Image Steganography with Dual Layer Security Using Fragment and Unite Technique

At the present time where a regularly increasing number of data is made in different structures, kept and transferred, online security is the most vigorous factor. Different ways such as Cryptography, Steganography and Digital Watermarking are used to defend the data. The proposed framework gives additional dual layer of security as Cryptography and Steganography have been combined. Here data will be encrypted by using Encryption Algorithm AES. Then the encrypted data is embedded into a system’s Defaulting image using least significant byte LSB Algorithm. Steganographed Default image is then fragmented into uniform parts and gets unite into reverse sequence using Uniform Fragment and Unite Technique. Reverse Steganographed Default image is then hidden (unseen) into another image. The proposed framework has summarized the goal to be safety and security factors

Rainfall Prediction a Novel Approach

The proposed framework is a prescient model for precipitation forecast. It is a framework which will foresee the future climate condition in light of the over a wide span of time climate conditions. The proposed framework makes utilization of more number of characteristics than the current framework which makes the forecast more precise. The framework utilizes the classifier calculation that is Naïve Bayes Algorithm for ordering the datasets. The system makes use of the huge dataset of weather condition of various location. The system uses the classifier algorithm called Decision tree classifier for classifying the dataset into a tree format which is used for the purpose of decision making

Alive Human Detection Robot for Rescue Operation

In the current technological world, the technologies are evolving day by day. In the modern world, there is continuous development of skyscraper buildings & dwellings, which increases the risk of losing life by natural calamities and man-made disasters. During earthquakes, landslides, and building collapse, a lot of times, humans are trapped under debris and it becomes impossible to detect their presence by the rescue team. There are some cases where it is impossible for rescue teams to reach certain locations in affected areas. The Proposed system is a raspberry pi based human detection robot, which is used to detect live human beings trapped under debris in a affected environment. The robot navigates through the zigzag path and it is controlled by an android application. The set of sensors assembled to the raspberry pi are Microwave radar sensor, Ultrasonic sensor, Temperature sensor and Gas sensor. The Microwave radar sensor is also used to detect the human being behind the obstacle. The Temperature sensor is used to detect the temperature and Gas sensor is used for gas leakage respectively. And the camera module is used to analyze the current scenario