Virtual Identity

•  Paradigm for the Connected World • 

Author: VIE

  • Let’s discuss Functional NFTs

    Let’s discuss Functional NFTs

    Functional NFTs are changing the ways we interact with each other and the gaming experience. Earlier, NFTs were limited to products but now it’s putting a value on services too. Now with functional NFTs, you can choose to buy an experience rather than a piece of art. 

    Non-Fungible Tokens (NFTs) have stirred up things in the world of art. While the underlying technology behind NFTs remains simple. They have morphed into multiple applications some of which we shall discuss soon. Traditionally there have been five categories of NFTs: Collectibles, Game Assets, Virtual Land, Crypto Art and Others (including domain names, property titles) etc. Currently, there seems to be another category that has been getting some buzz in the industry. This new player is called “Functional NFTs”. 

    What are Functional NFTs?

    Let’s discuss what Functional NFTs are first. The meaning should be clear from the name itself. NFTs that provide some sort of functionality. It could be a game asset that performs some function. For example, if a game has an avatar as an NFT and it provides certain functionality, then it can be called a Functional NFT. This functionality can be seen as accruing points in a game or giving the player some special power.

    Another example can be an NFT created by a restaurant owner. The NFT works as a pass for one person to have dinner on Sunday at the restaurant. Therefore the NFT has some functionality and serves a given purpose. In a similar fashion imagine walking into a club and not having to stand in a line. Well, there can be an NFT for that too. Owning that NFT can give you free access to the club and since you own the NFT, people do not need to check for your ID. 

    Normal vs Functional NFTs

    Moreover, there has been a heated debate about value accrual in normal NFTs vs Functional NFTs. The argument is that non-functional NFTs are easier to make and are sold quickly on the market. Thus acquiring value quickly. In comparison to that Functional NFTs such as in games need to be thought about. It takes time to build a great experience around the basic utility of the functional NFT.

    Consequently taking more time to build value. For example, Axie Infinity, a Pokemon-like game that allows players to collect, breed and battle creatures. It was launched in 2018, but it was quite different then from what it is right now. The developer team had multiple iterations to finesse the game experience. Once the gaming experience was finessed, the NFT assets within the game accrued value. The phenomenon is termed as “Promise Effect” which says that an NFT that promises some experience will accrue value slower than a non-functional NFT.

    A new type of Functional NFTs

    HODL Valley, a new metaverse gaming project is trying to create a tokenized city. One among many of its features is Functional NFT, but these NFTs take it a step too far. HODL Valley contains around 24 different locations, each with a specific function and utility. These locations are connected to DApps which carry out the functionality for users. These locations can be purchased in-app and the revenues generated by them can be taken home by the NFT owner. For example, let’s say a bank has been represented by an NFT. Since it’s connected to a DApp, it can provide lending and borrowing services. As other users in the game play and use the bank. The NFT owner, who is, in turn, the owner of the bank will be able to generate an income stream from it. That is how functional NFTs have been pitched recently. 

    These functional NFTs are bound to change the way we interact with games and real life. With added functionality, individuals can get a unique experience. It’s not just a token anymore which represents value, it’s a function in itself. If NFTs was money then it was only selling products until now. Now, it has started moving into services too.

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  • What is Facial Recognition?

    What is Facial Recognition?

    What is facial recognition?

    Facial recognition is a way of identifying or confirming an individual’s identity using their face. Facial recognition systems can be used to identify people in photos, videos, or in real-time.

    Facial recognition is a category of biometric security. Other forms of biometric software include voice recognition, fingerprint recognition, and eye retina or iris recognition. The technology is mostly used for security and law enforcement, though there is increasing interest in other areas of use.

    How does facial recognition work?

    Many people are familiar with face recognition technology through the FaceID used to unlock iPhones (however, this is only one application of face recognition). Typically, facial recognition does not rely on a massive database of photos to determine an individual’s identity — it simply identifies and recognizes one person as the sole owner of the device, while limiting access to others.

    Beyond unlocking phones, facial recognition works by matching the faces of people walking past special cameras, to images of people on a watch list. The watch lists can contain pictures of anyone, including people who are not suspected of any wrongdoing, and the images can come from anywhere — even from our social media accounts. Facial technology systems can vary, but in general, they tend to operate as follows:

    Step 1: Face detection

    The camera detects and locates the image of a face, either alone or in a crowd. The image may show the person looking straight ahead or in profile.

    Step 2: Face analysis

    Next, an image of the face is captured and analyzed. Most facial recognition technology relies on 2D rather than 3D images because it can more conveniently match a 2D image with public photos or those in a database. The software reads the geometry of your face. Key factors include the distance between your eyes, the depth of your eye sockets, the distance from forehead to chin, the shape of your cheekbones, and the contour of the lips, ears, and chin. The aim is to identify the facial landmarks that are key to distinguishing your face.

    Step 3: Converting the image to data

    The face capture process transforms analog information (a face) into a set of digital information (data) based on the person’s facial features. Your face’s analysis is essentially turned into a mathematical formula. The numerical code is called a faceprint. In the same way that thumbprints are unique, each person has their own faceprint.

    Step 4: Finding a match

    Your faceprint is then compared against a database of other known faces. For example, the FBI has access to up to 650 million photos, drawn from various state databases. On Facebook, any photo tagged with a person’s name becomes a part of Facebook’s database, which may also be used for facial recognition. If your faceprint matches an image in a facial recognition database, then a determination is made.

    Of all the biometric measurements, facial recognition is considered the most natural. Intuitively, this makes sense, since we typically recognize ourselves and others by looking at faces, rather than thumbprints and irises. It is estimated that over half of the world’s population is touched by facial recognition technology regularly.

    How facial recognition is used

    The technology is used for a variety of purposes. These include:

    Unlocking phones

    Various phones, including the most recent iPhones, use face recognition to unlock the device. The technology offers a powerful way to protect personal data and ensures that sensitive data remains inaccessible if the phone is stolen. Apple claims that the chance of a random face unlocking your phone is about one in 1 million.

    Law enforcement

    Facial recognition is regularly being used by law enforcement. According to this NBC report, the technology is increasing amongst law enforcement agencies within the US, and the same is true in other countries. Police collects mugshots from arrestees and compare them against local, state, and federal face recognition databases. Once an arrestee’s photo has been taken, their picture will be added to databases to be scanned whenever police carry out another criminal search.

    Also, mobile face recognition allows officers to use smartphones, tablets, or other portable devices to take a photo of a driver or a pedestrian in the field and immediately compare that photo against to one or more face recognition databases to attempt an identification.

    Airports and border control

    Facial recognition has become a familiar sight at many airports around the world. Increasing numbers of travellers hold biometric passports, which allow them to skip the ordinarily long lines and instead walk through an automated ePassport control to reach the gate faster. Facial recognition not only reduces waiting times but also allows airports to improve security. The US Department of Homeland Security predicts that facial recognition will be used on 97% of travellers by 2023. As well as at airports and border crossings, the technology is used to enhance security at large-scale events such as the Olympics.

    Applications of face recognition.

    Finding missing persons

    Facial recognition can be used to find missing persons and victims of human trafficking. Suppose missing individuals are added to a database. In that case, law enforcement can be alerted as soon as they are recognized by face recognition — whether it is in an airport, retail store, or other public space.

    Reducing retail crime

    Facial recognition is used to identify when known shoplifters, organized retail criminals, or people with a history of fraud enter stores. Photographs of individuals can be matched against large databases of criminals so that loss prevention and retail security professionals can be notified when shoppers who potentially represent a threat enter the store.

    Improving retail experiences

    The technology offers the potential to improve retail experiences for customers. For example, kiosks in stores could recognize customers, make product suggestions based on their purchase history, and point them in the right direction. “Face pay” technology could allow shoppers to skip long checkout lines with slower payment methods.

    Banking

    Biometric online banking is another benefit of face recognition. Instead of using one-time passwords, customers can authorize transactions by looking at their smartphone or computer. With facial recognition, there are no passwords for hackers to compromise. If hackers steal your photo database, ‘liveless’ detection – a technique used to determine whether the source of a biometric sample is a live human being or a fake representation – should (in theory) prevent them from using it for impersonation purposes. Face recognition could make debit cards and signatures a thing of the past.

    Marketing and advertising

    Marketers have used facial recognition to enhance consumer experiences. For example, frozen pizza brand DiGiorno used facial recognition for a 2017 marketing campaign where it analyzed the expressions of people at DiGiorno-themed parties to gauge people’s emotional reactions to pizza. Media companies also use facial recognition to test audience reaction to movie trailers, characters in TV pilots, and optimal placement of TV promotions. Billboards that incorporate face recognition technology – such as London’s Piccadilly Circus – means brands can trigger tailored advertisements. 

    Healthcare

    Hospitals use facial recognition to help with patient care. Healthcare providers are testing the use of facial recognition to access patient records, streamline patient registration, detect emotion and pain in patients, and even help to identify specific genetic diseases. AiCure has developed an app that uses facial recognition to ensure that people take their medication as prescribed. As biometric technology becomes less expensive, adoption within the healthcare sector is expected to increase.

    Tracking student or worker attendance

    Some educational institutions in China use face recognition to ensure students are not skipping class. Tablets are used to scan students’ faces and match them to photos in a database to validate their identities. More broadly, the technology can be used for workers to sign in and out of their workplaces, so that employers can track attendance.

    Recognizing drivers

    According to this consumer report, car companies are experimenting with facial recognition to replace car keys. The technology would replace the key to access and start the car and remember drivers’ preferences for seat and mirror positions and radio station presets.

    Monitoring gambling addictions

    Facial recognition can help gambling companies protect their customers to a higher degree. Monitoring those entering and moving around gambling areas is difficult for human staff, especially in large crowded spaces such as casinos. Facial recognition technology enables companies to identify those who are registered as gambling addicts and keeps a record of their play so staff can advise when it is time to stop. Casinos can face hefty fines if gamblers on voluntary exclusion lists are caught gambling.

    Examples of facial recognition technology

    1. Amazon previously promoted its cloud-based face recognition service named Rekognition to law enforcement agencies. However, in a June 2020 blog post, the company announced it was planning a one-year moratorium on the use of its technology by police. The rationale for this was to allow time for US federal laws to be initiated, to protect human rights and civil liberties.
    2. Apple uses facial recognition to help users quickly unlock their phones, log in to apps, and make purchases.
    3. British Airways enables facial recognition for passengers boarding flights from the US. Travellers’ faces can be scanned by a camera to have their identity verified to board their plane without showing their passport or boarding pass. The airline has been using the technology on UK domestic flights from Heathrow and is working towards biometric boarding on international flights from the airport.
    4. Cigna, a US-based healthcare insurer, allows customers in China to file health insurance claims which are signed using a photo, rather than a written signature, in a bid to cut down on instances of fraud.
    5. Coca-Cola has used facial recognition in several ways across the world. Examples include rewarding customers for recycling at some of its vending machines in China, delivering personalized ads on its vending machines in Australia, and for event marketing in Israel.
    6. Facebook began using facial recognition in the US in 2010 when it automatically tagged people in photos using its tag suggestions tool. The tool scans a user’s face and offers suggestions about who that person is. Since 2019, Facebook has made the feature opt-in as part of a drive to become more privacy focused. Facebook provides information on how you can opt-in or out of face recognition here.
    7. Google incorporates the technology into Google Photos and uses it to sort pictures and automatically tag them based on the people recognized.
    8. MAC make-up, uses facial recognition technology in some of its brick-and-mortar stores, allowing customers to virtually “try on” make-up using in-store augmented reality mirrors.
    9. McDonald’s has used facial recognition in its Japanese restaurants to assess the quality of customer service provided there, including analyzing whether its employees are smiling while assisting customers.
    10. Snapchat is one of the pioneers of facial recognition software: it allows brands and organizations to create filters which mould to the user’s face — hence the ubiquitous puppy dog faces and flower crown filters seen on social media.

    Technology companies that provide facial recognition technology include:

    • Kairos
    • Noldus
    • Affectiva
    • Sightcorp
    • Nviso

    Advantages of face recognition

    Aside from unlocking your smartphone, facial recognition brings other benefits:

    Increased security

    On a governmental level, facial recognition can help to identify terrorists or other criminals. On a personal level, facial recognition can be used as a security tool for locking personal devices and for personal surveillance cameras.

    Reduced crime

    Face recognition makes it easier to track down burglars, thieves, and trespassers. The sole knowledge of the presence of a face recognition system can serve as a deterrence, especially to petty crime. Aside from physical security, there are benefits to cybersecurity as well. Companies can use face recognition technology as a substitute for passwords to access computers. In theory, the technology cannot be hacked as there is nothing to steal or change, as is the case with a password.

    Removing bias from stop and search

    Public concern over unjustified stops and searches is a source of controversy for the police — facial recognition technology could improve the process. By singling out suspects among crowds through an automated rather than human process, face recognition technology could help reduce potential bias and decrease stops and searches on law-abiding citizens.

    Greater convenience

    As the technology becomes more widespread, customers will be able to pay in stores using their face, rather than pulling out their credit cards or cash. This could save time in checkout lines. Since there is no contact required for facial recognition as there is with fingerprinting or other security measures – useful in the post-COVID world – facial recognition offers a quick, automatic, and seamless verification experience.

    Faster processing

    The process of recognizing a face takes only a second, which has benefits for the companies that use facial recognition. In an era of cyber-attacks and advanced hacking tools, companies need both secure and fast technologies. Facial recognition enables quick and efficient verification of a person’s identity.

    Integration with other technologies

    Most facial recognition solutions are compatible with most security software. In fact, it is easily integrated. This limits the amount of additional investment required to implement it.

    Disadvantages of face recognition

    While some people do not mind being filmed in public and do not object to the use of facial recognition where there is a clear benefit or rationale, the technology can inspire intense reactions from others. Some of the disadvantages or concerns include:

    Surveillance

    Some worry that the use of facial recognition along with ubiquitous video cameras, artificial intelligence, and data analytics creates the potential for mass surveillance, which could restrict individual freedom. While facial recognition technology allows governments to track down criminals, it could also allow them to track down ordinary and innocent people at any time.

    Scope for error

    Facial recognition data is not free from error, which could lead to people being implicated for crimes they have not committed. For example, a slight change in camera angle or a change in appearance, such as a new hairstyle, could lead to error. In 2018, Newsweek reported that Amazon’s facial recognition technology had falsely identified 28 members of the US Congress as people arrested for crimes.

    Breach of privacy

    The question of ethics and privacy is the most contentious one. Governments have been known to store several citizens’ pictures without their consent. In 2020, the European Commission said it was considering a ban on facial recognition technology in public spaces for up to five years, to allow time to work out a regulatory framework to prevent privacy and ethical abuses.

    Massive data storage

    Facial recognition software relies on machine learning technology, which requires massive data sets to “learn” to deliver accurate results. Such large data sets require robust data storage. Small and medium-sized companies may not have sufficient resources to store the required data.

    Facial recognition security – how to protect yourself

    While biometric data is generally considered one of the most reliable authentication methods, it also carries significant risk. That’s because if someone’s credit card details are hacked, that person has the option to freeze their credit and take steps to change the personal information that was breached. What do you do if you lose your digital ‘face’?

    Around the world, biometric information is being captured, stored, and analyzed in increasing quantities, often by organizations and governments, with a mixed record on cybersecurity. A question increasingly being asked is, how safe is the infrastructure that holds and processes all this data?

    As facial recognition software is still in its relative infancy, the laws governing this area are evolving (and sometimes non-existent). Regular citizens whose information is compromised have relatively few legal avenues to pursue. Cybercriminals often elude the authorities or are sentenced years after the fact, while their victims receive no compensation and are left to fend for themselves.

    As the use of facial recognition becomes more widespread, the scope for hackers to steal your facial data to commit fraud — increases.

    Biometric technology offers very compelling security solutions. Despite the risks, the systems are convenient and hard to duplicate. These systems will continue to develop in the future — the challenge will be to maximize their benefits while minimizing their risks.

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  • What is the IoT?

    What is the IoT?

    The Internet of Things (IoT) describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. These devices range from ordinary household objects to sophisticated industrial tools. With more than 7 billion connected IoT devices today, experts are expecting this number to grow to 10 billion by 2020 and 22 billion by 2025. 

    Why is Internet of Things (IoT) so important?

    Over the past few years, IoT has become one of the most important technologies of the 21st century. Now that we can connect everyday objects—kitchen appliances, cars, thermostats, baby monitors—to the internet via embedded devices, seamless communication is possible between people, processes, and things.

    By means of low-cost computing, the cloud, big data, analytics, and mobile technologies, physical things can share and collect data with minimal human intervention. In this hyperconnected world, digital systems can record, monitor, and adjust each interaction between connected things. The physical world meets the digital world—and they cooperate.

    What technologies have made IoT possible?

    While the idea of IoT has been in existence for a long time, a collection of recent advances in a number of different technologies has made it practical.

    • Access to low-cost, low-power sensor technology. Affordable and reliable sensors are making IoT technology possible for more manufacturers.
    • Connectivity. A host of network protocols for the internet has made it easy to connect sensors to the cloud and to other “things” for efficient data transfer.
    • Cloud computing platforms. The increase in the availability of cloud platforms enables both businesses and consumers to access the infrastructure they need to scale up without actually having to manage it all.
    • Machine learning and analytics. With advances in machine learning and analytics, along with access to varied and vast amounts of data stored in the cloud, businesses can gather insights faster and more easily. The emergence of these allied technologies continues to push the boundaries of IoT and the data produced by IoT also feeds these technologies.
    • Conversational artificial intelligence (AI). Advances in neural networks have brought natural-language processing (NLP) to IoT devices (such as digital personal assistants Alexa, Cortana, and Siri) and made them appealing, affordable, and viable for home use.

    What is industrial IoT?

    Industrial IoT (IIoT) refers to the application of IoT technology in industrial settings, especially with respect to instrumentation and control of sensors and devices that engage cloud technologies. Refer to thisTitan use case PDF for a good example of IIoT. Recently, industries have used machine-to-machine communication (M2M) to achieve wireless automation and control. But with the emergence of cloud and allied technologies (such as analytics and machine learning), industries can achieve a new automation layer and with it create new revenue and business models. IIoT is sometimes called the fourth wave of the industrial revolution, or Industry 4.0. The following are some common uses for IIoT:

    • Smart manufacturing
    • Connected assets and preventive and predictive maintenance
    • Smart power grids
    • Smart cities
    • Connected logistics
    • Smart digital supply chains
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    What are IoT applications?

    Business-ready, SaaS IoT Applications

    IoT Intelligent Applications are prebuilt software-as-a-service (SaaS) applications that can analyze and present captured IoT sensor data to business users via dashboards. 

    IoT applications use machine learning algorithms to analyze massive amounts of connected sensor data in the cloud. Using real-time IoT dashboards and alerts, you gain visibility into key performance indicators, statistics for mean time between failures, and other information. Machine learning–based algorithms can identify equipment anomalies and send alerts to users and even trigger automated fixes or proactive counter measures.

    With cloud-based IoT applications, business users can quickly enhance existing processes for supply chains, customer service, human resources, and financial services. There’s no need to recreate entire business processes.

    What are some ways IoT applications are deployed?

    The ability of IoT to provide sensor information as well as enable device-to-device communication is driving a broad set of applications. The following are some of the most popular applications and what they do.

    Create new efficiencies in manufacturing through machine monitoring and product-quality monitoring.

    Machines can be continuously monitored and analyzed to make sure they are performing within required tolerances. Products can also be monitored in real time to identify and address quality defects.

    Improve the tracking and “ring-fencing” of physical assets.

    Tracking enables businesses to quickly determine asset location. Ring-fencing allows them to make sure that high-value assets are protected from theft and removal.

    Use wearables to monitor human health analytics and environmental conditions.

    IoT wearables enable people to better understand their own health and allow physicians to remotely monitor patients. This technology also enables companies to track the health and safety of their employees, which is especially useful for workers employed in hazardous conditions.

    Drive efficiencies and new possibilities in existing processes.

    One example of this is the use of IoT to increase efficiency and safety in connected logistics for fleet management. Companies can use IoT fleet monitoring to direct trucks, in real time, to improve efficiency.

    Enable business process changes.

    An example of this is the use of IoT devices for connected assets to monitor the health of remote machines and trigger service calls for preventive maintenance. The ability to remotely monitor machines is also enabling new product-as-a-service business models, where customers no longer need to buy a product but instead pay for its usage.

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    What industries can benefit from IoT?

    Organizations best suited for IoT are those that would benefit from using sensor devices in their business processes.

    Manufacturing

    Manufacturers can gain a competitive advantage by using production-line monitoring to enable proactive maintenance on equipment when sensors detect an impending failure. Sensors can actually measure when production output is compromised. With the help of sensor alerts, manufacturers can quickly check equipment for accuracy or remove it from production until it is repaired. This allows companies to reduce operating costs, get better uptime, and improve asset performance management.

    Automotive

    The automotive industry stands to realize significant advantages from the use of IoT applications. In addition to the benefits of applying IoT to production lines, sensors can detect impending equipment failure in vehicles already on the road and can alert the driver with details and recommendations. Thanks to aggregated information gathered by IoT-based applications, automotive manufacturers and suppliers can learn more about how to keep cars running and car owners informed.

    Transportation and Logistics

    Transportation and logistical systems benefit from a variety of IoT applications. Fleets of cars, trucks, ships, and trains that carry inventory can be rerouted based on weather conditions, vehicle availability, or driver availability, thanks to IoT sensor data. The inventory itself could also be equipped with sensors for track-and-trace and temperature-control monitoring. The food and beverage, flower, and pharmaceutical industries often carry temperature-sensitive inventory that would benefit greatly from IoT monitoring applications that send alerts when temperatures rise or fall to a level that threatens the product.

    Retail

    IoT applications allow retail companies to manage inventory, improve customer experience, optimize supply chain, and reduce operational costs. For example, smart shelves fitted with weight sensors can collect RFID-based information and send the data to the IoT platform to automatically monitor inventory and trigger alerts if items are running low. Beacons can push targeted offers and promotions to customers to provide an engaging experience.

    Public Sector

    The benefits of IoT in the public sector and other service-related environments are similarly wide-ranging. For example, government-owned utilities can use IoT-based applications to notify their users of mass outages and even of smaller interruptions of water, power, or sewer services. IoT applications can collect data concerning the scope of an outage and deploy resources to help utilities recover from outages with greater speed.

    Healthcare

    IoT asset monitoring provides multiple benefits to the healthcare industry. Doctors, nurses, and orderlies often need to know the exact location of patient-assistance assets such as wheelchairs. When a hospital’s wheelchairs are equipped with IoT sensors, they can be tracked from the IoT asset-monitoring application so that anyone looking for one can quickly find the nearest available wheelchair. Many hospital assets can be tracked this way to ensure proper usage as well as financial accounting for the physical assets in each department.

    General Safety Across All Industries

    In addition to tracking physical assets, IoT can be used to improve worker safety. Employees in hazardous environments such as mines, oil and gas fields, and chemical and power plants, for example, need to know about the occurrence of a hazardous event that might affect them. When they are connected to IoT sensor–based applications, they can be notified of accidents or rescued from them as swiftly as possible. IoT applications are also used for wearables that can monitor human health and environmental conditions. Not only do these types of applications help people better understand their own health, they also permit physicians to monitor patients remotely.

    trends

    How is IoT changing the world? Take a look at connected cars.

    IoT is reinventing the automobile by enabling connected cars. With IoT, car owners can operate their cars remotely—by, for example, preheating the car before the driver gets in it or by remotely summoning a car by phone. Given IoT’s ability to enable device-to-device communication, cars will even be able to book their own service appointments when warranted.

    The connected car allows car manufacturers or dealers to turn the car ownership model on its head. Previously, manufacturers have had an arms-length relationship with individual buyers (or none at all). Essentially, the manufacturer’s relationship with the car ended once it was sent to the dealer. With connected cars, automobile makers or dealers can have a continuous relationship with their customers. Instead of selling cars, they can charge drivers usage fees, offering a “transportation-as-a-service” using autonomous cars. IoT allows manufacturers to upgrade their cars continuously with new software, a sea-change difference from the traditional model of car ownership in which vehicles immediately depreciate in performance and value.

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  • How Can Blockchain And Digital Payments Reinvent The Internet Of Things?

    How Can Blockchain And Digital Payments Reinvent The Internet Of Things?

     

    The convergence of artificial intelligence, blockchain, cloud computing, edge computing, Internet of Things (IoT), 5G, computer vision and augmented/virtual reality is taking society on a journey through the next wave of the digital revolution and toward the metaverse.

     

    As one of the key enablers of the metaverse, IoT has reshaped our lives in significant ways with a myriad of applications, including smart homes, smart manufacturing, smart healthcare and intelligent transportation systems. Billions of connected devices have generated massive amounts of data that tech giants analyzed to extract valuable insight for their businesses.

     

    However, the IoT industry presently possesses several limitations that restrict the sustainable growth of IoT ecosystems. Can blockchain and cryptocurrency help tackle industry-wide challenges and take IoT to the next level?

     
     

    Internet of Things: The Status Quo

    Today, a typical IoT application is still primarily centralized. An IoT company distributes smart devices to its customers and builds the entire solution that often includes various components.

    These include identity management, device management, connectivity gateway, data storage, digital twin, data visualization and others, all on a preferred cloud platform. Centralized IoT system architecture was developed to deliver incredible value to customers, but it comes with five key disadvantages:

     

    • Single point of failure: An IoT solution deployed as a centralized solution is subject to a single point of failure. Although cloud service providers have made efforts to improve the scalability, reliability and availability of their platforms, cloud platforms still experience service outages from time to time, leaving customers with smart devices in the lurch.

    • Ownership of devices and data: Users who purchase IoT devices do not truly own their devices or data that’s collected. The lifecycle of smart devices is often fully managed by IoT companies, and it is quite difficult, if not impossible, for users to repurpose their devices for other applications. Moreover, IoT companies have extensively used data collected by smart devices, creating new value in businesses without compensating their customers.

    • Application and data silos: Most IoT solutions deployed on a centralized platform are self-contained, thereby forming application and data silos. Those silos hinder the value exchange between different IoT systems and result in the loss of new business opportunities.

    • Misalignment of values: IoT ecosystems consist of multiple stakeholders, such as device manufacturers/OEMs, network operators, platform providers, service providers, end-users, etc. The centralized IoT architecture enables platform and service providers to maximize their shares of the value chain revenue, whereas the profit margins for device manufacturers/OEMs are quite slim. In addition, end-users are excluded from the centralized IoT value chain.

    • Barriers to innovation: The application and data silos, coupled with rigid business models, create barriers to continuous innovation in IoT. It slows down technology adoption and ecosystem growth.

    Internet of Things: A New Dawn

    The introduction of blockchain and cryptocurrency has shed light on a new community-driven machine economy called MachineFi. The innovative combination of blockchain, cryptocurrency and IoT provides effective solutions to address challenges that the IoT industry is facing.

    • High availability and security: The decentralized nature of blockchain implies that applications running on top of it can achieve high availability and security. As a result, IoT companies could leverage blockchain to deploy the critical components of their solutions, thereby reducing service downtime and enhancing system trustworthiness.

    • User-owned device and data: By applying the emerging concepts such as decentralized identifiers (DIDs) and verifiable credentials (VCs) to build a self-sovereign identity metasystem for people, organizations and IoT devices, users can gain control over data collected by their smart devices and decide how it’s shared.

    • Interoperable applications and data: Using blockchain as the underlying fabric can connect different IoT applications, enabling them to exchange digital assets in a transparent and trustworthy manner. In particular, large-scale decentralized and autonomous IoT applications can be built upon individual applications by leveraging interoperable data.

    • Fair distribution of values: Cryptocurrencies and associated token economy models provide powerful tools for incentivizing all the stakeholders in IoT ecosystems. Aligning the stakeholders’ benefits in a fair and consistent manner is the main force for transforming the IoT industry and forming the flywheel effect.

    • Endless innovation: By combining IoT with the value exchange layer powered by DeFi, NFTs and DAOs, the IoT industry is able to create new business models and build a wide range of community-driven, machine-centric applications. Such digital transformation will bring endless innovation opportunities to IoT ecosystems.

    MachineFi represents a paradigm shift in the way IoT systems are designed and monetized. It considers all of the stakeholders in an ecosystem and incentivizes them to move the value-creation flywheel continuously. The exciting future of an IoT for all of us is no longer a dream. It’s a reality.

    Xinxin Fan

    Dr. Xinxin Fan is the Head of Cryptography at IoTeX, a startup empowering the future machine economy with blockchain and IoT.

  • Why multiple identities are closer than you think

    Why multiple identities are closer than you think

    Identities are complex to form, hard to define and increasingly easier to steal and fake. Author Tracey Follows explains how will we define ourselves and what happens to our legacy identities as they drift through time and space?
    Why multiple identities are closer than you think | What the Future: Identity
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    Identity issue

    The central question of this issue is how we will shape our identities in virtual spaces. Futurist Tracey Follows tackled this in her new book, “The Future of You.” While there are certainly questions that will still be answered over the coming decade, she offers some hints about what the future will hold. 

    Matt Carmichael: How do we create our identities online today? 

    Tracey Follows: It’s somewhat of an elusive concept but then I don’t go along with the people who say that it’s just an illusory concept. Because you have to know who someone’s identity is because you have to ascribe rights and duties and responsibilities and even emotions to a specific person. And that person has to have some continuity. In the past we would’ve said it was continuity over time, but now we’re saying it’s continuity over space. 

    Carmichael: What do you mean by that? 

    Follows: Are you the same person in real life as you are in these online worlds? Partially it depends on your philosophical take. It depends what culture you’ve grown up with? For some people and some groups, it’s a very tribal thing and your identity’s conferred on you by the group that you want to belong to. For Buddhists, the identity is something that is arrived at, towards the end of life because it’s the summation of every single interaction you’ve had with every single person.

    Carmichael: How do you see this changing as we have identities now in more virtual spaces? 

    Follows: We will have much more fluid identities because we’ll be in more fluid spaces. But then I see the counter trend which is the authorities or institutions needing to reclaim back or to manage these fluid identities with centrally organized, biometrically underpinned identity systems.

    Carmichael: How do we keep control of our identity and our biometrics like our face, our fingerprints? 

    Follows: It’s a vigilance on behalf of every single citizen. We have to stop thinking of ourselves just as consumers or users of these technology products and understand that we are citizens and that we have some digital rights. 

    Carmichael: There’s a way in which this could allow people to be their more authentic selves in a safer space than would necessarily be in the real world. Then there’s a clear counter to that where it becomes even more toxic in the online world than it is in the real world.

    Follows: It will be interesting to watch is how different virtual reality and virtual media is from social media. I’m sure you know the Marshall McLuhan quote, “All forms of violence are quests for identity.” We see a lot of aggression and antagonistic behavior on social media, it’s because people are fighting to get their identity represented. When we have sensory capabilities in virtual media, I think then we’ll get a proper representation. I think it will be less antagonistic than we find social media right now and more empathetic. 

    Carmichael: How many identities will you have in these sorts of worlds? 

    Follows: We are used to having one authentic identity physicality because we’re embodied in this physical body, but we won’t have that. We could have many different identities in the metaverse or whatever you call it. That means that you could end up meeting up with yourselves. And I think that’s the most interesting thing that you can bend time and space so that you don’t have to be just one person living a very linear life. One could meet up with different versions of one self at different ages lifestyle ages, perhaps you could meet up with your younger self or older self, you know, all of these things could be possible and that will really give us a completely different sense of reality. 

    Carmichael: How do you build trust in those communities if you don’t really know who you’re interacting with and if it’s really them? 

    Follows: Eric Schmidt has suggested that we’ll all have of AI assistants who are very good at detecting what’s authentic and what’s not. Sort of an AI detective on your shoulder trying to work out the digital forensics. I’m not entirely sure people want to live like that. I don’t see it as this huge, unfettered progress. People will stop doing certain things and decide, oh no, we want much more human contact again. It’ll be cyclical. Then they’ll come back to doing much socializing or work in the virtual environment. 

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    WHAT THE FUTURE: IDENTITY

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  • How To Use Metaverse Technology To Design A Better Real World

    How To Use Metaverse Technology To Design A Better Real World

     

    Design thinking, a method that puts people and empathy at the center of new product development, has swept from consultancies like IDEO and Frog to nearly every corporate innovation group. Design thinking starts with ethnographic research and insights, then uses prototypes and resonance testing to iterate towards more successful user-centered products. This process is now the gold standard in modern product development. But rather than selling more products, what if the goal is to solve large-scale social problems? How can we enlist metaverse technologies like AI, computer vision, augmented reality, and spatial computing on these meaningful issues? 

     

    Metaverse technologies’ incredible potential should be applied beyond avatar chat rooms and virtual property pyramid schemes– They should be put to work to do so much more.

     

    There are many programs to learn design thinking, coding, or 3D modeling and animation in the service of producing first-person shooters, but only one academic program in the world that makes solving a United Nations Sustainable Development Goals a central requirement for every student project. The Copenhagen Institute of Interaction Design takes the United Nations’  collection of 17 interlinked global goals designed to be a “blueprint to achieve a better and more sustainable future for all” as a core tenet of their teachings.

     

    In January I was invited by co-founders Simona Maschi and Alie Rose, to teach a week-long SuperSight workshop in Costa Rica, focusing on computer vision and augmented reality to envision a better world. “The SDGs are backed up by the most extensive market research in history: they tell us where the needs are at the planetary level. If there are needs there are markets to be created. The great responsibility for design teachers and students is to accelerate the transition towards sustainable products and services that are regenerative and circular. In this process nature can be a mentor teaching us about eco-systems and circularity.” To prepare students for the challenges ahead, the CIID curriculum includes biomimicry and immersive learning sessions in the jungle of Costa Rica. 

     

    So to Costa Rica we went. Over the course of the week, my co-instructor Chris McRobbie and I showed some of our AR projects, introduced foundational concepts, design principles, and riffed on the vast potential for the metaverse. The students made things: they used the latest machine learning algorithms built into SNAP lenses and the SNAP Lens Studio tool, then used Apple’s Reality Composer to make a series of augmented reality prototypes. Let me show you what they made, and WHY:

     

    Manali and Jen created an AR tool to replace all the statues of old white men in San Jose with inspirational women. Why? For a kid who passes these landmarks every day ambiently learning about their world, “there are a lot of women who deserve to be recognized more.” The student video is here: 

     

    Jose, Pablo, and Priscilla used computer vision to blur product packages in the grocery store that are unsustainable. This diminished reality application stears shoppers toward buying products in packaging that’s better for the environment. 

    Lisa and Karla created a gamified stretching experience to motivate some movement between all those zoom meetings.

    Mia and Vicky used computer vision for an application that is central to so many families and drives a lot of social interaction–pet ownership. Automatic human face recognition remains a fraught topic, but this team used pet-recognition which is much less controversial. The concept helps strangers learn if a dog is friendly, get some ideas for good conversations with the owner, and safely return them home if they are lost.

    The most controversial project was from Sofi and Dee, who created a smart glasses app for women to discreetly tag creepy men. Other women see the augmented marks if they choose–a kind of an inverse scarlet letter. 

    In last years’ CIID program, Arvind Sanjeev, envisioned a new way to create shared ad-hoc metaverse experiences with an AR flashlight called LUMEN. It has a computer vision system on the front and a bright laser projector to show information anywhere you shine its beam. LUMEN is great for groups of people to peer into the metaverse together. For example, point the beam on a wall to see where electrical conduits run, or onto a body to see the underlying skeletal structure and learn about a knee or shoulder implant. After graduation, Arvind joined forces with Can Yanardag and Matt Visco to develop Lumen into a real venture/platform. The transparent body X-ray effects are so compelling I’m showing LUMEN to orthopedic surgeons and physical therapists at the Healthcare Summit in Jackson Hole this week. 

     

    Run a metaverse envisioning workshop for your company this year. 

    There are now so many accessible immersive computer prototyping tools like Apple Reality Composer, Adobe Aero, and Snap Lens studio to help your team start experimenting. Even a one-day workshop with a skilled facilitator can help your team ask important questions and start to sketch some ideas to prototype. I often bring in an illustrator or storyboard artist to capture ideas from a good strategic discussion, then hire a game studio to create a fast 3D interactive “sketch” to envision the most promising concepts that come out of a workshop. Building things is a blast. Teams are engaged, learn about the potential of the new medium, and there’s enormous pride that “we made this!”

    Tangible prototypes communicate ideas incredibly effectively around the organization.

    The metaverses are coming; start sketching experiences for these new worlds.

    Each metaverse will have its own technology, privacy policy, business model, and architecture—isolationist or open. Zuckerberg’s vision will be very different than Google’s, Microsoft’s, Apple’s, Amazon’s, MagicLeap’s, UnReal’s or Nvidia’s. Niantic is pursuing a metaverse that augments the world with digital game layers to encourage people to get outside—the real-world metaverse is the one I’m most excited to design and develop.

    The key is to get your team to start driving the metaverse-building engines, as my workshop students did. A link to the best prototyping tools is on SuperSight.world. Sketch some experiences: How might this technology change how you collaborate at a distance, learn in context, configure and sell products, envision the future? Becoming fluent in these tools for rapid prototyping and remote work is imperative to stay agile, competitive, and creative.

    David Rose
     
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Virtual Identity