Internet is changing the world and overall activities. Internet is the global system of network of networks and comprised with the private, public, academic and research, business and commercial, activities and sectors. Initially internet was mainly offered in the Government activities and mainly in the defense and space stations but gradually internet become a tool of common man and involved in most of the activities and sectors. Internet may be accessed in various way and methods; importantly internet services are also changing due to its features and emerging speed. The data transfer rate is differs from the technology to technology and importantly country to country. This paper is talks about the data transfer and its changing pattern and emphasizing speed divide among the countries. Paper highlights all these aspects in brief manner with theoretical context.

Cyberbullying is a socially aggressive and has powerful negative effects for individuals, specifically adolescents and youngsters. Cyberbullying allows the offender to mask his or her identity behind a computer. This anonymity makes it easier for the offender to strike blows against a victim without having to see the victim’s physical response. The distancing effect that technological devices have on today’s youth often leads them to say and do crueler things compared to what is typical in a traditional face-to-face bullying situation. In the recent times many methods for automatic thoughts of mining in the online data are becoming increasingly important, to increase the safety parameter of the people. This framework is proposed to extract Cyberbully polarity from the Forum using Fuzzy logic technique. At first, the given input is pre-processed and the useful content is gathered. Subsequently, the pre -processed data will be sent to the features extraction method. Probabilities of the words are calculated by using Fuzzy Decision Tree Method. Fuzzy rules can be applied in all these features to extract the certain set of cyberbully words like bad words, insulting words, threatening words and terrorism words from the given input, hence we use text mining here. Finally this method will return the reduced and accurate cyberbully words. This method is performed by human annotation using the existing methods like Mamdani Fuzzy System and Naive Bayes classifier. Extensive experiments are performed by using fuzzy logic on crime debate forum and the results show that this proposed approach is better than the traditional one. Aggressive text detection in social networks allows identifying offenses and misbehavior, and leverages tasks such as cyberbullying detection. Social media became a very useful platform to express ourselves. The expressions have adverse reactions as well. We intend to take data from these platforms and make use of it to improve on the safety parameter. For the development of the system we take the data available on Twitter and filter all the useful contents.

An advanced and novel system for monitoring and tracking the school van to ensure the safety of children, the proposed system works in case of emergencies such as accidents, break down, fire accidents by immediately sharing the location and images of the inside environment of the bus to the school authorities. Images are captured using Pi camera and location by GPS module. Radio Frequency Identifier (RFID) tags are used to track the number of students travelling. A panic switch and two keys are provided. Keys are used if vehicle gets stuck in traffic and in the case of vehicle breakdown. An email alert will be sent to the parents. Panic switch is used in case of emergency. In each case email is attached with the images of the inside environment of the bus. The system possess the hall effect sensor to sense the speed of the vehicle, In case of rash driving the sensor intimates the Raspberry Pi and an alert is sent to the school authority through email.

In today’s competitive world, an individual needs to act smartly and take rapid steps to make his place in the competition. The ratio of the youngsters to that of the elder people is comparatively more and also they contribute towards the development of the society. This paper presents the methodology to extract emotion from the text at real time and add the expression to the textual contents during speech synthesis by using Corpus , emotion recognition module etc. Along with the emotions recognition from the human textual data the system will analyze the various human body signals such as blood pressure, EEG signals , vocal prosody to predict the level of depression so that suitable therapy can be suggested using Prediction algorithm. In text analysis, all emotional

In Wireless Sensor Networks (WSN) applications include an arrangement of separated urban zones secured by sensor hubs (SNs) checking ecological parameters. Singlebounce exchange of information from SNs that exist in the MS's range or overwhelming contribution of system outskirts hubs in information recovery, preparing, buffering and conveying errands. These hubs risk fast vitality fatigue bringing about the loss of system availability and diminished system lifetime. Proposed framework goes for limiting the general system overhead and vitality use related with the multihop information recovery handle while additionally guaranteeing adjusted vitality utilization among SNs and delayed system lifetime. This is accomplished through building bunch structures comprised of part hubs that course their deliberate information to their doled out group head (CH). CHs perform information separating upon crude information misusing potential spatial-transient information access and forward the sifted data to fitting end hubs with adequate lingering vitality, situated in nearness to the MS's direction. This approach fabricates a bunching structure on top of the sensor arrange. That way, high information collection proportions are conceivable since information from the hubs of a similar bunch, for the most part, are firmly connected and along these lines accumulation at each group head impressively diminishes the information sent to RNs. This thusly prompts much lower vitality utilization in the WSN and furthermore a great deal less information is cradled at RNs, diminishing so the likelihood of support floods at an RN.