SMART SENSOR FOR LABELING

In keeping pace with the fast emerging global trends, we have introduced stickers (self-adhesive) labeling machines, suitable for almost all sizes and types of containers.
The sticker labeling machines are the first of their king in India. The sticker labeling machine eliminates most of the disadvantages of the wet glue labeling machines. The sticker labeling machine are 100% user friendly, virtually maintenance free, do not require any data input/retrieval for label size and coding impression. The sticker labeling machines have built-in no bottle-no label system, production counter and synchronized on-line speed control system. The machines are compatible for any contact coding and inkjet coding system.
The machine settings are easy, and can be made by the operating staff with out much fuss. More over this sticker labeling machines will have speeds ranging from 50 to 400 labels per minute. In the following pages, we are going to describe the methods for proper setting and trouble shooting.
APPLICATIONS:
These can label nearly up to 400 containers per minute.
These sensors are very compact and can be fixed any where, it is of size 200mm-400mm.
These are controlled and sensed by simple photodiodes.
These sensors can label top, bottom, top/bottom, front/back, side and wrap around.
These sensors can label with width 8mm and maximum 90-180mm. These can handle up to outer diameter 400mm max and inner diameter 70/76mm
At last many of the systems were introduced by various companies but we introduce a smart technique for the sensor by which the labeling of the container makes task easier and effective. This smart sensor is very co-friendly and above all since its construction is very simple it is inexpensive. So this labeling sensor will be of very good use to the pharmaceutical industries which manufacture their chemicals and pack them in the containers which are to be labeled.

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CHARACTER RECOGNITION METHODS

1 Template Matching and Correlation Techniques

In 1929 Tausheck obtained a patent on OCR in Germany and this is the first conceived idea of an OCR. Their approach was, what is referred to as template matching in the literature. The template matching process can be roughly divided into two sub processes, i.e. superimposing an input shape on a template and measuring the degree of coincidence between the input shape and the template. The template, which matches most closely with the unknown, provides recognition. The two-dimensional template matching is very sensitive to noise and difficult to adapt to a different font. A variation of template matching approach is to test only selected pixels and employ a decision tree for further analysis. Peephole method is one of the simplest methods based on selected pixels matching approach. In this approach, the main difficulty lies in selecting the invariant discriminating set of pixels for the alphabet. Moreover, from an Artificial Intelligence perspective, template matching has been ruled out as an explanation for human performance [1, 2].

2 Features Derived from the Statistical Distribution of Points

This technique is based on matching on feature planes or spaces, which are distributed on an n-dimensional plane where n is the number of features. This approach is referred to as statistical or decision theoretic approach. Unlike template matching where an input character is directly compared with a standard set of stored prototypes. Many samples of a pattern are used for collecting statistics. This phase is known as the training phase. The objective is to expose the system to natural variants of a character. Recognition process uses this statistics for identifying an unknown character. The objective is to expose the system to natural variants of a character. The recognition process uses this statistics for partitioning the feature space. For instance, in the K-L expansion one of the first attempt in statistical feature extraction, orthogonal vectors are generated from a data set. For the vectors, the covariance matrix is constructed and its eigenvectors are solved which form the coordinates of the given pattern space. Initially, the correlation was pixel-based which led to large number of covariance matrices. This approach was further refined to the use of class-based correlation instead of pixel-based one which led to compact space size. However, this approach was very sensitive to noise and variation in stroke thickness. To make the approach tolerant to variation and noise, a tree structure was used for making a decision and multiple prototypes were stored for each class. Researchers for classification have used the Fourier series expansions, Walsh, Haar, and Hadamard series expansion.

3 Geometrical and Topological Features

The classifier is expected to recognize the natural variants of a character but discriminate between similar looking characters such as ‘k’ – ‘ph’, ‘p’ - ‘Sh’ etc. This is a contradicting requirement which makes the classification task challenging. The structural approach has the capability of meeting this requirement. The multiple prototypes are stored for each class, to take care of the natural variants of the character. However, a large number of prototypes for the same class are required to cover the natural variants when the prototypes are generated automatically. In contrast, the descriptions may be handcrafted and a suitable matching strategy incorporating expected variations is relied upon to yield the true class. The matching strategies include dynamic programming, test for isomorphism, inexact matching, relaxation techniques and multiple to-one matching. Rocha have used a conceptual model of variations and noise along with multiple to one mapping. Yet another class of structural approach is to use a phrase structured grammar for prototype descriptions and parse the unknown pattern syntactically using the grammar. Here the terminal symbols of the grammar are the primitives of strokes and non-terminals represent the pattern-classes. The production rules give the spatial relationships of the constituent primitives.

4 Hybrid Approach

The statistical approach and structural approach both have their advantages and shortcomings. The statistical features are more tolerant to noise (provided the sample space over which training has been performed is representative and realistic) than structural descriptions. Whereas, the variation due to font or writing style can be more easily abstracted in structural descriptions. Two approaches are complimentary in terms of their strengths and have been combined. The primitives have to be ultimately classified using a statistical approach. Combine the approaches by mapping variable length, unordered sets of geometrical shapes to fixed length numerical vectors. This approach, the hybrid approach, has been used for omni font, variable size character recognition systems.
5 Neural Networks
In the beginning, character recognition was regarded as a problem, which could be easily solved. But the problem turned out to be more challenging than the expectations of most of the researchers in this field. The challenge still exists and an unconstrained document recognition system matching human performance is still nowhere in the sight. The performance of a system deteriorates very rapidly with deterioration in the quality of the input or with the introduction of new fonts handwriting. In other words, the systems do not adapt to the changed environment easily. Training phase aims at exposing the system to a large number of fonts and their natural variants. The neural networks are based on the theory of learning from the known inputs. A back propagation neural network is composed of several layers of interconnected elements. Each element computes an output, which is a function of weighted sum of its inputs. The weights are modified until a desired output is obtained. The neural networks have been employed for character recognition with varying degree of success. The neural networks are employed for integrating the results of the classifiers by adjusting weights to obtain desired output. The main weakness of the systems based on neural networks is their poor capability for generality. There is always a chance of under training or over training the system. Besides this, a neural network does not provide structural description, which is vital from artificial intelligence viewpoint. The neural network approach has solved the problem of character classification no more than the earlier described approaches. The recent research results call for the use of multiple features and intelligent ways of combining them. The combination of potentially conflicting decisions by multiple classifiers should take advantage of the strength of the individual classifier, avoid their weaknesses and improve the classification accuracy. The intersection and union of decision regions are the two most obvious methods for classification combination.

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ULTRA WIDEBAND COMMUNICATIONS APPLICATIONS

The trade-off between data rate and range in UWB systems holds great promise for a wide variety of applications in military, civilian, and commercial sectors. The FCC categorizes UWB applications as either radar, imaging, or communications devices. Radar is considered
one of the most powerful applications of UWB technology. The fine positioning characteristics of narrow UWB pulses enables them to offer high-resolution radar (within centimeters) for military and civilian applications. Also, because of the very wide frequency spectrum band, UWB signals can easily penetrate various obstacles. This property makes UWB-based ground-penetrating radar (GPR) a useful asset for rescue
and disaster recovery teams for detecting survivors buried under rubble in disaster situations.
In the commercial sector, such radar systems can be used on construction sites to locate pipes, studs, and electrical wiring. The same technology under different regulations can be used for various types of medical imaging, such as remote heart monitoring systems. In addition, UWB radar is used in the automotive industry for collision avoidance systems.
Moreover, the low transmission power of UWB pulses makes them ideal candidates for covert military communications. UWB pulses are extremely difficult to detect or intercept; therefore, unauthorized parties will not get access to secure military information. Also, because UWB devices have simpler transceiver circuitry than narrow band transceivers, they can be manufactured in small sizes at a lower price than narrow band systems. Small and inexpensive UWB transceivers are excellent candidates for
wireless sensor network applications for both military and civilian use. Such sensor networks are used to detect a physical phenomenon in an
inaccessible area and transfer the information to a destination.
A military application could be the detection of biological agents or enemy tracking on the battlefield. Civilian applications might include habitat monitoring, environment observation, health monitoring, and home automation.
The precise location-finding ability of UWB systems can be used in inventory control and asset management applications, such as tagging
and identification systems—for example, RFID tags. Also, the good performance of UWB devices in multi path channels can provide accurate geo location capability for indoor and obscured environments where GPS receivers won’t work. The high-data-rate capability of UWB systems for short distances has numerous applications for home networking and multimedia-rich communications in the form of WPAN applications. UWB systems could replace cables connecting camcorders and VCRs, as well as other consumer electronics applications, such as laptops, DVDs, digital cameras, and portable HDTV monitors. No other available wireless technologies—such as Blue tooth or 802.11a/b—are capable of transferring streaming video.

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ADVANTAGES OF ULTRA WIDEBAND COMMUNICATIONS

The nature of the short-duration pulses used in UWB technology offers several advantages over narrowband communications systems. In this
section, we discuss some of the key benefits that UWB brings to wireless communications.

5.1 Ability to share the frequency spectrum.

The FCC’s (Federal Communications Commission) power requirement of –41.3dBm/MHz, 5 equal to 75 nano watts/MHz for UWB systems, puts them in the category of unintentional radiators, such as TVs and computer monitors. Such power restriction
allows UWB systems to reside below the noise floor of a typical narrow band receiver and enables UWB signals to coexist with current radio services with minimal or no interference. However, this all depends on the type of modulation used for data transfer in a UWB system.
Some modulation schemes generate undesirable discrete spectral lines in their PSD, which can both increase the chance of interference to other systems and increase the vulnerability of the UWB system to interference from other radio services. Figure 1–6 illustrates the general idea of UWB’s coexistence with narrow band and wide band technologies.

5.2. Large channel capacity

One of the major advantages of the large bandwidth for UWB pulses is improved channel capacity. Channel capacity, or data rate, is defined as the maximum amount of data that can be transmitted per second over a communication channel. The large channel capacity of UWB communication systems is evident from Hartley-Shannon’s capacity formula:
where C represents the maximum channel capacity, B is the bandwidth, and SNR is the signal-to-noise power ratio. As shown in Equation 1–5, channel capacity C linearly increases with bandwidth B. Therefore, having
several gigahertz of bandwidth available for UWB signals, a data rate of gigabits per second (Gbps) can be expected. However, due to the FCC’s current power limitation on UWB transmissions, such a high data rate is
available only for short ranges, up to 10 meters. This makes UWB systems perfect candidates for short-range, high-data-rate wireless applications
such as wireless personal area networks (WPANs). The trade-off between the range and the data rate makes UWB technology ideal for a wide array of applications in military, civil, and commercial sectors.

5.3. Ability to work with low signal to noise ratios

The Hartley-Shannon formula for maximum capacity (Equation 1–5) also indicates that the channel capacity is only logarithmically dependent on signal-to-noise ratio (SNR). Therefore, UWB communications systems
are capable of working in harsh communication channels with low SNRs and still offer a large channel capacity as a result of their large BW.

5.4 Low probability of intercept and detection.
Because of their low average transmission power, as discussed in previous sections, UWB communications systems have an inherent immunity to detection and intercept. With such low transmission power, the eavesdropper has to be very close to the transmitter (about 1 meter) to be able to detect the transmitted information. In addition, UWB pulses are time modulated with codes unique to each transmitter/receiver pair. The time modulation of extremely narrow pulses adds more security to UWB transmission, because detecting picoseconds pulses without knowing when they will arrive is next to impossible. Therefore, UWB systems hold
significant promise of achieving highly secure, low probability of intercept and detection (LPI/D) communications that is a critical need for military operations.

5.5 Resistance to jamming

Unlike the well-defined narrow band frequency spectrum, the UWB spectrum covers a vast range of frequencies from near DC to several gigahertz and offers high processing gain for the UWB signals. Processing gain (PG) is a measure of a radio system’s resistance to jamming and is defined as the ratio of the RF bandwidth to the information bandwidth of a signal

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INTRODUCTION TO ULTRA WIDEBAND COMMUNICATIONS

Ultra-wideband communications is fundamentally different from all other communication techniques because it employs extremely narrow RF pulses to communicate between transmitters and receivers. Utilizing
short-duration pulses as the building blocks for communications directly generates a very wide bandwidth and offers several advantages, such as
large throughput, covertness, robustness to jamming, and coexistence with current radio services .

2. HISTORY AND BACKGROUND

Ultra-wideband communications is not a new technology; in fact, it was first employed by Guglielmo Marconi in 1901 to transmit Morse code sequences across the Atlantic Ocean using spark gap radio transmitters. However, the benefit of a large bandwidth and the capability of implementing multi-user systems provided by electromagnetic pulses were never considered at that time.
Approximately fifty years after Marconi, modern pulse-based transmission gained momentum in military applications in the form of impulse radars. From the 1960s to the 1990s, this technology was restricted to military and Department of Defense (DoD) applications
under classified programs such as highly secure communications. However, the recent advancement in micro processing and fast switching in semiconductor technology has made UWB ready for commercial applications.
Therefore, it is more appropriate to consider UWB as a new name for a long-existing technology.

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Wireless Charging of Mobile

With the mobile phones becoming a basic part of life, the recharging of batteries has become a big problem and with the prospect of mobile devices being equipped with additional peripheral devices like cameras, this problem worsens. As already mentioned, this paper suggests a novel method to charge the mobile phones on the move. The main principle in this proposal is to convert the incoming microwave energy to D.C through the rectenna, and use this voltage to charge the battery of the mobile.

A RECTifying anTENNA; rectifies received microwaves into DC current. A rectenna comprises of a mesh of dipoles and diodes for absorbing microwave energy from a transmitter and converting it into electric power. Its elements are usually arranged in a mesh pattern, giving it a distinct appearance from most antennae. A simple rectenna can be constructed from a schottky diode placed between antenna dipoles Rectennae are highly efficient at converting microwave energy to electricity. In laboratory environments, efficiencies above 90% have been observed with regularity.

The transmitter can be any one of the high frequency oscillators such as Klystrons, Traveling Wave Tubes, and Magnetrons. In our proposal the use of magnetron as the high frequency oscillator is explained. Magnetrons are preferred because they are highly stable.

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