Dead Communication Technology - Report Example

Dead Communication Technology by (Student’s Name) Foundation Course- Tutor: (Instructor’s Name) Institution’s Name Department Date Dead Communication Technology Introduction In the recent past, there have been innumerable technological advancements. These advancements seek to better the lives of people dwelling in society seeking to indoctrinate the globalization sentiments. Additionally, organizations and governmental institutions inculcate technological advancements in their procedures and operations. The intent behind such moves is to ensure that efficiency and effectiveness is harnessed in the organizational setting. It is evident that resources are continually eradicated by humanity creating the need to preserve available reserves. Scarce resources call for overly efficient tools and equipments that reduce material wastage, increase productivity, reduce time wastage and ensure accuracy in operations. Additionally, governments have redesigned the educational frameworks ensuring that students gain expertise at tender ages (Grantham & Vaske 1985). This resonates to technologically enhanced products that perform better in both the short and long run. Conversely, the technological advancements evidenced in the modern societal setting indicate that the past technology is obsolete. It is notable that new technological equipment is a new product based on past ideas. This implies that modern equipments are not new formulations but rather enhancements from past models. With new technological products, the old products are obsolete, inefficient and hence, users prefer new models. With the passage of time, the old neglected models are forgotten thus referred to as dead technology. Dead technology represents the mass of obsolete equipments that humanity no longer uses given the prevalent upsurge in developments. There are immense examples of dead technologies in the communication sector with an example of the optical character recognition. Optical Character Recognition Optical Character Recognition is an electronic device that converts either handwritten, print or type written text into scanned images (Balm 1970). The device seeks to enhance data entry functions converting variety of data into usable scanned images. With the onset of computerization, each endeavor is now digitalized negating the negative effects emanating from paperwork. The optical character recognition digitalizes formally print text converting the data into computer readable information. This is because computers create a dire need for digitalization given the inherent benefits that come along. For instance, on line display, compatible storage, electronic enhanced search, and machine process are all computer-enhanced capabilities. It is worth noting that Optical Character Recognition is an element devised to harness the realm of research through computer vision, artificial intelligence, and pattern recognition. Technological advancements have led to the development of newer Optical Character Recognition as opposed to the older models that required character recognition to be programmed in line with a single image. The modern developments paved way for intelligent systems that avail high degree recognition accuracy using common fonts. Additionally, the newer models have extra features that facilitate formatting and production of copies similar to the original documents. History The history of the Optical Character Recognition dates back to 1914. During this period, two vital issues needed redress and urgent rectification. First, there was a dire need to expand telegraphy given the upsurge in population. This implies that the rise in population pressured for an increase telegraphy bandwidth to serve the entire populace holistically. Secondly, there was a need to create devices usable by the blind to enhance reading. Goldberg Emanuel was the first developer to formulate an electronic device that would convert print characters into standardized telegraph code. Another developer formulated a similar device had the ability to move across a printed page producing tones of corresponding characters. This was a hand held scanner later modified to the Optical Character Recognition devise. Applications or uses of the Optical Character Recognition General uses The Optical Character Recognition was commonly used for data entry. This is because, during the formative years of the devise, people were over reliant on analogue communication frameworks. The urge to digitalize operations, harness accuracy, and ensure timely procedures necessitated creation of an electronic device. The Optical Character Recognition also used to recognize number plates automatically, which was crucial during the yesteryears. Third, the Optical Character Recognition quickly converted print documents to scans accessible by computers. During the late 1990s, the Optical Character Recognition was available as a reliable web service usable in a cloud computing environ, or mobile application. Visually impaired or blind users Bergeron (1998) indicates that the development of Optical Character Recognition heightened after the second world liberation. In 1970s, an electronics wizard by the name Ray Kurzweil sought to develop related computer products. It is worth noting that, although Ray Kurzweil retains admirable praise as the initiator of the Omni font Optical Character Recognition devise, it was in use since a decade into the past. The computer geek however produced a reading machine for the blind (Bergeron, 1998). The intent was to develop a devise that would enhance a computer’s ability to read aloud for the blind to hear. These devise required the incorporation of two separate technologies, which included the flatbed scanner and the text to speech synthesizer. In the late 1970s, the company unveiled a working Optical Character Recognition computer program that was availed for commercial purchases. History indicates that the initiator disposed of the company to investor with a desire to commercialize the paper to text converter. Types of the Optical Character Recognition First, there is the Optical Character Recognition that targets print, or typed text. The Optical Character Recognition converts a character or glyph at a time. The intelligent character recognition is a type of Optical Character Recognition that involves machine learning but targets a single character at a time (Unknown Author 1971). This second type of Optical Character Recognition is usable where the glyphs used in cursive script are inseparable. It is notable that the Optical Character Recognition is on offline system that analyses documents in their static form. With the passage of time, the offline data recognition devise has been wiped off rendering the Optical Character Recognition obsolete. In the modern market, there has been a prevalent upsurge in the demand for an online system. Technology has delivered efficient devises meant for to meet the upcoming consumer needs. They include the online character recognition, the intelligent character recognition, the dynamic character recognition, or the real time character recognition devices. Technological and Social “Death” of the Optical Character Recognition Optical Character Recognition has gone through all development cycles in the technological sector. Since its inception, the device has been improved seeking to attain more accurate, efficient, and timely results. The Optical Character Recognition is still usable in the modern age but at the peril of the client. This is because of the fact that technological death does not mean utter lack of use. It means that the piece of technology has been overridden by modernized sophisticated gadget that performs better than the old device. With the Optical Character Recognition, this is the scenario implying that though it is still in the market, users alienate its use going for better models. Social death is estranged to the technological death in the realm of obsoleteness. This is because in the event that a devise’s useful life elapses, the technological sector endeavors to develop a newer better model that will assure better results. Conversely, the social death of a devise emanates from the fact that marketers and advertising agency cease to publicize the equipment. This would be because of the fact that society looses relevance for old equipment and adopt new technology. Optical Character Recognition was replaced by optical mark recognition technology (Wynn 2012). The new technology has the ability to capture human marked data from tests or survey documents. It is worth noting that unlike the Optical Character Recognition reader, the optical mark recognition is not complicated. Consequently, the optical mark recognition can relay sensitive information like answer sheets. Additionally, the optical mark recognition software has computer software’s that only fosters compatibility but also enhances the use of image scanners. Compared to the Optical Character Recognition software that only used dedicated scanners, the optical mark recognition are used with image scanners that harness the production of better results. The new optical mark recognition device can be used in an array of activities including: institutional research, consumer, or community surveys, data compilation, tests, assessments, product evaluation, and time sheets. Since inception, the optical mark reader requires special ink as well as a special reader that spearhead the devises activities. The recent technological advancements now allow the users to formulate and print their own forms from scratch. It is worth noting that optical mark recognition can be acquired for personal use as it is an all in one printer. Selective printing is harnessed and as such, the optical mark reader does not compare to the Optical Character Recognition. It is evident that the Optical Character Recognition is no longer feasible in the current market. Given the dynamic progress attained in the recognition sector of characters, the Optical Character Recognition ranks lowly. It is worth taking into account that the Optical Character Recognition singly recognizes characters while the optical mark reader is holistic software. Additionally, the Optical Character Recognition has no inbuilt computer compatibility (Stevens 1970). The optical mark reader has inbuilt computer software that adds value to the machine as well as newer features. In conclusion, it is evident that the technological realm has evolved immensely over the years. This is because of the fact that technology is the sole driving force that fosters growth and development. With adequate technological advancements, numerous avenues are viable in the societal setting. Similarly, once technology advances endeavors to produce a new devise, strategy, or procedures the older models are considered dead. This is because the social and technological setting desire to use newer models as they are based on older generations. The mythical belief is that the new models advance the former and rectify any prevalent defects. This implies that new models are efficient and effective in terms of price and resource utilization. The Optical Character Recognition has been replaced by the optical mark recognition. Both devises undertake similar duties only that one is superior. The Optical Character Recognition is almost extinct as the optical mark recognition supersedes it technologically. For the mean time, the optical mark recognition is used as everyone awaits technological advancements in the foreseeable future. Reference list Balm, G, (1970), An Introduction To Optical Character Reader Considerations. Pattern Recognition, 2(3), 151-166. Bergeron, B, (1998), Optical Mark Recognition Tallying Information From Filled-in 'bubbles'. Postgraduate, 104(2), 236. Unknown Author, (1971), Character Recognition. Optics & Laser Technology, 3(1), 58-58. Grantham, C. E., & Vaske, J, (1985), Predicting The Usage Of An Advanced Communication Technology. Behaviour & Information Technology, 4(4), 327-335. Ledley, R, (1970), Special Issue On Optical Character Recognition. Pattern Recognition, 2(3), 145. Stevens, M, (1970), Introduction To The Special Issue On Optical Character Recognition (OCR). Pattern Recognition, 2(3), 147-150. Wynn, R. (2012). Optical Mark Recognition. Data Processing , 26(9), 26-27. Read More