Co-authored a paper which focuses on enhancing data security at scale with the help of implementing various cryptographic algorithms. Pan Tompkins Algorithm has been used for QRS detection which predicts the abnormal deflections that lead to the irregular data loss events. The same reports have been used to classify which type of cardiac arrhythmia the patient has using MLP (Multilayer Perceptron) algorithm. Both the Pan Tompkins and MLP were developed using PyCharm (IDE for python).

With the progression in the digital sector, regular utilization of the internet and advancements prompts digital attacks. Digital forensic is performed to collect digital data and examine the suspected evidence found in the framework or on an organization to make it acceptable in court. Digital forensics is a part of forensic science concerned about utilizing digital data delivered, stored, and communicated by pcs as a wellspring of proof in examinations and official actions. This paper comprises of a concise outline of the digital forensics process, trailed by the review of the OSForensics tool, its working, features, and implementation. Also, the difficulties and future extent of digital forensics are discussed in the paper.

The current era of information technology revolutions needs rapid progress of digital transformation. Question-answer system is one such remarkable intelligent application based on artificial intelligence that analyzes and processes human interactions, either spoken or written. Question-answer systems have been proven a very effective way of providing 24-hour interaction service that is interacting with end-users thru digital devices as if the user is interacting with a real human being. This application has found its major utilization in answering customers’ queries in almost every business ranging from government to non-profit sectors and from very small to large organizations. Many chatbot frameworks are available that are either code-based or interface-based. However, they lack the usefulness of personal touch in communication. Thus, to have better customer interactions in the form of question-answers and improved personalization, this paper proposes a face recognition-based chatbot system utilizing the natural language processing toolkit with python. The proposed method implements a tailored user-centric approach to a simplistic version of the Question-answer system by implementing machine learning models for Face Recognition which rely on Local Binary patterns and HAAR Classifications. The method trains and maintains a unique dataset mapped to each user associated with the user’s biometric identification. This chatbot focuses on speech synthesis and language processing to retrieve queries of each user based on their unique dataset.

The phrase "big data" emerged in response to the exponential growth of global data as a technology that can store and handle extensive and diverse amounts of data, giving businesses and scientists profound insights into their customers/experiments. Due to cloud computing, big data decentralized mechanisms may be housed in a scalable, fault-tolerant, and dependable environment. The big data computation technique is used in the cloud to improve application consolidation, aggregation of data, and data usage. The most effective approach for complicated computing is cloud computing. Expensive computing gear, specialized space, and software are eliminated using it. The amount of massive data has seen a significant expansion because of cloud computing. Big data management is a difficult and time-consuming process.Big Data is utilized in the decision-making system to uncover valuable, practical inputs for engineering and businesses concealed in the data. Despite its processing limitations, cloud computing has offered computation, networking, and storage capabilities that have assisted in the evolution of big data. This article provides a brief outline of big data implementation, its uses in cloud computing, Cloud computing, and Big data's four pillars—performance, input detail, insights, and reliability and security—that can be leveraged in cloud computing to obtain these benefits at comparably reduced costs. This article also discusses various analytics, the technologies required in linking big data with cloud computing, the difficulties associated with this process, trends in applications of the area, and security considerations. This study also reviews the benefits and drawbacks of employing cloud computing resources to convert big data. It focuses on the connections among big data, cloud computing, storage technologies, and Hadoop technology.

The continuous spread of Internet of Things (IoT) innovations in every field is opening enormous opportunities for everyone. The most astounding applications of IoT revolve around the Smart Cities that is ceaselessly expanding and developing. Smart City is nothing but the coordination of ICT (Information communication Technologies) as well as IoT into the city management, with the intent of tending to the dramatic development of urbanization and population. It not only improves the standards of living for the citizens of any country but also focuses on reducing the impacts of urban activities on our environment, optimization of resources, building innovative technologies and easy resolutions for the citizens of these smart cities. In this paper provides analysis of IoT and its applications, Indian government initiatives with respect to IoT and smart cities and its architecture. This paper highlights essential components of smart city and attempts to establish relation between IoT and Smart cities, issues and challenges and then future opportunities that this new model bringing in the areas of transportation and mobility, parking, defence, education sector, malls, hospitals, health, industries, waste management.