Hypercontext & Reality Operating System (ROS)

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Hypercontext: A forecast of key trends in the evolution of online services for 2020–2030

Author: Askar Tuganbaev, media expert, 27 October 2013, Этот e-mail адрес защищен от спам-ботов, для его просмотра у Вас должен быть включен Javascript

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Over the past 20 years, the principal commercial task of the Internet (and of other media as well) has been to identify user preferences and generate offline product sales using refined media targeting and contextual advertising. The Internet was used to construct user profiles based on online media usage, communications, and searches. The resulting sociodemographic data was used, together with identified interests, by online and offline commercial entities to drive users to sales channels and generate sales volume.

It is logical to suppose that evolution of the online medium as a commercial engine will continue because it successfully generates sales for each user. This requires a more precise determination of user preferences, both at the global and immediate level. The principal technological drivers here are: (1) a more precise recognition and description of consumed content, parsing it by interest tags, brand tags, and mood-related psychological characteristics of various scenes and their progressions, while eschewing existing global metadata in favor of personal content projections; (2) refinement of the user's location context to a granularity of centimeters of physical location, direction of gaze, and motion of extremities; and (3) real-time biometric measurement of the user's state, i.e., current levels of activity, attention, health, body tone, etc., so as to identify biological states and immediate needs, while building offline consumption and activity profiles.


Location precision. Over the next few years, producers of hardware, software, and online services, as well as service providers, will devote significant effort to improving the precision of metric parameters associated with offline user activity. This will be done to more effectively interact using new interfaces (gesture, voice, gaze) and more precisely engage in context-based interactions that generate offline usage. The user will be transformed from a point particle on a map into a three-dimensional object that interacts with an interface map in closed and open spaces with a readable visual field and object environment.

Biometrics. The determination and real-time transmittal of a user's principal biometric indices—respiration and pulse rate, attention level, body tone, reaction speed, and symptoms of distress—will become important factors that determine day-to-day consumption against a background of an increasingly complex technological environment, an increased scope and speed of continuous data exchange and significant extension of life span, in the face of exponential growth in the quality of the level of consumption (life).

Video recognition. An acute, multifold increase in the number of produced and used video units, resulting from communications channel expansion and an increase in the number of sources (including mobile devices, fixed cameras, vehicles, and eyewear) and the need to perform quick video search and navigation will lead to an unavoidable lack of video metadata and their insufficiency for unambiguous automated processing of video streams on behalf of each individual user. A technology will be required to automatically dissect (parse) video, in real time and faster, so as to identify locations, persons, objects, brands, event types, etc. The data sequence thus obtained may be used to construct meaningful personal media usage, as well as in day-to-day monitoring, control, and information-sharing systems.


Smart clothing. A natural source of refined local spatial user data is his or her clothing, provided appropriate sensors and controllers are incorporated into the clothing. Footwear, outer clothing, and accessories (purses, eyewear, canes, and adornments) may be used to precisely determine the position of the user's extremities and head in a virtual space to keep track of received data while managing interfaces or engaging in interactive media usage or location-related consumption of goods.

Diagnostics. Devices designed to inform the user or remote medical personnel of current body state may emerge as sources of biometric data, as may sports, diet, and other wearable devices used to promote wellness and monitor caloric intake and expenditure.

Augmented reality. Wearable miniature cameras that are built into clothing, eyewear, headgear, vehicles, etc. may be used to obtain, analyze, and augment a user's personal video environment. The resulting video sequence, parsed into its components in real time, will permit optimization of context information, as well as media and product consumption.


Clothing search engine. Currently and over the near term, selection of clothing will be an important aspect of social behavior. However, there are no documented algorithms or schemes for automating the process of selecting clothing for a user. In the professional environment of manufacturers and distributors, however, there exists a hierarchical system of rules for recommending fashions, brands, and models that is based on standard patterns of users and their sociodemographic characteristics. The creation of online systems to search for, select, and recommend clothing with a significant product and marketing offline component will create a comprehensive base for future monitoring of location-related personal data streams generated by clothing.

Branded social behavior. The user's brand selection is a popular tool for personal tagging of his or her social attributes. A personal history of consumed branded products and services permits substantial optimization of recommendations and generation of future consumption. Online game services that gamify links between brands and the user may be used to create such a history, as may loyalty marketing programs and social photo services (such as Pinterest, Instagram, etc.), with the possibility of creating friend links based on complementary personal brand profiles, as well as the development and introduction of a personal reporting system that tracks brands when goods are disposed of.

Gastro-community. Food and culinary art are an important aspect of social behavior and also manifest personal preferences. The creation of a social service around the preparation and consumption of food will permit the accumulation of a large volume of personal data and will optimize the recommendation process. It will also improve user biometric profiles.

Location-related social behavior. User location-related consumption histories are most easily constructed, analyzed, forecast, and generated with the aid of location-related social services that are created to promote social interaction and media and product consumption based on location information from service providers and by gamifying the process of logging usage within the scope of loyalty marketing programs.

Friending of those with similar interests. Future socialization systems will use, as baseline data, not only the information stated by the user and gathered as a result of online media usage (as is currently the case), but they will also—and principally—rely upon the actual offline activities of participants, i.e., their movements, offline product and media consumption, as well as their offline location-related activity and biometric data.

Video recommendations. Using metadata about what is happening on screen, existing recommendation video services are based on consciously organized data, i.e., metadata from producers and aggregators, viewing histories, user data, editing sequences, etc. This method of content selection is poorly suited to an environment where there is an abundant library of offerings, and is of even less utility when using interactively generated, complex metacontent. Thus, it is unlikely that it will be used successfully to navigate an infinite number of video streams generated in real time. In such a situation, it is necessary to be able to identify on-screen locations, persons, and objects (including their commercial characteristics), as well as the nature of video events and other psychophysical aspects of personal perception for each user.

Offline recommendations. Over the next 10–20 years, the volume of data moving between devices and between humans and devices will significantly exceed the traffic used and produced directly by people, while the quantity of simultaneous communications sessions and the volume of data processed for a single user will exceed anyone's physical ability to keep track of them by several factors. Under such conditions, it will be necessary to create location-related forecasting and caching mechanisms for offline user activity to manage surrounding devices and interfaces for media, information, and product use. These will be based on artificial intelligence systems and systems for storing user personal activity data. It will be necessary to create and maintain a Reality Operating System (ROS) to manage and monitor the multiple devices, sensors, and controllers helping to improve the quality of life in the future.


A location-related social system of offline recommendations

In summary, it may be supposed that product manufacturers, service providers, and users will, in the near future, have a need for a social service that provides for the real-time, location-related exchange of media, communications, and recommendation information, with a link to offline activity to stimulate and manage control, entertainment, and consumption. Building such a service will require further development of artificial intelligence technologies, more precise location positioning, video recognition, and biometric monitoring. Additional high-speed, universal-coverage channels will also be required, along with mobile devices exhibiting a new level of efficiency, capable of monitoring biometric data and the surrounding environment in three-dimensions. At the same time, monitoring the location-related mobile use of communications services, positioning, payment systems, etc. assumes strategic importance, since the information system built on such data can not only establish a baseline for commercial interactions for all market participants, but can also become a critical point of vulnerability for the society of the future.

Обновлено 07.03.2014 14:13