USE OF SOCIAL POSTS FOR DISASTER DETECTION USING NATURAL LANGUAGE PROCESSING

A person’s attitude is reflected using his behavior. If we want to know a person’s behavior, we can ask to his friend about him. With the growing importance of social media, researchers made social media as a business review machine. Using sentiment analysis on reviews, product’s market value, lifespan of product etc. can be predicted. Social media can also be helpful to get reaction of public on some social issue. This will help to politicians for analyzing the impact of social issue on public’s mood. Sentiment analysis of reviews from different social media such as short texts are insufficient for analysis. The main idea behind the proposed system is to make use of social media which is immensely active i.e. Facebook and use the posts which are posted. Using sentiment analysis and Natural Language Processing (NLP) on posts, disasters are extracted (riots, accidents, traffic issue, natural calamities etc.) and using Naïve Bays classification technique disasters are classified. The challenges are processing of unstructured data and finding the annotated data. In this paper we find the solution for above challenges which will be beneficial for our system and provide solution to handle unstructured data easily

Solar Operated Weather Forecasting Station

The electrical energy generated by PV systems depends mainly on the available solar radiation reaching the PV modules. Tracking systems ensure that the sun's rays fall perpendicular on the active surface of the PV module. Improving the efficiency of solar panels is the main task of solar energy generation. One of the methods is a solar tracking system. The most critical parameters of tracking systems is a precise orientation to the sun. This paper presents the outline and execution of a simple, easy and cheaper automatic, Aurdino based single-axis solar tracking for weather forecasting station application. In this paper, single-axis solar trackers' performance based on schedule and light-dependent resistor (LDR) photosensors and a stationary photovoltaic installation in various weather conditions has compared. A comparative analysis of the operation of a manufactured schedule solar tracker and an LDR solar tracker in different weather conditions for one year has performed; also, a simple method for determining the rotation angle of a solar tracker based on the encoder has proposed