​Augmented Reality (AR) is the enhanced version of reality where live direct or indirect views of physical real-world environments are augmented with superimposed computer-generated images over a user's view of the real-world. In other words, AR is the integration of digital information with the user’s environment in real time.

It is common for people to confuse it with Virtual Reality (VR), but AR uses an already existing natural environment and superimposes on top of it. Users of AR experience a new and improved natural world with the interaction of virtual information which provides different interactive options. On the other hand, VR creates a totally new artificial  environment.

Even if the technology, apparently, is perfect for leisure and enjoyment, the truth is that AR is becoming very useful in many other industries such as healthcare, public sector, tourism, marketing, etc.

Augmented Reality embraces different type of technologies. All of them have different own use cases:

• Marker Based Augmented Reality: using a camera and a visual marker, some results are obtained when a reader senses a marker (ex: QR Code). This is the simplest AR technology as it does not need much power to process.
• Marker-less Augmented Reality: this kind of AR uses GPS, digital compass, velocity meter or other type of sensors to provide data on location. This is mostly used for mapping, locating directions or businesses...
• Projection Based Augmented Reality: it projects artificial light onto real world surfaces. It is used mostly to overlap holograms.
• Superimposition Based Augmented Reality: it replaces the original object with a newly augmented view of that object. It is very useful for commercial uses.

There are some components required for AR devices: sensors, cameras, projectors, processors and reflection machines.

As mentioned above, there are many different types of applications of Augmented Reality in different use cases. Below are some use cases and providers:

• Google glass
• XºVito Technology's Star Walk
• Layar
• Augmented Reality for IOS
• Ikea augmented reality furniture catalog
• Microsoft Kinect for Xbox
• Vuforia
• Roar
• Eon Reality
• Plattar
• ViewAR
• Augment
• Apple AR Kit 

There are many international standards for the application of the Augmented Reality in multiple sectors. Some of the most relevant ones:

• IEEE P802.15.8 - Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Peer Aware Communications (PAC)
• IEEE P1278.2 - Draft Standard for Distributed Interactive Simulation - Communication Services and Profiles
• IEEE P1484.11.1 - Draft Standard for Learning Technology--Data Model for Content Object Communication
• IEEE P1589 - Standard for an Augmented Reality Learning Experience Model
• IEEE P2048.1 - Standard for Virtual Reality and Augmented Reality: Device Taxonomy and Definitions
• IEEE P2048.2 - Standard for Virtual Reality and Augmented Reality: Immersive Video Taxonomy and Quality Metrics
• IEEE P2048.3 - Standard for Virtual Reality and Augmented Reality: Immersive Video File and Stream Formats
• IEEE P2048.4 - Standard for Virtual Reality and Augmented Reality: Person Identity
• IEEE P2048.5 - Standard for Virtual Reality and Augmented Reality: Environment Safety
• IEEE P2200 - Draft Standard Protocol for Stream Management in Media Client Devices
• IEEE P3333.1.2 - Standard for the Perceptual Quality Assessment of Three Dimensional (3D) and Ultra High Definition (UHD) Contents
• IEEE 802.1AB-2009 - IEEE Standard for Local and metropolitan area networks -- Station and Media Access Control Connectivity Discovery
• IEEE 802.1AE-2006 - IEEE Standard for Local and Metropolitan Area Networks: Media Access Control (MAC) Security
• IEEE 802.1AX-2008 - IEEE Standard for Local and Metropolitan Area Networks - Link Aggregation*
• IEEE 802.1AR-2009 - IEEE Standard for Local and Metropolitan Area Networks - Secure Device Identity
• ISO/IEC 23000-13:2017 Information technology - Multimedia application format (MPEG-A) - Part 13: Augmented reality application format
• ISO 9241-940:2017 Ergonomics of human-system interaction -- Part 940: Evaluation of tactile and haptic interactions

For a more exhaustive list with standards, read here.

Augmented Reality is a very new technology that is still working in setting standards. Especially the IEEE Standards Association is working on new standards for virtual and augmented realities, with a working group establishing categories for devices. Standards related to video quality, user interfaces, and file formats. Even if there are already a great number of projects and standards identified, more will be discussed due to the different sectors able to apply them.
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Some of the standards under development are:

• ISO/IEC DIS 18039 Information technology -- Mixed and augmented reality (MAR) reference model
• ISO/IEC AWI 21858 Information model for mixed and augmented reality (MAR) contents
• ISO/IEC DIS 18040 Information technology -- Computer graphics, image processing, and environmental data representation -- Live actor and entity representation in mixed and augmented reality (MAR)
• ISO/IEC DIS 18520 Information technology -- Computer graphics, image processing, and environmental data representation -- Benchmarking of vision-based spatial registration and tracking methods for mixed and augmented reality (MAR)
• ISO/IEC CD 18038 Information technology -- Computer graphics, image processing, and environmental data representation and coding of audio, picture, multimedia, and hypermedia information -- Sensor representation in mixed and augmented reality (MAR)

Augmented Reality has an enormous potential in most of the sectors. Some of the potential uses are:

• Healthcare: probably one of the most benefitted sectors thanks to the AR. It will help to improve complicate medical procedures. It will also help for the training of non-expert surgeons and students.
• Education: it will allow students to be trained in the simulation of real environments accelerating the learning process.
• Recruitment: new recruiting techniques imply the use of new technologies like VR and AR.
• Reality glasses for people with any visual impairment to help them with daily life difficulties.
• Reparation and maintenance of machines.
• Ecommerce: previsualization of products.
• Shows and sports visualization: it will provide a better view of what is happening in some fields in which the view is not the best (ex: golf).
• Navigation and location, showing best places or meeting points in 3D.
• Gaming will keep improving and trying to maximize the AR which will help them to provide a more realistic way of gaming.
• Silver Economy: where elder people will be able to recreate some of past moments and will be able to train their cognitive capacities.
• Sales: where sellers will be able to show previously how their product will be produced (Automotive industries for example
• The gaming industry will continue evolving thanks to the application of AR on most platforms.

​Author
KISMC

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This article is a continuation of an article we published in August 2020 - “Disruptive Technologies for Smart Cities – Cloud Computing” for the presentation of the interim results of the ongoing Erasmus+ project Smart technologies by design (Smart by Design). The article is based on the materials produced by the project partners GAIA & DEUSTO.
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Data Analytics is the approach that allows companies to analyse the data they generate in their activity enabling them to draw conclusions that affect their business. Better known as Big Data, companies manage this information in order to adopt strategies that will help them to improve their business turnover. Thus, it helps them improve operational efficiency, customer user experience and also allows them to improve their business models. All these data generated by companies in their activity is one of the concerns they have to face today. They should evaluate the importance of this information, what information they will have to store or even what part of all these data they can sell.
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Data analysis means the translation of information into opportunities for companies to take advantage of all these data (Schneider. 2017). This is why, “Data Analytics” is also called as a translator or business generator, because it allows to explore personalised solutions to carry out your projects. At present, information as services is a business model that is expanding wherein increasingly more businesses are seeking to monetise the information they obtain. According to the International Statistical Institute, businesses that use information will see their productivity increase by 430 billion dollars by 2020 in contrast with those that do not use it.
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Services offered by platforms related to information analysis is growing along with new solutions in terms of storage capacities as well as processing. Some of the platforms that currently exist are as follows:

• Hadoop
• Gridgain
• HPCC
• Storm
• Spark
• Hive
• Kafka
• Flume

​The first standard on big data was published in the end of 2015 by the International Telecommunication Union (ITU), hence, there are already international rules and standards. ITU-T Y.3600: provides requisites, capabilities and use cases of cloud computing based big data (Y.BigDatareqts, 2015).

Big Data when merged with Cloud Computing offers the ability to collect, store, analyse, visualise and handle large amounts of data, which cannot be analysed with traditional technologies (Iglesias. A, 2015).
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When we refer to data analysis, we can differentiate five key applications of such technologies: ​

1. Explore massive data or Big Data management. Information management is assumed to be one of the biggest challenges that the companies will be facing for best decision-making, operations improvement and risk reduction. To obtain a more complete view of customers. The companies have a greater number of information sources about their customers, which they manage to provide better and more personalised services, as well as to predict customer behaviour.

• Increase in security. Such technologies are used in order to prevent attacks by locating anomalies that may occur, by analysing patterns and threats. In this usage type, we can distinguish three applications:

• Improve intelligence and surveillance: with continued real time analysis to find patterns.
• Prevention of attacks: with network traffic analysis to deal with espionage, intrusiveness, cyber attacks…
• Prediction and prevention of cybercrime: by analysing telecommunications and social network data to analyse threats and to act before the criminals.

• Operations Analysis. Helps companies to make operational decisions, increasing their intelligence and efficiency. To do so, they can check the updated information with the different possible systems.
• Increase in data storage. Creation of new data storage structures.

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​The expected evolution is that the data volumes will continue to grow due to the expected increase in the number of networked devices. The future platforms will improve the ways in which data is analysed, while SQL will continue to be the standard, Spark is emerging as a complementary tool which will continue to grow.

New tools will be created to analyse without an analyst, companies such as Microsoft and Salesforce have announced such type of solutions. Programmes such as Kafka and Spark that allow to use these data in real time will also continue to be developed. According to many experts, it is thought that “fast data” and “actionable data” will replace big data. It is also expected that algorithm markets will emerge. Companies will begin to buy algorithms instead of programming them and add their own information (Logicalis, 2016). Although such type of solutions already exist, it is assumed that these will grow multi-fold.
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On the other hand, one of the challenges data analytics platforms will face is privacy, especially since the latest regulations made by the European Commission.
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With regard to standards, The Big Data Value Association (BDVA) is working to define standards of Big Data priorities and interoperability. The association has a team dedicated to this matter (Task Force 6) that, as of today, has already defined a reference model for Big Data.

​A workshop was held in Brussels in June 2017 to collaborate with other standardisation communities to create a roadmap for the harmonisation of Big Data standards. Representations from ETSI, AIOTI WG3, CEN/CENELEC, OASC, ISO/JTC1/WG9, W3C, OneM2M, Industry 4.0, European Commission, PPP based important Big Data projects among others, participated in the event. Follow-up activities took place in 2017 on the side-lines of the ISO IEC JTC1 WG9 Data Reference Architecture meeting held in Dublin.
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Information analysis has a large number of potential applications and areas of use (Marr.B, 2016):

• Continue working in customer segmentation
• Optimisation and understanding of business processes
• Monitoring and optimisation of business processes
• Improve public health systems
• Improve sport yields of citizens
• Improvements in science and innovation
• Optimise the performance of machinery of companies
• Improvement in security and support for the fulfilment of law
• Applications in Smart Cities related solutions
• Finance

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This material is prepared for the needs of Output 1 of the SMART project and is based on the market study conducted by the Cluster Sofia Knowledge City in 2019, supported by some of the members of the SMART project team at that time.

By smart city technologies are meant those technologies that refer to the concept of a smart city, most often these are digital and/or data-based technologies that are applicable in the real conditions of the city and contribute to the city's coping with public problems or challenges. In smart cities, these technologies are used to develop "critical infrastructure" in the following areas: transport, water and waste management, construction, energy, security, education, health, and urban management.
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The following areas of application of these technologies are presented below. All of them are known cumulatively in most of the smart cities around the world, which are at different stages in the process of transformation. This list does not represent all areas of application at all and is only an introduction for a better understanding of the way and reasons for the penetration of these technologies.

• Autonomous vehicles - vehicles equipped with sensors and software to work alone; full self-management capability (level 4) is achieved when human intervention is not expected to take control at any time.
• Bicycle sharing - bicycles for public use, either in docking centers or as freely used, to provide an alternative to riding, public transport, and private bicycle ownership. This option can cover the first mile / last mile segment when public transport does not take a door-to-door journey.
• Car sharing - access to short-term use of cars without full ownership; can be bidirectional (station-based), unidirectional (free-floating), spot-to-spot, or partial.
• Congestion pricing - fees for using a personal car in certain areas, during peak demand, or both.
• Demand-based micro-transit - sharing services with fixed routes, fixed stops, or both, often complementing existing public transit routes. The algorithms use a historical search to determine routes, vehicle size, and travel frequency. May include seat reservation options.
• Payment by digital public transport - digital and contactless payment systems in public transport, which allow prepayment and faster upload. Includes smart cards and mobile payments.
• Electronic call (private and combined) - the real-time ordering of point-to-point transportation via a mobile device. Unified e-ringing involves the dynamic connection of individual journeys with compatible routes to increase vehicle utilization (ie local real-time search optimization).
• Integrated multimodal information - real-time information on price, time, and availability of transport options in many modes.
• Intelligent road signals - improving overall traffic by dynamically optimizing traffic lights and speed limits, leading to higher average road speeds and less frequent stopping and returning. Includes preferential light technology that prioritizes emergency vehicles, public buses, or both.
• Consolidation of the parcel load - online matching of the demand for supplies with the available supply of freight capacity. By making maximum use of vehicles, fewer trucks make more deliveries.
• Predictable maintenance of transport infrastructure - sensory monitoring of the condition of public transport and related infrastructure (such as rails, roads, and bridges) so that predictive maintenance can be performed before accidents and disruptions occur.
• Real-time public transport information - real-time arrival and departure information for modes of public transport, including informal bus systems.
• Real-time road navigation - real-time navigation tools for selecting driving routes, with signals for construction, detours, traffic jams, and accidents. This is especially true for those who drive alone or in a car.
• Smart mailboxes - boxes in a place where people can pick up packages using individual access codes sent to their mobile devices.
• Smart parking - systems that direct drivers directly to the available spaces; may affect demand through variable charges.

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• Leak detection and control - remote monitoring of the condition of the pipes with the help of sensors and control of the pump pressure to reduce or prevent water leakage. Early identification of leaks can lead to follow-up by relevant city departments and utilities.
• Smart irrigation - optimizing irrigation by analysing information such as local weather, soil conditions, plant species, etc. to eliminate unnecessary watering.
• Monitoring of water consumption - feedback (via a mobile application, e-mail, text, etc.) on the water consumption of the occupant in order to raise awareness and reduce consumption. Smart water meters allow utilities to measure consumption remotely, reducing labour costs for a manual meter reading. It also allows for dynamic pricing.
• Water quality monitoring - real-time water quality monitoring (in networks, rivers, oceans, etc.) through signals delivered to the public through channels such as a mobile application, e-mail, text or website. This warns the public to avoid consumption or contact with polluted water and to make cities and utilities follow the problem immediately.
• Digital tracking and payment for waste disposal - digital payment systems according to the volume of generated waste; includes feedback (via mobile app, email, text, etc.) provided to users to raise awareness and reduce waste.
• Optimization of the waste collection route - use of sensors in the waste containers to measure the volume of waste and direct the routes of waste trucks. This application restricts the travel of garbage trucks to bins with a small amount of waste.

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• Building automation systems - systems that optimize the use of energy and water in commercial and public buildings by using sensors and analysis to manually or automatically eliminate inefficiencies. Includes optimized lighting and HVAC, as well as features such as access/security control and parking information.
• Home energy automation systems - optimization of energy consumption from the home by using intelligent thermostats, programmable and remotely controlled electronic devices (smart home), and control of backup electricity.
• Tracking energy consumption in the home - tracking the consumption of electricity in homes with feedback provided to the consumer through a mobile application, e-mail, or text to raise consumer awareness and promote their protection. It also allows utilities to remotely measure electricity use.

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• Supply automation systems - various types of smart grid technologies, including FDIR, M&D, Volt / Var, and substation automation, to optimize energy efficiency and grid stability.
• Dynamic electricity pricing - dynamic adjustment of electricity prices to reduce electricity consumption and reduce electricity generation costs. By reducing peak consumption, cities can reduce the number of power plants that operate during peak hours.
• Intelligent street lamps - connected and equipped with sensors energy-saving street lights (including LED), which optimize brightness and reduce maintenance needs. Smart street lights can be equipped with speakers, shot sensors, and other features to improve functionality

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• Body cameras - audio, video or photographic recording systems commonly used by police officers to record incidents and police operations.
• Crowd management - technology for monitoring and, where necessary, guiding crowds to ensure safety.
• Data-based building inspections - use of data and analysis to focus inspections on the buildings with the highest potential risks (e.g. prioritization of commercial buildings for fire code inspections and homes for lead inspections).
• Disaster Early Warning Systems - technology designed to anticipate and mitigate the effects of natural disasters such as hurricanes, earthquakes, floods and forest fires.
• Emergency response optimization - the use of analyses and technologies to optimize the processing of emergency calls and field operations, such as the strategic deployment of emergency vehicles.
• Shot Detection - Acoustic surveillance technology that includes audio sensors to detect, locate and alert police agencies to real-time shooting incidents.
• Home security systems - security systems that monitor homes and alert users, emergency services, or both, to unusual activity.
• Personal alarm applications - applications that alert you to an emergency by alerting the Emergency Center, loved ones, or both. Devices (such as personal protective equipment, crash detectors, and fall warning systems) can transmit location and voice data.
• Predictable control - the use of big data and analysis (including social media monitoring) to predict more accurately where and when crimes are likely to occur. These systems are used to deploy police patrols and prevent prevention.
• Real-time crime mapping - a technology used by law enforcement to map, visualize and analyse crime incident models. Information gathering and intelligence serves as a management tool for the efficient allocation of resources and accountability among employees.
• Intelligent surveillance - intelligent monitoring to detect anomalies based on visual emissions, including face recognition, intelligent closed-circuit television systems and registration number recognition.

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• Personalized learning - the use of data from students to identify people who need extra attention or resources; the potential for adapting the learning environment for individual students.
• Online retraining programs - lifelong learning opportunities provided in digital format, especially to help people who are unemployed or at risk of becoming unemployed to acquire new skills.
• Local e-career centers - online platforms for publishing open positions and profiles of candidates; can use algorithms to match compatible candidates with available jobs.
• Reduce job search time and increase net new employment.

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• Public health interventions based on maternal and child health data - use of analyses to target highly targeted health interventions for at-risk groups (in this case, identification of pregnant and new mothers to conduct educational campaigns for and postnatal care).
• Public-based health interventions to improve sanitation and hygiene - use of analyses to target highly targeted interventions, such as understanding where to increase rainfall absorption capacity or collecting data on sewage leaks systems.
• Urgent aid alerts - technologies that alert passers-by trained in CPR so that victims of cardiac arrest receive prompt and urgent care.
• Monitoring of infectious diseases - collection, analysis and response to prevent the spread of infectious and epidemic diseases. Includes awareness and vaccination campaigns (eg for HIV / AIDS).
• Integrated patient flow management systems - real-time hardware and software solutions that provide visibility to where patients are in the system to improve hospital operations and coordinate use at the city or multi-site level.
• Lifestyle clothing - portable devices that collect data on lifestyle and activity indicators and inform the user; they can promote exercise or other aspects of a healthy lifestyle.
• Online care search and planning - tools that support the selection of providers and providers with financial and clinical transparency.
• Real-time air quality information - real-time sensors to detect and monitor the presence of air pollution (outdoor, indoor, or both). Individuals can view the information online or on a personal device and decide to change their behaviour accordingly.
• Remote patient monitoring - collection and transmission of patient data for analysis and intervention by the healthcare provider elsewhere (eg monitoring of vital signs or blood sugar). Includes drug adherence technologies that help patients take medications as recommended by their healthcare provider.
• Telemedicine - virtual interaction of the patient and the doctor through audio-visual technology

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• Obtaining licenses and permits for business digitally - a digitalized process (as an online portal) for companies to obtain licenses and permits for operation.
• Digital Tax Submission - a business channel to perform online tax filing.
• Obtaining permits for the use of land and buildings by digital means - digitalization and automation of the application process for permitting the use of land and construction, reducing the time for approval, and increasing transparency.
• Open database for the cadastre - a complete database for the plots in the city, open to the public; allows for a more efficient land market by creating transparency of available land and reducing the cost of registering plots.
• Peer-to-peer accommodation platforms - digital markets where individual owners can list and rent properties for short-term accommodation.
• Digital civil services - digitalization of state administrative services aimed at citizens, such as filing income tax, registering cars or applying for unemployment benefits.
• Local applications of civic engagement - public engagement in urban issues through digital applications. It may include reporting problems and maintenance needs (for example, reporting broken street lamps through an application), providing information on policy decisions, participating in digital urban initiatives (such as open data hackathons), and interacting with city authorities and social services departments. networks,
• Local communication platforms - websites or mobile applications that help people connect and potentially meet other people in their community. It can be used to find people with similar interests and hobbies, to connect with neighbours, etc

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