In this paper, I propose a smart door and doorbell system for home automation using the Internet of things (IoT) and Artificial Intelligence (AI) for old aged and differently able people to make their life easy and secure. In this model, I am using Raspberry Pi for managing various interfaces and communications. The model consists of multiple interfaces, including sensors, actuators and multiple inputs and out interfaces. To implement my IoT solution I have used AWS (Amazon web service) IoT to provide many cloud services to support IoT-based applications. The apps give access to IoT devices and the features the cloud services offer to those connected. The tools use various technologies and protocols such as Wi-Fi or cellular data to communicate with the cloud. The mode of communication is via MQTT (Message Queuing and Telemetry Transport) process. I have also used various software, including device software, control services, data derives and core services provided by the AWS IoT, making this model efficient and scalable. The overall aim of this paper is to make appropriate use of the technology for the needy and coming generations to come

Internet of Things (IoT) makes the Internet available to billions of users. Managing large quantities of devices is very critical. Among many other protocols, the global standards adopted Lightweight Machine 2 Machine(LWM2M) defines many traditional system management functions, such as remote device functions, firmware and software updates, communication monitoring, and security. Accessible Mobile Alliance Light-weight specification (OMA LwM2M) has given greater interoperability of applications to the absence of effort faced by the heterogeneous design, fragmented evolution environment and the interface between established solutions. This paper explains the firmware update architecture of LWM2M artefacts using standard OMA Specification. This involves downloading firmware kit, upgrading settings, upgrading states, and taking action after firmware updates

Software engineering practices have been used for years to build software products. Choosing a software development methodology suitable for a specific project and harmonizing the methodology for clear requirements has been controversial ever since the discipline of the software development organization. Currently, the goal of most software companies is to produce software in minimal time at an insignificant cost and to produce software in an unbalanced and changing environment as Agile grows. Finding and addressing mechanisms to address and consider improving successful agile implementation, use, and delivery. In this paper, we will discuss some configurations that confirm why Agile is preferred over waterfall models. As the appeal of Agile methods grows, many software organizations are moving away from traditional systems to adopt Agile development methodologies. As an alternative to extrapolation, Agile is highly adaptable and people-focused. Support those who work closely and for joint teams. However, team size is limited by the workforce factor. This white paper provides a multidimensional observation of performance factors in agile software development projects. Then, evaluate the performance factors published in research papers, articles and technical reports related to real agile projects. To promote the indulgence of success factors, researchers organize them into five categories: organization, people, process, design, and technology. This is why in this white paper we will analyze some of the success factors of agile practices that are manipulated at the organizational level.

In this paper, I propose a model that will analyze the persons sentiment and emotion using social media. Face book, using machine learning and deep learning. Nowadays, most teenagers are depressed and stressed due to the overuse of social media and emotional breakdown. This project will help them to know their status and improve emotional stability. The numerous data floating around virtually can be taken as the context of data science and big data. In this paper, I will show how useful information can be mined out of those data sets. This paper aims to retrieve and pre-process social media data for sentiment analysis, which is a part of natural language processing. I will use several techniques of NLP for data pre-processing for better sentiment analysis. This paper essential requirement is to show the realization how individuals feel certain social media status, which will be utilized for classification.

Participation in every film is free. The traditional approach is to register for the service to be attended to keep at the individual student. The biometric system is another measure of attendance. The implementation of biometric recognition systems to the physical or behavioural characteristics, such as iris, voice, face and fingerprints. However, these measures have proved-time consuming and boring. This makes significant progress in the stands automatically, marking the counting process through. The proposed method is aimed at the students present at the time, and it can be used by other teachers for verification. In this paper along with the CCTV cameras to capture entering students in the classroom and went out. Attendance is displayed by the numbers an hour from entering the class areas

In India online matrimonial websites are widely used among the customers and are the trusted and reputed website of the Indian globally. The number of people getting registered in the matrimonial sites it creates a lot of data sets, a lot of unstructured data sets which is floating around the internet. there comes the concept of big data analysis, big data analysis is the analysis of the data science and machine learning algorithms through which we can extract and mine the knowledgeable and informative data sets which can be used for predicting the future instances. In this paper we are analyzing the big data set from the machine learning data repository, to be driven analyze the different it is its using implementing a different machine learning algorithm and regal the informative information. we will be implementing various data mining operations such as opinion mining and sentiment analysis data visualisation and machine learning technique, marriage information have always been an integral and confidential knowledgeable in any civilized and welleducated society. some online agency rate on these matrimonial websites by creating a profile of an individual to get in touch with the other individual for their life purposes. in this paper, we will be analysing the total number of sexual harassment and domestic violence cases that have been registered in India. since 2001 marriage culture the dowry is one of the conventional and ever emergence kind of sickness. which cannot be removed ever. using data visualisation technique by a language we will show how many cases have been registered in India in sexual harassment and dowry. we will also implement the several operations such as horoscope preferences income and statuses of the individual as per the data collected by the matrimonial data repository

- In recent years the product quality has been one of the crucial parts for every single industry. The conventional methods for assessing the product quality are very time consuming and also not having the optimal result however with the resultant in dynamic Technology movement. We have the concepts of machine learning and data science through this technique its become more efficient to assess or to predict any kind of thing efficiently. In this paper, we have explored several machine learning techniques for evaluating wine quality based on different metrics and properties related to wine quality. In this paper, we have also used several machine learning algorithms to rank the quality of wines and investigate why people make the wine taste more interesting. We have selected the features using the most popular machine learning techniques. We used different types of datasets for this particular study.