Smart Glasses....

Smart glasses are wearable devices that display real-time information directly in front of users’ field of vision by using Augmented Reality (AR) techniques. Generally, they can also perform more complex tasks, run some applications, and support Internet connectivity. This paper provides an overview of some methods that can be adopted to allow gesture-based interaction with smart glasses, as well as of some interaction design considerations. Additionally, it discusses some social effects induced by a wide-spread deployment of smart glasses as well as possible privacy concerns.

Head-worn displays (HWD) have recently gained significant attention, in particular thanks to the release of a temporary version of Google Glass. Moreover, the anticipation of the commercial launch of Google Glass1 in the upcoming months and the fresh news that Facebook, Inc. acquired Oculus Rift2 increased the popularity of such devices even further. The trend of wearable device purchases is importantly growing and some business analysts forecast more than 20 million annual sales of Google Glass in 2018. Furthermore, researchers have been already studying and investigating HWD for several years. As a consequence, it is important to give an overview of different methods that could be used to interact with smart glasses and, above all, analysing privacy concerns and identifying the current and potential social implications related to these devices has a great significance at this point.

The main purpose of smart glasses is to provide users with information and services relevant for their contexts and useful for the users to perform their tasks; in other words, such devices augment users’ senses. In addition, they allow users to do basic operations available on today common mobile devices such as reading, writing e-mails, writing text messages, making notes, and answering calls. Therefore, although most of the usage of smart glasses is passive for the users, i.e. reading content on the little screen of the device, active interaction with such devices is fundamental to control them and supply inputs. In fact, users need ways to ask smart glasses for instance to open a particular application, answer something they need to know, insert content for emails, messages or input fields, or to control games

Interaction approaches

Two different categories of interaction methods can be distinguished for smart glasses: free form and others. The former includes for example eye tracking, wink detection, voice commands, and gestures performed with fingers or hands. On the other hand, the latter comprises for instance the use of hand-held devices, e.g. point-and-click controllers, joysticks, one-hand keyboards and smartphones, or smart watches to control the HWD. The aforementioned examples should help to understand the difference between the two kinds of interaction. However, it can be expressed by saying that the free form does not require any extra device other than the smart glass to be performed and detected; on the contrary, it is obvious how the control of the smart glass that happens via smartphones, pointer, etc. cannot satisfy the free form criterion.

GESTURE-BASED INTERACTION

Thereinafter, we will only focus on gesture-basted interaction, because it is preferable to assure a great user experience. Gesture-based interaction has been researched more than eye tracking and wink detection so far, and voice recognition has already reached a huge diffusion on today mobile devices. It is relevant to note that several different techniques to detect gestures exist; analysing them in detail would lead us to stray from the purpose of this paper. Some of them make use of devices and sensors that have to be tied to users’ body, e.g. to wrists, hands or fingers, whereas others exploit cameras that are external to the smart glass itself and are located around the user. In addition, some of these methods are used together with markers, e.g. reflective, infrared, coloured, in order to identify the position of users’ hands. Alternatively, gestures can be recognized by using cameras or sensors, such as RGB or 3D cameras and depth sensors, that can be embedded into smart glasses. It is essential to stress that real free forms of interaction are realized only by using cameras or sensors embedded into the HWD as they nullify the need of external components and reduce the encumbrance. As a consequence, these approaches are ideal for the commercial version of the smart glasses that will be launched on the market. Differently, the other recognition techniques that have been classified as non-free forms are usually used in research for several studies in this context.

Gestures on body/smart glass

Another significant distinction applicable to gestures is based on where the gesture is performed. A common solution is doing gestures very close to or directly on some surfaces such as some parts of the smart glass itself or the user’s body. The following paragraphs present two different studies that have investigated this approach.

Hand-to-face input

Serrano et al. describe their study aimed at identifying which gestures and surfaces allow fast interaction with as little effort as possible. As regards the surface, they considered and compared the results about some parts of both the smart glass and the user’s face. In particular, the face has been chosen since it is a part of the body we interact with very often, i.e. 15.7 times/hour in a working set; consequently, this means that gestures performed on some parts of the face could be less intrusive than others and may reach a good level of acceptance. On the other hand, the high frequency of hand-face contacts leads to the need of gesture delimiters used by the users to inform the system that a new gesture is starting and avoid unintentional triggers; for instance, voice commands or long pressing on the surface can be used to invoke new gestures. The need to find an alternative to performing gestures directly on the smart glass itself arises from the fact that the touchable area available for interaction on such devices is usually only a narrow strip in correspondence to the user’s temple; in fact, this means that many gestures are needed to browse some pages or applications that require a lot of panning and zooming due to the very small size of the interaction surface. As a result, the time taken to reach a target in a page is negatively affected as well as the armshoulder fatigue is significant because of the prolonged lifting.

Palm-based imaginary interfaces

The purpose of this second study is to identify and quantify the role of visual and tactile cues when browsing imaginary interfaces . Specifically, imaginary interfaces can be defined as spatial and non-visual interfaces for mobile devices and, in this particular case, they consist of matching between some application to be opened or actions to be triggered and some parts of the user’s hand (see figure 3). This approach is very useful to impaired users and eye-free interaction with smart glasses and, above all, is less intrusive and tiring than hand-to-face and hand-to-HWD interaction.

Figure 4 shows the four study conditions investigated in this study. The study shows that when not blindfolded (Figure 4a), the grid drawn on the fake phone (Figure 4c) orients users on the screen and helps them to find the targets that were reached faster than on the palm (Figure 4d). Additionally, this experiment proved that, in contrast, touching the palm was faster than touching the fake phone when blindfolded; this has a great importance because it demonstrates that the tactile cues received by the users touching their own palms is very significant. After having found that the tactile cues are relevant, it is interesting to understand how the two different tactile senses, i.e. active and passive, contribute to help users to browse the interface. In particular, the active sense is perceived by the finger that actively touches the palm, whereas the passive one is sensed by the palm when touched by the finger.

Hi-Fi

Definition of Hi-Fi

Hi-Fi paper presents a sufficiently low bit rate Hi-Fi audio coding technique with low computation designed for transmitting real-time high-quality audio signal over wireless channel. This technique applies wavelet packet transform to decompose audio signal into subbands to eliminate redundant data using spectral and temporal masking properties. The encoded audio data is framed with some critical field is protected by channel coding to improve noise immunity when frames are transmitted wirelessly. Experimental results show that transparent CD-audio quality can be achieved at 80kbps encoding bit rate. Moreover, the proposed technique still offers near CD-audio quality when frames are transmitted over AWGN channel with BER below 10-5. These encouraging results clearly exhibit the superior features of our technique compared to others such as Ogg/Vorbis and MP3, which are ubiquitously employed nowadays.

Current hi-fi audio CODECs employ entropy coding such as run-length and Huffman code, where important parameters required to decode are assumed to be error−free. Otherwise, the frame will be discarded making it susceptible to noisy wireless channel. As a result, we identify such parameters and protect them using channel coding that can correct up to 29 bits (one of every seven bits). Perceptual coding technique is used reduce the bit rate based on “human hearing masking” property. In general, perceptual codec consists of five modules which are filer bank, psychoacoustic analyzer, bit allocation, quantizing and encoding, and framing.

The output from filter bank (time/frequency analysis) is quantized according to masking thresholds calculated by the psychoacoustic analyzer. In [1,2] use polyphase filter bank which requires 512 coefficients to represent each filter. This can take significant time to encode the signal. In contrast, we use wavelet−based filter bank to transform signal into wavelet domain that analyzes both time and frequency simultaneously. The filter bank uses fewer coefficients and can represent variable sized subbands that more accurately match the characteristic of non−stationary audio signal [7]; human can only detect frequency difference at low− or medium−frequency. This hypothesis leads us to believe that the proposed technique should be simpler (can be implemented in hardware). Moreover, MATLAB experiments confirm that, at 80kbps, our wavelet−packet audio codec yields comparable audio quality to that of the 64kbps MP3 and Ogg/Vorbis. It is worth noting that the higher bit rate of wavelet codec partially accounts for channel coding. This makes it wireless transmission ready.

Wavelet-packet Audio CODEC

This section explains structure and function of the proposed wavelet−packet codec which takes audio CD samples (44.1ksps @ 16bps PCM) as its inputs. Audio samples are framed at 1,024 samples each [7]. Fewer samples would affect the coding efficiency whereas more samples would impose long coding delay, violating the real−time requirement. Subsequent frames share 16 overlapping samples to reduce discontinuity between reconstructed frames at the decoder. Each frame is windowed by raised cosine filter to avoid sudden change of the signal [7] then proceeds to the encoder

Li-Fi Technology...

Li-Fi Technology.......

Introduction of Li-Fi Technology

In simple terms, Li-Fi can be thought of as a light-based Wi-Fi. That is, it uses light instead of radio waves to transmit information. And instead of Wi-Fi modems, Li-Fi would use transceiver-fitted LED lamps that can light a room as well as transmit and receive information. Since simple light bulbs are used, there can technically be any number of access points.
This technology uses a part of the electromagnetic spectrum that is still not greatly utilized- The Visible Spectrum. Light is in fact very much part of our lives for millions and millions of years and does not have any major ill effect. Moreover there is 10,000 times more space available in this spectrum and just counting on the bulbs in use, it also multiplies to 10,000 times more availability as an infrastructure, globally.
It is possible to encode data in the light by varying the rate at which the LEDs flicker on and off to give different strings of 1s and 0s. The LED intensity is modulated so rapidly that human eyes cannot notice, so the output appears constant.
More sophisticated techniques could dramatically increase VLC data rates. Teams at the University of Oxford and the University of Edinburgh are focusing on parallel data transmission using arrays of LEDs, where each LED transmits a different data stream. Other groups are using mixtures of red, green and blue LEDs to alter the light's frequency, with each frequency encoding a different data channel.
Li-Fi, as it has been dubbed, has already achieved blisteringly high speeds in the lab. Researchers at the Heinrich Hertz Institute in Berlin, Germany, have reached data rates of over 500 megabytes per second using a standard white-light LED. Haas has set up a spin-off firm to sell a consumer VLC transmitter that is due for launch next year. It is capable of transmitting data at 100 MB/s - faster than most UK broadband connections.

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Genesis of LI-FI:

Harald Haas, a professor at the University of Edinburgh who began his research in the field in 2004, gave a debut demonstration of what he called a Li-Fi prototype at the TEDGlobal conference in Edinburgh on 12th July 2011. He used a table lamp with an LED bulb to transmit a video of blooming flowers that was then projected onto a screen behind him. During the event he periodically blocked the light from lamp to prove that the lamp was indeed the source of incoming data. At TEDGlobal, Haas demonstrated a data rate of transmission of around 10Mbps -- comparable to a fairly good UK broadband connection. Two months later he achieved 123Mbps.

How Li-Fi Works?

Li-Fi is typically implemented using white LED light bulbs at the downlink transmitter. These devices are normally used for illumination only by applying a constant current. However, by fast and subtle variations of the current, the optical output can be made to vary at extremely high speeds. This very property of optical current is used in Li-Fi setup. The operational procedure is very simple-, if the LED is on, you transmit a digital 1, if it’s off you transmit a 0. The LEDs can be switched on and off very quickly, which gives nice opportunities for transmitting data. Hence all that is required is some LEDs and a controller that code data into those LEDs. All one has to do is to vary the rate at which the LED’s flicker depending upon the data we want to encode. Further enhancements can be made in this method, like using an array of LEDs for parallel data transmission, or using mixtures of red, green and blue LEDs to alter the light’s frequency with each frequency encoding a different data channel. Such advancements promise a theoretical speed of 10 Gbps – meaning one can download a full high-definition film in just 30 seconds.

To further get a grasp of Li-Fi consider an IR remote. It sends a single data stream of bits at the rate of 10,000-20,000 bps. Now replace the IR LED with a Light Box containing a large LED array. This system is capable of sending thousands of such streams at very fast rate.