fast as the times if they hope to stay on the forefront of their industry. In the era of big data, the bigger your brand, the more possibilities digital marketing entails. As AI becomes more accessible, businesses of all sizes are wise to take advantage of the digital landscape and find ways to offer a more personal experience for their customers.

How the Internet of Behaviors Will Shape the Future of Digital Marketing

In the digital age, businesses need to leverage every possible platform and cutting-edge technology in order to get a leg up on the competition. We’ve covered the Internet of Things extensively on the Mystic Media blog, but a new and related tech trend is making waves. This trend is called the Internet of Behaviors and according to Gartner, about 40% of people will have their behavior tracked by the IoB globally by 2023.

WHAT IS THE IOB?

Internet of Behavior, or the IoB, exists at the intersection of technology, data analytics, and behavioral science. The IoB leverages data collected from a variety of sources, including online activities, social media, wearable devices, commercial transactions and IoT devices, in order to deliver insights related to consumers and purchasing behavior.

With devices more interconnected than ever, the IoB tracks, gathers, combines and interprets massive data sets so that businesses can better understand their consumers. Businesses leverage analysis from the IoB to offer more personalized marketing with the goal of influencing consumer decision making.

HOW DOES IT WORK?

Traditionally, a car insurance company would analyze a customer’s driving history in order to determine if they are a good or bad driver. However, in today’s digital age, they might take it a step further and analyze social media profiles in order to “predict” whether a customer is a safe driver. Imagine what insights they could gather from a user’s Google search history or Amazon purchases? Access to large datasets enables large companies to create psychographic profiles and gather an enhanced understanding of their customer base.

Businesses can use the IoB for more than just purchasing decisions. UX designers can leverage insights to deliver more effective customer experiences. Large companies such as Ford are designing autonomous vehicles that change based on the city, modulating behavior based on vehicle traffic, pedestrians, bicycles and more.

GBKSOFT created a mobile application that collects data from wearable devices in order to help golfers improve their skills. The application records each golf ball hit, including the stroke, force, trajectory and angle, and delivers visual recommendations to improve their swing and technique. Insights gathered through data are translated into behavioral trends that are then converted into recommendations to improve the user’s game.

The IoB is all about collecting data that can be translated into behavior which helps companies understand consumer tendencies and translate them into meaningful actions.

CONCERNS

While there is quite a bit of enthusiasm surrounding the potential impact of the IoB for B2C companies, a number of legal concerns come with it. A New York Times article, written by Harvard Business School emeritus professor Shoshana Zuboff, warns of the age of surveillance capitalism where tech behemoths surveil humans with the intent to control their behavior.

Due to the speed at which technology and the ability to collect data has proliferated, privacy and data security are under-regulated and major concerns for consumers. For example, Facebook was applying facial recognition scans in advance of the 2016 election without user’s consent. Cambridge Analytica’s use of psychoanalytic profiles has been the subject of much derision. Momentum for data privacy regulation is growing and since the IoB hinges on the ability for companies to collect and market data, forthcoming regulations could inhibit its impact.

CONCLUSION

Despite regulatory concerns, the IoB is a sector that we expect to see grow over time. As the IoT generates big data and AI evolves to learn how to parse through and analyze it, it’s only natural that companies will take the next step to leverage analysis to enhance their understanding of their customers’ behaviors and use it to their advantage. The IoB is where that next step will take place.

How Bluetooth Became the Gold Standard of Wireless Audio Technology

Bluetooth technology has established itself over the years as the premiere wireless audio technology and a staple of every smartphone user’s daily mobile experience. From wireless headphones, to speakers, to keyboards, gaming controllers, IoT devices, and instant hotspots—Bluetooth is used for a growing variety of functions every year.

While Bluetooth is now a household name, the path to popularity was built over the course of over 20 years.

CONCEPTION

In 1994, Dr. Jaap Haartsen—an electrical engineer working for Ericsson’s Mobile Terminal Division in Lund—was tasked with creating an indoor wireless communication system for short-range radio connections. He ultimately created the Bluetooth protocol. Named after the renowned Viking king who united Denmark and Norway in 958 AD, the Bluetooth protocol was designed to replace RS-232 telecommunication cables using short range UHF radio waves between 2.4 and 2.485 GHz.

In 1998, he helped create the Bluetooth Special Interest Group, driving the standardization of the Bluetooth radio interface and obtaining worldwide regulatory approval for Bluetooth technology. To this day, Bluetooth SIG publishes and promotes the Bluetooth standard as well as revisions.

BLUETOOTH REACHES CONSUMERS

In 1999, Ericsson introduced the first major Bluetooth product for consumers in the form of a hands-free mobile headset. The headset won the “Best of Show Technology” award at COMDEX and was equipped with Bluetooth 1.0.

Each iteration of Bluetooth has three main distinguishing factors:

  • Range
  • Data speed
  • Power consumption

The strength of these factors is determined by both the modulation scheme and data packet employed. As you might imagine, Bluetooth 1.0 was far slower than the Bluetooth we’ve become accustomed to in 2021. Data speeds capped at 1Mbps with a range up to 10 meters. While we use Bluetooth to listen to audio on a regular basis today, it was hardly equipped to handle music and primarily designed for wireless voice calls.

THE BLUETOOTH EVOLUTION

The Bluetooth we currently enjoy in 2021 is version 5. Over the years, Bluetooth’s range, data speed, and power consumption have increased dramatically.

In 2004, Bluetooth 2.0 focused on enhancing the data rate, pushing from 0.7Mbps in version 1 to 1-3Mbps while increasing range from 10m to 30m. Bluetooth 3.0 increased speeds in 2009, allowing up to 24Mbps.

In 2011, Bluetooth 4.0 introduced a major innovation in BLE (Bluetooth Low Energy). BLE is an alternate Bluetooth segment designed for very low power operation. It enables major flexibility to build products that meet the unique connectivity requirements of their market. BLE is tailored toward burst-like communications, remaining in sleep mode before and after the connection initiates. The decreased power consumption takes IoT devices like industrial monitoring sensors, blood pressure monitoring, and Fitbit devices to the next level. These devices can employ BLE to run at 1Mbps at very low power consumption rates. In addition to lowering the power consumption, Bluetooth 4.0 doubles the typical maximum range from 30m in Bluetooth 3.0 to 60m.

BLUETOOTH 5

Bluetooth 5 is the latest version of the technology. Bluetooth 5 doubles the bandwidth by doubling the speed of transmission. In addition, it quadruples the typical max range, bringing it up to 240m. Bluetooth 5 also introduces Bluetooth Low Energy audio, which enables one device to share audio with multiple other devices.

CONCLUSION

Bluetooth is a game-changing technology which stands to revolutionize more than just audio. IoT devices, health tech, and more stand to improve as the Bluetooth SIG continues to upgrade the protocol. After thirty years of improvement, the possibilities remain vast for savvy developers to take advantage of the latest Bluetooth protocols to build futuristic wireless technologies.

HL7 Protocol Enhances Medical Data Transmissions–But Is It Secure?

In our last blog, we examined how DICOM became the standard format for transmitting files in medical imaging technology. As software developers, we frequently find ourselves working in the medical technology field navigating new formats and devices which require specialized attention.

This week, we will jump into one of the standards all medical technology developers should understand: the HL7 protocol.

The HL7 protocol is a set of international standards for the transfer of clinical and administrative data between hospital information systems. It refers to a number of flexible standards, guidelines, and methodologies by which various healthcare systems communicate with each other. HL7 connects a family of technologies, providing a universal framework for the interoperability of healthcare data and software.

Founded in 1987, Health Level Seven International (HL7) is a non-profit, ANSI-accredited standards developing organization that manages updates of the HL7 protocol. With over 1,600 members from over 50 countries, HL7 International represents brain trust incorporating the expertise of healthcare providers, government stakeholders, payers, pharmaceutical companies, vendors/suppliers, and consulting firms.

HL7 has primary and secondary standards. The primary standards are the most popular and integral for system integrations, interoperability, and compliance. Primary standards include the following:

  • Version 2.x Messaging Standard–an interoperability specification for health and medical transactions
  • Version 3 Messaging Standard–an interoperability specification for health and medical transactions
  • Clinical Document Architecture (CDA)–an exchange model for clinical documents, based on HL7 Version 3
  • Continuity of Care Document (CCD)–a US specification for the exchange of medical summaries, based on CDA.
  • Structured Product Labeling (SPL)–the published information that accompanies a medicine based on HL7 Version 3
  • Clinical Context Object Workgroup (CCOW)–an interoperability specification for the visual integration of user applications

While HL7 may enjoy employment worldwide, it’s also the subject of controversy due to underlying security issues. Researchers from the University of California conducted an experiment to simulate an HL7 cyber attack in 2019, which revealed a number of encryption and authentication vulnerabilities. By simulating a main-in-the-middle (MITM) attack, the experiment proved a bad actor could potentially modify medical lab results, which may result in any number of catastrophic medical miscues—from misdiagnosis to prescription of ineffective medications and more.

As software developers, we advise employing advanced security technology to protect patient data. Medical professionals are urged to consider the following additional safety protocols:

  • A strictly enforced password policy with multi-factor authentication
  • Third-party applications which offer encrypted and authenticated messaging
  • Network segmentation, virtual LAN, and firewall controls

While HL7 provides unparalleled interoperability for health care data, it does not provide ample security given the level of sensitivity of medical data—transmissions are unauthenticated and unvalidated and subject to security vulnerabilities. Additional security measures can help medical providers retain that interoperability across systems while protecting themselves and their patients from having their data exploited.

HOW DICOM BECAME THE STANDARD IN MEDICAL IMAGING TECHNOLOGY

Building applications for medical technology projects often requires extra attention from software developers. From adhering to security and privacy standards to learning new technologies and working with specialized file formats—developers coming in fresh must do a fair amount of due diligence to get acclimated in the space. Passing sensitive information between systems requires adherence to extra security measures—standards like HIPAA (Health Insurance Portability and Accountability Act) are designed to protect the security of health information.

When dealing with medical images and data, one international standard rises above the rest: DICOM. There are hundreds of thousands of medical imaging devices in use—and DICOM has emerged as the most widely used healthcare messaging standards and file formats in the world. Billions of DICOM images are currently employed for clinical care.

What is DICOM?

DICOM stands for Digital Imaging and Communications in Medicine. It’s the international file format and communications standard for medical images and related information, implemented in nearly every radiology, cardiology, imaging, and radiotherapy devices such as X-rays, CT scans, MRI, ultrasound, and more. It’s also finding increasing adoption in fields such as ophthalmology and dentistry.

DICOM groups information into data sets. Similar to how JPEGs often include embedded tags to identify or describe the image, DICOM files include patient ID to ensure that the image retains the necessary identification and is never separated from it. The bulk of images are single frames, but the attribute can also contain multiple frames, allowing for storage of Cineloops.

The History of DICOM

DICOM was developed by the American College of Radiology (ACR) and the National Electrical Manufacturer’s Association (NEMA) in the 1980s. Technologies such as CT scans and other advanced imaging technologies made it evident that computing would play an increasingly major role in the future of clinical work. The ACR and NEMA sought a standard method for transferring images and associated information between devices from different vendors.

The first standard covering point-to-point image communication was created in 1985 and initially titled ACR-NEMA 300. A second version was subsequently released in 1988, finding increased adoption among vendors. The first large-scale deployment of ACR-NEMA 300 was in 1992 by the U.S. Army and Air Force. In 1993, the third iteration of the standard was released—and it was officially named DICOM. While the latest version of DICOM is still 3.0, it has received constant maintenance and updates since 1993.

Why Is DICOM Important?

DICOM enables the interoperability of systems used to manage workflows as well as produce, store, share, display, query, process, retrieve and print medical images. By conforming to a common standard, DICOM enables medical professionals to share data between thousands of different medical imaging devices across the world. Physicians use DICOM to access images and reports to diagnose and interpret information from any number of devices.

DICOM creates a universal format for physicians to access medical imaging files, enabling high-performance review whenever images are viewed. In addition, it ensures that patient and image-specific information is properly stored by employing an internal tag system.

DICOM has few disadvantages. Some pathologists perceive the header tags to be a major flaw. Some tags are optional, while others are mandatory. The additional tags can lead to inconsistency or incorrect data. It also makes DICOM files 5% larger than their .tiff counterparts.

The Future

The future of DICOM remains bright. While no file format or communications standard is perfect, DICOM offers unparalleled cross-vendor interoperability. Any application developer working in the medical technology field would be wise to take the time to comprehensively understand it in order to optimize their projects.

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

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

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.

Maximize Profits with the Top Freemium Tactics of 2020

The global gaming market is estimated at $152 billion, with 45% derived from mobile games. The mobile game market is constantly evolving, new tactics and even platforms, like Apple Arcade, are being introduced. As a mobile game developer, being dynamic and staying up on the latest trends is of the utmost importance. Staying on top of these trends will help make a more engaging and profitable mobile game.

Keeping this in mind, below are the top freemium tactics of 2020:

RETENTION IS (STILL) KING

Mobile game developers must remember that freemium games begin and end with a good retention strategy that keeps users engaged.

Daily Tasks: Set-up daily tasks that pass the Starbucks Test. One of them can be opening the app on a daily basis. These should be fairly simple to complete and offer a reward, encouraging users to integrate gameplay into their daily lives.

Rewards Pack on User Birthdays: Give users some kind of bonus on their birthday to enrich their personal relationship with the game.

Challenge Dormant Users: After 3 days, give users a special, temporary challenge to reengage them with the app. Temporary promotions can be an effective way to instill a sense of urgency in the call-to-action and trigger users to open the app.

Promotion Before Subscription/Free Trial Ends: Tempt the user to sign-up or to extend their subscription by offering a temporary promotion 24-48 hours before their free trial/subscription ends.

When it comes to measuring retention, check out the model retention rates below from The Tool (Performance-Based Mobile ASO):

  • Day 1 Retention – 40%
  • Day 7 Retention – 20%
  • Day 28 Retention – 10%

Retention can also be tracked hourly instead of daily where Day 1 Retention will be the percentage of users who returned within 24-48 hours from the install. Here’s how it might look in analytics systems such as devtodev (via The Tool):

Retention-Analytics

OUTSTREAM VIDEO ADS

Outstream Video is a new type of video ad unit, referred to sometimes as “native video”, designed for targeting mobile users.

Outstream Video ads do not require placement within a Youtube video. They play with the sound off on mobile screens when more than 70% of the ad is visible. The user can tap the ad to turn the sound on and restart the video from the beginning, or they can continue scrolling. When less than 70% of the ad is visible, the video pauses.

Advertisers such as the Hong Kong tourism board have had great success using Outstream Video ads, delivering 30% incremental reach with a 40% lower cost per completed video and 85% lower CPM.

REWARDED ADS PAY OFF

When it comes to monetizing a mobile game through advertising, rewarded ads remain at the top of the food chain. A recent survey of app publishers asked what their most successful monetization method was. Rewarded Video Ads won with 75% of the vote.

By offering users some kind of in-game reward, such as an extra life, a bonus item, or a new avatar, app developers can improve UI and engagement while encouraging ad views without bothering the user. Rewarded ads remain the ad unit with the highest earning potential.

LOOT BOXES

A loot box is a randomized box of in-game prizes. Users pay for an in-app purchase, but there is no guarantee of whether it will contain gold or pennies, the user has to make the decision to purchase in exchange a random reward. While this tactic is somewhat controversial in Europe where Belgium and the Netherlands have cracked down and labeled it gambling, it remains a popular tactic. Loot boxes are particularly effective for  Whales, wealthy mobile game users who will readily pay to improve their performance in the game.

SELL YOUR DATA

The collection and sale of data is a massive industry. If your app offers the technical means to collect user-generated data such as geolocation, it may be worth it to acquire user consent to license that data.

Applications like Waze & Foursquare receive community-generated data from their users and effectively leverage it to monetize their applications. Waze licenses data to businesses placing location-based ads, whereas Foursquare licenses point of interest geolocation data to Google & Apple for their first party GPS apps Apple Maps & Google Maps.

CONCLUSION

It is important to keep in mind that monetization is the icing on the cake—without an engaging game that hooks users, there will be nothing to monetize. However, making key decisions in the development process with the monetization strategy in mind will *literally* pay off in the long run.

Check out our previous blogs on Mobile Game Monetization for an overview of the fundamentals.

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

In the last installment of our blog series on smart cities, we examined how smart infrastructure will revolutionize smart cities. This week, we will examine the many applications which will soon revolutionize smart transportation.

A smarter world means a faster, more efficient and environmentally-friendly world. And perhaps the biggest increase in efficiency and productivity will be driven by the many ways in which AI can optimize the amount of time it takes to get where you’re going.

Here are the top applications in smart transportation coming to a city near you:

Autonomous-vehicle-AdobeStock_174958313_rm

AUTONOMOUS VEHICLES

Some say autonomous vehicles are headed to market by 2020. Others say it could take decades before they are on the road. One thing is for certain, they represent a major technological advancement for smart transportation. Autonomous cars will communicate with each other to avoid accidents and contain state-of-the-art sensors to help keep you and your vehicle safe from harm.

Although autonomous vehicles are arguably the largest technological advancement on the horizon, they will also benefit greatly from a variety of smart transportation applications that will accelerate navigating your local metropolis.

Integrated-Roadways

SMART ROADS

What if we could turn roads into a true digital network, giving real-time traffic updates, supporting autonomous car technology, and providing true connectivity between vehicles and smart cities?

That’s the question tech start-up Integrated Roadways intends to answer. Integrated Roadways develops fiber-connected smart pavement outfitted with a vast amount of sensors, routers, and antennae that send information to data centers along the highway. They recently inked a 5 year deal to test out patented fiber-connected pavement in Colorado.

Smart Roads represent a major advancement in creating vehicle-to-infrastructure (V2I) connectivity. With 37,133 deaths from motor vehicles on American roads in 2017, the combination of AI applications in smart roads and autonomous cars could revolutionize vehicular transport and create a safer, faster world.

smart-traffic-lights-1_AMaJV_24429

SMART TRAFFIC LIGHTS

The vehicle-to-infrastructure connectivity spans beyond the roads and into the traffic light. Idling cars generate an estimated 30 million tons of carbon dioxide. Traffic jams can make it harder for first responders to reach emergencies. Rapid Flow proposes that the answer may be their AI-based adaptive traffic management system called Surtrac.

Surtrac uses a decentralized network of smart traffic lights equipped with cameras, radar, and other sensors to manage traffic flows. Surtrac’s sensors identify approaching vehicles, calculate their speed and trajectory, and adjust a traffic signal’s timing schedule as needed.

red line bus

SMART PUBLIC TRANSIT

There are a variety of smart applications which are revolutionizing public transportation.

In Singapore, hundreds of cameras and sensors citywide analyze traffic congestion and crowd density, enabling government officials to reroute buses at rush hour, reducing the risk of traffic jams. In Indianapolis, the electric Red Line bus service runs a 13 mile path that travels within a quarter of a mile of roughly 150,000 jobs.

One of the major disruptors which has seen rapid adoption in the smart public transport are electric scooter sharing services like Bird and Lime. Electric scooters fill in the public transportation gap for people looking to go 1-3 miles without having to walk or take a taxi. Electric scooters have seen adoption in Los Angeles, San Francisco, Salt Lake City, Brooklyn, and more cities around the globe.

CONCLUSION

Smart cities will have a host of revolutionary applications working in unison and communicating through smart infrastructure with municipalities to ensure maximum efficiency and safety when it comes to transportation. In our next installment of our series on smart cities, we’ll examine how smart security will help keep city-dwellers safe.

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

Imagine a city that monitors its own health, identifies potential fail points using AI algorithms, and autonomously takes action to prevent future disasters.

This is the smart-city of the future. In our first installment of our blog series on Smart Cities, we ran through an overview of how Smart Cities will change our world. In this second entry of our blog on smart cities, we’ll examine perhaps the biggest building block necessary to create a smart city: smart infrastructure.

The construction of a smart city begins with developing a vast, city-wide IoT system, embedding sensors and actuators into the infrastructure of the city to create a network of smart things. The sensors and actuators collect data and send it to field gateways which preprocess and filter data before transmitting it through a cloud gateway to a Data Lake. The Data Lake stores a vast amount of data in its raw state. Gradually, data is extracted for meaningful insights and sent to the Big Data warehouse where it’s structured. From here, monitoring and basic analytics will occur to determine potential fail points and preventative measures.

Check out the breakdown below:

Breakdown

As you can see, it all begins with the construction of smart infrastructure that can collect data. Here are some of the big applications in the smart infrastructure space:

STRUCTURAL HEALTH

One of the major applications of smart infrastructure will be monitoring key data points in major structures, such as the vibrations and material conditions of buildings, bridges, historical monuments, roads, etc.

Cultivating data will initiate basic analysis and preventative measures, but as we gather more and more data, AI and machine learning algorithms will learn from vast statistical analysis and be able to analyze historical sensor data to identify trends and create predictive models to prevent future disasters from happening with unprecedented accuracy.

Learn more about how Acellant is building the future of structure health monitoring.

ENVIRONMENTAL APPLICATIONS

There are a multitude of potentially environmental applications for smart infrastructure designed to optimize city activities for environmental health. For example, embedding street lights with intelligent and weather adaptive lighting will reduce the amount of energy necessary to keep roads alight.

Air pollution monitoring will help control CO2 emissions of factories and monitor the pollution emitted by cars. Ultimately, earthquake early detection can help monitor distributed control in specific places of tremors.

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WASTE MANAGEMENT

Boston is well-known as one of the top college cities in the United States. Every fall, over 160,000 college students from MIT, Harvard, Northeastern, BU, BC, Berklee School of Music, and more move in to their new living spaces, causing undue stress on the city’s waste management administration. ANALYZE BOSTON, the city’s open data portal, provided key data points such as housing rentals, trash volume and pick-up frequency, enabling a project called TRASH CITY to reroute waste management routes during this trying time.

CONCLUSION

Projects like Trash City show the many ways in which we can optimize city operations by analyzing data effectively. As smart infrastructure enables the collection of more and more data, projects like TRASH CITY will become more efficient and more effective.

Of course, the biggest application of Smart Infrastructure will be the many ways in which it will change how you get from A to B. Next week, we’ll focus in on smart transportation and how it will reshape metropolitan transportation.

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

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!