There is no suspicion that IoT has added a new dimension to the living being by the link between smart objects. Thus making the link among any media and anything at any place and anytime was appreciable. Under the umbrella of the Internet of Things (IoT) the number of interconnected devices is expected to grow exponentially toward more than 34 billion devices until 2021. IoT will propose the unique identification of the objects and their virtual representation as the basis for autonomously development of applications and services. These will be characterized by enormous and self-governing data capture, incident transfer, network connectivity and interoperability. This technology has a lot of applications in heterogeneous fields. The IoT technology and applications are likely to be major drivers of investment and innovation in the communications sector, over the forthcoming years, delivering the valued advantage to citizens, client and industrial end-users. These will lead to the introduction of many new and modern services. It will permit data to be transmitted between many various types of devices, enhance the safety of transportation, and decrease the consumption of energy and enhance our health. In this paper, we are briefly discussing about the Internet of Things and applications in several fields. The IoT applications are using at the edge of the network sensors accumulate data on a computing and communicating device and actuators to perform distinguished tasks controlled by these devices.

At present IoT is immensely a descriptive term of a vision that everything should be connected to the internet. IoT applications have been widely used in several fields of social living such as healthcare and social products, industrial automation and energy. In this scenario, there are more than 14 billion interconnected digital and electronic devices in operation worldwide, the equivalent of almost two devices for every human being on earth. The IoT connects different nonliving objects through the internet and enables them to share information with their community network to automate processes for human beings and makes their lives convenient. Subsequently, objects are being amalgamated with internet connectivity and powerful data analysis capabilities that promise to change the way we work and live. The Internet is a worldwide system of interconnected computer networks that use the standard Internet protocol suite (TCP/IP) to serve billions of users globally. The most vital characteristics of IoT include connectivity, active engagement, connectivity, sensors, artificial intelligence, and small device use. This paper provides an overview of existing Internet of Things (IoT), technical details, and applications in this new emerging area as well as we are thoroughly analyzing the layer about the IoT. However, this manuscript will give a better understanding for the new researchers, who want to do research in this field of Internet of Things.

Today scenario almost all the peoples are using internet to fulfill their task through a wired or wireless network. The speed of internet is an important issue and everyone be it business, organizations, entrepreneurs, and institutions is thrust for getting correct information at the correct time and correct place. Then need rapid internet connectivity, technology and huge spectrum of channels. The wireless-fidelity (Wi-Fi) gives you the speed of 150 Mbps, according to standards of 1EEE 802.11n, but not sufficient to fulfill the necessity of required users over the network. In order to remove this deficiency of Wi-Fi, a new technology is developed by German physicist, professor Harald Haas is known as Li-Fi. The Li-Fi is a wireless communication system in which light is used as a carrier signal instead of traditional radio frequency as in Wi-Fi. Li-Fi is a technology that utilizes a light emitting diode to transmit data wirelessly. It uses a bidirectional and the wireless mode of communication using light. In this paper, I am aiming to demonstrate a close-up view about Li-Fi Technology. This technology we can obtain the data rate greatly speedier than 10 Mbps, which is a lot greater than our LAN (Local Area Network). Li-Fi is very remunerative over Wi-Fi as it uses VLC by which we can make use of the maximum 60 GHz spectrum. Li-Fi confer transmission of data via LED bulb whose intensity change in an excessively faster speed that it could not be able to be explored by the human eye. Li-Fi is confined to the illuminated area, endue a tremendously controllable environment. The signals cannot travel via walls and are fully secure essentially disassemble the threat of data being hacked remotely.

Recent years have seen the swift development and deployment of Internet-of-Things (IoT) applications in a variety of application domains. In this scenario, people worldwide are now ready to delight the benefits of the Internet of Things (IoT). The IoT is emerging as the third wave in the evolution of the Internet. The 1990s’ Internet wave connected 1.2 billion subscribers while the 2000s’ mobile wave connected another 2.4 billion. Actually, IoT is expected to consist of more than 84 billion connected devices generating 186 zettabyte of data by 2025, in the opinion of IDC. It includes major types of networks, such as distributed, ubiquitous, grid, and vehicular, these have conquered the world of information technology over a decade. IoT is growing fast across several industry verticals along with increases in the number of interconnected devices and diversify of IoT applications. In spite of the fact that, IoT technologies are not reaching maturity yet and there are many challenges to overcome. The Internet of Things combines actual and virtual anywhere and anytime, fascinate the attention of both constructor and hacker. Necessarily, leaving the devices without human interference for a long period could lead to theft and IoT incorporates many such things. In this paper, we are briefly discussing technological perspective of Internet of Things security. Because, the protection was a major concern when just two devices were coupled. In this context, security is the most significant of them. Today scenario, there are millions of connected devices and billions of sensors and their numbers are growing. All of them are expected secure and reliable connectivity. Consequently, companies and organizations adopting IoT technologies require well-designed security IoT architectures.

Even today in Twenty First Century Handwritten communication has its own stand and most of the times, in daily life it is globally using as means of communication and recording the information like to be shared with others. Challenges in handwritten characters recognition wholly lie in the variation and distortion of handwritten characters, since different people may use different style of handwriting, and direction to draw the same shape of the characters of their known script. This paper demonstrates the nature of handwritten characters, conversion of handwritten data into electronic data, and the neural network approach to make machine capable of recognizing hand written characters.Key Words: Machine recognition, Handwriting recognition, neural networks. INTRODUCTIONHandwritten characters are vague in nature as there may not always be sharp perfectly straight lines, and curves not necessarily be smooth, unlikely the printed characters. Furthermore, characters can be drawn in different sizes and orientation which are often supposed to be written on a baseline in an upright or downright position. Therefore, a robust handwritten recognition system can be designed by considering these limitations. However, it is quiet tedious sometimes to recognize hand written characters as it can be seen that most of the people can not even read their own written notes. Therefore, there is an obligation for a writer to write clearly. But even today in Twenty First Century Handwritten communication has its own stand and most of the times, in daily life it is globally using as means of communication and recording the information like to be shared with others.Researchers already paid many efforts in designing hand written character recognition system most of them cited as [1-5] because of its important application like bank checking process, reading postal codes and reading different forms [6]. Handwritten digit recognition is still a problem for many languages like Arabic, Farsi, Chinese, English, etc [7]. A machine can perform more tasks than a human being in the same time; this kind of application saves time and money and eliminates the requirement that a human perform such a repetitive task. For the recognition of English handwritten characters, various methods have been proposed [8][9][10][11][12]. Also a few numbers of studies have been reported for Farsi language [13][14][15]. Proposed Hand written character recognition system for machine recognition can be developed in these phases: scanning of hand written characters i.e conversion into electronic data, usually an black & white image file; some preprocessing can be applied to the image; then the feature of the character will be extracted from the image; finally, on the basis of extracted features from the image, the character can be classify to recognize using gradient descent learning method for feed forward neural network. In next sections we explore the proposed hand written character recognition system step by step. Finally, in the last section results will be...

The Internet as a whole does not use secure links, thus information in transit may be vulnerable to interruption as well. The important of reducing a chance of the information being detected during

This paper demonstrates the use of neural networks for developing a system that can recognize hand-written English alphabets. In this system, each English alphabet is represented by binary values that are used as input to a simple feature extraction system, whose output is fed to our neural network system. KeywordsNeural network pattern recognition, hand written character recognition.

Stock Market is the market for security where organized issuance and trading of Stocks take place either through exchange or over the counter in electronic or physical form. It plays an important role in canalizing capital from the investors to the business houses, which consequently leads to the availability of funds for business expansion. In this paper, we investigate to predict the daily excess returns of Bombay Stock Exchange (BSE) indices over the respective Treasury bill rate returns. Initially, we prove that the excess return time series do not fluctuate randomly. We are applying the prediction models of Autoregressive feed forward Artificial Neural Networks (ANN) to predict the excess return time series using lagged value. For the Artificial Neural Networks model using a Genetic Algorithm is constructed to choose the optimal topology. This paper examines the feasibility of the prediction task and provides evidence that the markets are not fluctuating randomly and finally, to apply the most suitable prediction model and measure their efficiency