Smart Manufacturing using IOT

We are entering a new era of computing technology that many are calling the Internet of Things (IoT).Machine to machine, machine to infrastructure, machine to environment, the Internet of Everything, the Internet of Intelligent Things, intelligent systems–call it what you want, but it's happening, and its potential is huge. We see the IoT as billions of smart, connected “things” (a sort of “universal global neural network” in the cloud) that will encompass every aspect of our lives, and its foundation is the intelligence that embedded processing provides. The IoT is comprised of smart machines interacting and communicating with other machines, objects, environments and infrastructures. As a result, huge volumes of data are being generated, and that data is being processed into useful actions that can “command and control” things to make our lives much easier and saferand to reduce our impact on the environment. The creativity of this new era is boundless, with amazing potential to improve our lives

A Novel IR for Relational Database using Optimize Query Building

The different type search engine like Google, binge, AltaVista is used to fetch the information from the database by easy language. The non-technical employee they don’t understand the database and query cannot access the database. The proposed system is performing work as a search engine where users can fetch the information from the database by natural human sounding language. The previous existing system doesn’t able to solve queries in one easy statement. The structured query approach, while expressive and powerful, is not easy for naive users. The keyword-based approach is very friendly to use, but cannot express complex query intent accurately. This paper emphasis on Natural Language based query processor. We have proposed the use of query optimization approach to convert complex NLP query to SQL query, SPAM word removal, POS tagger applied over NL query and concluded that execution time lesser when query size increases.</jats:p

Hindi &amp; Telugu Text-to-Speech Synthesis (TTS) and inter-language text Conversion

Abstract- In this paper, I am explaining single text-to-speech (TTS) system for Indian languages (Viz., Hindi, Telugu, Kannada etc.) to generate human voice or speech (text to a spoken waveform). In a text-to-speech system, spoken utterances are automatically produced from text. This paper present a corpus-driven text-to-speech (TTS) system based on the concatenative synthesis approach. The output generated by the proposed text-to-speech synthesis system resembles natural human voice. It accepts input in two forms: manual user entry and from file (text or MS Word document). Proposed system supports multiple way of output; direct to computer speakers, Wav file, or MP3 file. Generated output can have different accent, tone based on selected languages. The proposed text-tospeech system will be implemented in C#.Net (Windows Form Application) and runs on Windows platforms. This paper has examples for Hindi (North Indian) and Telugu (South Indian) languages ’ to elaborate proposed system. This It also elaborates inter-language text conversion (not translation). Therefore, Hindi text will be converted into Telugu text and vice-versa. The research and development of this TTS done for my M. Tech major project. Index Terms- text-to-speech, indian language, hindi, telugu, speech synthesis, concatenation, text conversion