Nowadays the multimedia data easily available to most people. It is the main cause of illegal access to multimedia content, theft of the intellectual property, easily copying and manipulate the data over the internet, and spreading fake news. With the increase in the availability of the internet to a common man, it is observed that most of the multimedia data misused. Nowadays telemedicine, tele diagnosis, tele consultation, teleradiology, telematic services are necessary. Electronic Patient Record is essential to provide these services. It is necessary to secure the multimedia data by using a suitable watermarking technique. Due to the huge availability of high-speed internet, digital movie piracy was increased rapidly and it causes revenue loss and affects the employment of the people. The high demand for protecting digital videos or movies from unauthorized access. So, it is necessary to protect the intellectual property of the owner, stop unauthorized access of data, also protect and stop the spreading of fake news. In this article, we presented a survey of digital watermarking, bolding its key concepts, embedded and extracted features, state-of-the-art implementation, and research challenges. The primary goal of this article is to provide an improved understanding of the embedding-extracting of watermarking challenges of watermarking and identify important research paths in health care and multimedia applications.

The advancements of smartphone technology, bring together doctors and patients for monitoring clinical activities, remote assistants, and preemptive measures, specifically for those who are under medical control. As smartphones become an integral part of human life, they are employed to monitor health conditions within the human activity recognition (HAR) system. This paper presents a Smartphone-Based Human Activities Recognition System using Random Forest Algorithm(RFA). The RFA algorithm is a classifier that has several decision trees on subclasses of the dataset. The RFA takes the average to enhance the projecting accuracy of the given dataset. Four evaluation parameters such as F1 Score, accuracy, precision, and sensitivity are considered to estimate the proposed system performance. Further, comparing the performance of the proposed RFA with existing classifiers, the accuracy of the proposed system achieves 98.34% as compared with other classifiers.

Nowadays, digital watermark protects intellectual property in the digital world. In this article, a new singular value decomposition (SVD) based robust unsighted video watermarking technique is used for protection of copyright or owns individual work. The Singular Value Decomposition is used in this method to embed the information in a video file. In the embedded process the information generally referred to as watermark, which is of the form either audio, text, video, or any binary image or digital image. The embedded information can be identified in this process without considering the mechanisms of the original video, or any other knowledge about the encoded video ‘s main singular values. Singular value decomposition is used in embedding the information as well as retrieving the information from the embedded watermarked video. SVD based robust unsighted video technique shows that it bears required robustness on various attacks like MPEG-2 compressed video, median filtered, small rescaled, and rotational videos. In the experimental result, it is noticed that the unsighted video watermarking technique has visible quality and robustness for various attacks. In which watermark is installed in uniquely chose particular estimations of the video, and the first request can be kept up to recovering the data in our method and it has been indicated roust to different attacks.