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Review Paper

Privacy-preserving location data publishing using anonymization method

Publishing datasets plays an essential role in open data research and promoting the transparency of government agencies. However, such data publication might reveal users' private information. One of the most sensitive sources of data is geo-life datasets. Unfortunately, merely removing unique identifiers cannot preserve the privacy of users. Adversaries may know parts of the trajectories or be able to link the published dataset to other sources for the purpose of user identification. Therefore, it is crucial to apply privacy-preserving techniques before the publication of geo-life datasets. In this project, the proposed method is the MLA an enhanced anonymity framework termed k-anonymity algorithms to preserve the privacy of users in the publication of geo life datasets. MLA consists of 2 interworking algorithms clustering and alignment. Alignment: By formulating the anonymity process as an optimization problem and finding an alternative representation of the system. The clustering is able to apply machine clustering algorithms for clustering trajectories. The general approach is to implement one of the k-anonymity techniques and evaluate the privacy of the users to be compromised.

Published by: K. Shanmuga Raja

Author: K. Shanmuga Raja

Paper ID: V8I3-1387

Paper Status: published

Published: June 7, 2022

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Review Paper

The impact of digital marketing on customer acquisition cost

This paper evaluates the factors that have led to a rise in digital marketing and discusses its impact on various components of the sales funnel. It analyzes how the costs associated with it have dropped over the last few years. This phenomenon has been leveraged by several companies to reduce the cost of acquiring a new customer and accelerating business growth.

Published by: Maanya Sharma

Author: Maanya Sharma

Paper ID: V8I3-1384

Paper Status: published

Published: June 6, 2022

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Research Paper

Efficient cloud data storage and file management using AWS S3 bucket

In the world of IT, end-user data is considered to be the basis of everything. A huge amount of data is added every day to the system and a far greater amount of data is being modified every second. Everyone expects that storing of data should be on the go and that their data should be safe and secure. While keeping the data secure, the procurement of the same should be seamless and fast. To serve this purpose, one of the dominant and reliable, technologies of the 20th century has been provided by one of the many products of Amazon Web Services by the name of Simple Storage Service(S3) that can store and retrieve huge amounts of data from any form of application, be it web-based or mobile, at an incredible speed. The data stored in S3 uses a flat-file system that is easy to understand and implement. Amazon S3 (Simple Storage Service) provides object storage, that is built for storing and recovering any amount of information or data from anywhere over the internet. It provides this storage through a web services interface. It can also store different file formats up to 5 terabytes in size. The scope of this project is to establish easy upload/retrieval of files from AWS S3 storage using different compression techniques and perform file operations on it. This way, one will be able to check which compression technique works efficiently in terms of compressed data size and also if the original data or file is corrupted, compromised, or destroyed, a backup is available on the cloud to recover. The proposed methodology also targets a few of the limitations of the flat file system of AWS S3 and provides a solution in the form of directory structure which on implementation can result in more security and can tackle inconsistency even for huge databases.

Published by: B. Akhil Kumar, Dr. T. Uma Devi

Author: B. Akhil Kumar

Paper ID: V8I3-1379

Paper Status: published

Published: June 6, 2022

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Others

Image-based pothole detection using Machine Learning

Potholes can generate damage to vehicles which may lead to many accidents. Thus, accurately detecting potholes is one of the important tasks for determining proper strategies in ITS service and road management systems. Many attempts are made for developing a technology that can automatically detect and recognize potholes. One great solution is to utilize image processing techniques, as various sources of images are available, e.g., surveillance cameras, in-vehicle cameras, or smartphones. These image-based solutions help to detect and classify road damages. An image related to road damage includes objects such as potholes, shadows, lanes, and cracks, so it is hard to detect a specific object. In this paper, we propose an image-based pothole classification model. The proposed method converts RGB image data, including potholes and other objects, to grayscale to reduce computation time. It detects all objects using an object detection algorithm. We are using Gaussian and median filtering to reduce noises in the image. We use k-means clustering and the YOLO algorithm for segmentation. We are using CNN algorithm for image classification. It will show if the road has potholes or not.

Published by: Dhanalakshmi M., Sharmila . A, Reena . R

Author: Dhanalakshmi M.

Paper ID: V8I3-1378

Paper Status: published

Published: June 4, 2022

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Others

Fog removal in an image using fuzzy c-means and active contour segmentation

Edge-maintaining smoothing is a picture processing approach that smooths away textures whilst keeping sharp edges. Image de-noising is the approach to lessen noises from corrupted pics. The goal of image denoising is to enhance the evaluation of the picture or notion of records in pics for human visitors or to offer higher output for different automatic picture processing techniques. The severe risk of air pollutants to human fitness makes air first-rate awareness of public attention, and effective, well-timed air first-rate tracking is vital to pollutants manipulation and human fitness. This paper proposes a deep getting to know and picture-primarily based totally version for air first-rate estimation. The noise introduces itself into a picture by changing a number of the pixels of the unique picture through new pixels having luminance values close to or identical to the minimal or most of the allowable dynamic luminance range. Preprocessing an image is a good way to adjust the picture for similar classes and segmentation

Published by: Abirami S., Kaviya.P, Reena.R

Author: Abirami S.

Paper ID: V8I3-1382

Paper Status: published

Published: June 4, 2022

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Research Paper

Artificial Intelligence: Based Voice Assistance

Technological advancements in Artificial Intelligence (AI) are among the most recent to arise, carrying with it difficult and innovative features that are increasing at a rapid pace. While it appears that these technologies are becoming extensively accepted, some people do not want to use them in specific situations. In fact, its been studied extensively for many decades, and there are a plethora of generic models available in literature that explain how humans respond to new technological developments. The development of more special model for new technologies different properties, on the other hand, appears to be required. Using the information gathered from this research, we have constructed a concept model that includes a new scheme performance construction known as "interaction quality," which we believe is more accurate in depicting the deployment of artificial intelligence-based innovations. In addition to the double our model, we make use of such a voice-activated assistant to help us with our research.

Published by: Akash Keisham, Ratikant Dehury, Albin Sunny, Amit Kumar

Author: Akash Keisham

Paper ID: V8I3-1205

Paper Status: published

Published: June 3, 2022

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