This paper aims at combining object detection at real time and recognition with suitable deep learning methods in order to detect and recognize objects position as well as the names of multiple objects detected by the camera using an object detector algorithm. This is to aid the visually impaired user without the help of any other person. The image and video processing algorithms were designed to take real-time inputs from the camera, Deep Neural Networks were used to predict the objects and uses Google’s famous Text-To-Speech (GTTS) API module for the anticipated voice output precisely detecting and recognizing the category or class of objects and locations contained. Our best result shows that the system recognizes 91 categories of outdoor objects and produces the output in speech i.e. in an audio format even when a reduced amount of spectral information from the data is available.

Objective: Nowadays, Big Data technologies play a vital role in diverse areas like health domain, finance, and social networking, and so forth. This paper enlightens the readers, students and research scholars to be aware of challenges and opportunities with Big Data applications over "Smart Healthcare System" for refining optimized patient-centric services.Methods/Analysis: Big Data applications over the smart health care system with challenges and opportunities which support providers to identify and recommend appropriate medication in advance using Sensor Technology, machine learning, and Big Data techniques.Findings: This paper introduces appropriate medications, augmenting in research by understanding the Big Data Challenges and Opportunities, which deal with patient data capture, store, search, sharing, transfer, analysis, and visualization.Applications/Improvements: Big Data Analytics on Smart Health Care systems with sensor technology, which improves diagnosis, therapy, and cares at an advanced level, saves time and reduces the cost.

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