VOLUME 12, ISSUE 3, MARCH 2023

Abstract:  With increased technology development, governments and specifically urban managers require the most recent technology to make their smart cities safer. Intelligent transportation systems (ITS) have been highly incorporated within this area to improve effective smart city applications. A digital twin (i.e., a copy of a real-world construct) is required to manage a building structure and resources during smart city construction to optimize the overall perf ormance. This research objective can be achieved by incorporating big data techniques that maximize available resources with the help of a graphical processing unit (GPU) that can manipulate complex data successfully. The GPU integrates fuzzy rough set theory (FRST) and a multilayer perceptron neural model (MNM) to minimize the multi-classification problem during analysis. This neural model uses multiple layers that can understand the data structure and classify resources with minimal computational errors. It uses the AdaBoost learning parameter to minimize complexity while making decisions in smart city applications. This framework uses data from the Internet of Things (IoT) to manage resources and energy in a smart city. The FRST-enabled MNM approach explores the gathered data with appropriate forecasting accuracy while minimizing the running time and computation complexity and increasing the processing speed. Keywords: Smart City, Intelligent Transportation, Internet of Things (IoT), Big Data, Fuzzy Rough Set Theory, Graphical Processing Unit, AdaBoost.  

Abstract: The personal information which we post/share online is called a Digital Footprint. Most of us have a digital footprint over the internet be it knowingly or unknowingly. Technology and our personal information are getting intertwined as we become more and more dependent on technology for everyday activities. With basic information such as names, addresses, and phone numbers; personal information also includes one’s demographic location, interests, relationship status, and social media accounts that can be tracked easily. Teenagers nowadays are so engrossed with technology that they spend most of their time on social media. Relationship status, personal images, and videos are shared on an everyday basis. With a such wide variety of personal information being captured and exposed online, private life is not so “private”. This study proposes how digital footprints can impact an individual by measuring the discoverability of various types of personal information.

Keywords: OSINT, digital footprint, personal data, technology, cybersecurity, awareness, social media

Abstract: In the work, an automated skeletal maturity recognition system is proposed. It first accurately detects the distal radius and ulna (DRU) areas from hand and wrist X-ray images by a faster region-based convolutional neural network model. Then, a well-tuned convolutional neural network (CNN) classification model is applied to estimate the bone ages. We discussed the model performance according to various network configurations. After parameter optimization, the proposed model finally achieved 92% and 88% accuracy for radius and ulna, respectively.  Keywords: convolutional neural network; skeletalmaturity; classification

Abstract: Purpose of this application is to design, build and deploy a Hyperledger Fabric based Blockchain application namely “CBFT Application” having the ability to query from the banks network’s data that is available as part of the blockchain (Reading bulk data from the Blockchain), query any one of the banks network’s data that is available as part of the blockchain (reading individual record or data from the blockchain), add a new bank, customer, forex value data and verify that these values get added successfully into the blockchain (writing new records into the blockchain and its verification) and pay from any one of the banks’ customer account to any other bank’s customer account across the available banks in the network effectively using the applicable forex rates without any third-party involvement (cross border fund transfer (CBFT)). further verifying the successful transfer of the fund across the customer accounts.

Keywords: Blockchain, Hyperledger Fabric, Cross Border Fund Transfer, Bank, Forex.

Abstract: With the rapid advancement of blockchain technology in recent years, its application in scenarios requiring confidentiality, such as the health sector, has become encouraged and extensively discussed. This paper presents an architecture for protecting the privacy of stored health-related data. This paper presents an architecture to ensure the privacy of health-related data, which are stored and shared within a blockchain network in a decentralized manner through encryption with the RSA, ECC, and AES algorithms. To determine the impact of cryptography on the proposed architecture in terms of computational effort, memory utilization, and execution time, evaluation tests were conducted. The results primarily impact the execution time and the increase in computational effort for transmitting data to the blockchain. This is justifiable in light of the privacy and security offered by the architecture and encryption.

Keywords: blockchain; cryptography; DApp; health data; data privacy; encryption.

Abstract: An Ethereum blockchain-based pre-owned car application could offer several advantages over traditional methods of buying and selling used cars. By utilizing smart contracts, off-chain data storage, and a reputation system, the platform could provide increased transparency, security, and efficiency for buyers and sellers. However, it is important to note that this is a proposed methodology and further research and development would be necessary to fully implement such a system. Additionally, it is also important to consider any legal and regulatory challenges that may arise with using blockchain technology in this context. Overall, a blockchain-based platform for pre-owned car sales has the potential to revolutionize the way we buy and sell used cars, making the process more secure, transparent and efficient.

Keywords: Blockchain, Ethereum, Solidity, Pre-Owned Cars, Smart Contracts.

Abstract: Data is described in so many ways for the true understanding of data, and one of the methods to elaborate data is a data visualization. It is obvious that data can have different facts and figures, and the beauty of data visualization is that it can elaborate   data with the help of different visual elements such as maps, graphs, and charts. The good thing about this graphical representation is that it provides a nice view of the data to understand its outliers, patterns, and trends. A cryptocurrency dashboard will visualize live updated market data of cryptocurrency for different types of cryptocurrencies. A crypto dashboard is a digital platform that exists on a website or an application. Its purpose is to track your   cryptocurrency accounts and coins and monitor their current values and historical prices.

Keywords: cryptocurrency, dashboard, visualization.

Abstract: Peer-to-peer carpooling using blockchain is a decentralized approach that enables individuals to share their cars with others who are traveling in the same direction. Blockchain technology provides a secure and transparent way to handle transactions and eliminates the need for intermediaries. This paper proposes a peer-to-peer carpooling system that utilizes blockchain technology to facilitate transactions and provide a trustless environment. The proposed system would enable individuals to connect with each other and share rides without the need for a centralized platform. It also ensures that all transactions are recorded on the blockchain, providing transparency and security. The system would utilize smart contracts to automate the process of matching drivers with riders and handling payments. This approach could potentially reduce traffic congestion, lower transportation costs, and contribute to a more sustainable environment.

Keywords: Blockchain; peer-to-peer carpooling; ride sharing; decentralization

Abstract: The Risk Analyzer and Prioritizer tool is a software application designed to help organizations identify, evaluate, and prioritize potential risks that could impact their operations. The tool typically uses a combination of qualitative and quantitative risk assessment methods to analyze the likelihood and potential impact of identified risks. The risk prioritizer aspect of the tool involves assigning a priority ranking or score to each identified risk based on its level of severity and the organization's tolerance for risk. The tool may also provide recommendations for risk mitigation strategies, such as risk avoidance, risk reduction, risk transfer, or risk acceptance. Overall, the Risk Analyzer and Prioritizer tool can help organizations make informed decisions about risk management and allocate resources more effectively to mitigate potential risks. By using this tool, organizations can enhance their overall risk management processes and reduce the likelihood and impact of potential risks on their operations.

Keywords: Prioritizer, Analyzer, Risk, Mitigate.

Abstract: The addresses of Internet protocol (IP) are essential resource for the Internet.   An internet protocol l(IP) uniquely identifies every computer and device connect to the internet. Every device connected to the internet has an address. And each IP address uniquely identifies that device. The addresses are still assigned by using Internet Protocol version 4 (IPv4). IPv4 is the most widely used protocol on the Internet, and its address space is. applications and easy operation. IPv4 had been designed to cover all the network interfaces, however with growth of the number of devices (mobile, computer, server, routers, etc.) the reserve of assigned addresses is finished. To solve the problem of insufficient addresses, the IETF designed the next generation IPv6 protocol to replace IPv4, IPv6 has been deployed for providing new services and for supporting the internet growth. This study compares the key specifications of IPv4 and IPv6, contrasts IPv4 and IPv6 header’s fields, the structure of headers, explains advantages of IPv6 and disadvantages of IPv4, and why we are running out of IPv4.

Keywords: Include at least 4 keywords or phrases.

Abstract: Securing e-healthcare involves encrypting sensitive patient data, such as medical records, in a way that allows for search operations to be performed on the encrypted data without compromising the security of the patient's information. One way to accomplish this is through the use of homomorphic encryption, which allows computations to be performed on ciphertext, resulting in an encrypted output that can be decrypted to the same plaintext as if the computation was performed on the plaintext. Another way is through the use of searchable encryption, which uses a combination of encryption and data structures such as inverted indexes to enable keyword searches on encrypted data. These methods can be used to create secure systems for e-healthcare that allow authorized personnel to search patient data while ensuring that the data remains confidential and protected from unauthorized access. E-Healthcare systems are increasingly popular due to the introduction of wearable healthcare devices and sensors. Personal health records (PHRs) are collected by these devices and stored in a remote cloud. Due to privacy concern, these records should not be accessible by any unauthorized party, and the cloud providers should not be able to learn any information from the stored records. To address the above issues, one promising solution is to employ attribute-based encryption (ABE) for fine-grained access control and searchable encryption for keyword search on encrypted data. However, most of existing ABE schemes leak the privacy of access policy which may also contain sensitive information. On the other hand, for users' devices with limited computing power and bandwidth, the mechanism should enable them to be able to search the PHRs efficiently. Unfortunately, most existing works on ABE do not support efficient keyword search on encrypted data. In this work, we propose an efficient hidden policy ABE scheme with keyword search. Our scheme enables efficient keyword search with constant computational overhead and constant storage overhead. Moreover, we enhance the recipient's privacy which hides the access policy. As of independent interest, we present a trapdoor malleability attack and demonstrate that some of previous schemes may suffer from such attack.

Keywords: Advance Encryption Standard, E-healthcare, Security, Cloud Security, Attribute Based Encryption, Fine Grained Access Control.

Abstract: With the increasing globalisation and the quickening pace of technological advancement, the quantity of production and the ease of finding counterfeit products have increased to vast range levels. To deter counterfeiting of food, drugs, or luxury products, all sorts of industrial manufacturing and distribution companies are now seeking greater transparency in supply chain activities.. In order to detect fake goods in the supply chain system, this article offers a decentralized Blockchain-based application system (DApp). Due to the rapid advancement of Blockchain systems, it is now widely accepted that the records kept there is safe and unalterable. Therefore, the project that is being proposed here uses this concept to deal with the transfer of ownership of products. A customer can verify the distribution and ownership details of the products by scanning a Quick Response (QR) code generated by the DApp for each product linked to the Blockchain Index Terms:  Counterfeit, Supplychain, Blockchain, Ethereum, QR Code.

Abstract: IoT privacy risks and security vulnerabilities are emerging from a lack of basic security technology, despite the IoT's rapid development and widespread attention in academia and industry. The blockchain technique was proposed as a decentralized and distributed approach to guarantee security requirements and encourage the growth of the IoT and IIoT because of its decentralization and information disclosure. First, we briefly overview blockchain's overall design and highlight its most important features before discussing the security measures needed to fully realize the Internet of Things and the Fourth Industrial Revolution. Then, we delve into how blockchain's security features can be utilized by the IoT for Industry 4.0. To promote the features and benefits of the blockchain technique on IoT and IIoT platforms, we explain the most important blockchain-based IoT applications. Finally, suggestions are made to help future blockchain researchers and coders get started.

Keywords: IoT; Security; IIoT; Smart Home; Data Privacy; Smart City.

Abstract: The medical industry urgently needs to address issues such as secure storage, reliable sharing, access control and privacy protection. In this article, we propose EHRChain, a blockchain-based EHR system that uses an attribute-based homomorphic cryptosystem to solve the aforementioned problems. First, we designed a medical record storage solution based on blockchain and IPFS technology to achieve secure large-capacity medical data storage and reliable sharing. Second, we proposed an improved cryptographic primitive called SHDPCPC-CP-ABE. Our SHDPCPC-CP-ABE simultaneously realizes the functions of partially concealing ciphertext-based semi-policy and dynamic authority change. In addition, our regime achieves subject neutrality of forensic identification of medical disputes and fine-grained access control to medical data. Third, our system applies an additional homomorphic cryptosystem, the Paillier cryptosystem, with optimized parameters to protect patient privacy during the medical insurance claim process. Index Terms: Ethereum, Blockchain, EHRchain, Healthcare

Abstract: Social media sites such as Twitter have become an integral part of our daily lives. With the growing popularity of these sites, the problem of spamming has also increased, leading to a cluttered and irrelevant feed. To address this problem, we propose a machine learning-based approach to filter out spam messages from social media feeds. Our approach involves preprocessing the social media feed to extract relevant features such as message content, user activity, and metadata. We then use supervised machine learning algorithms such as Naïve Bayes, Random Forest, and Support Vector Machines to train our model on a labeled dataset of spam and non-spam messages. We evaluate the performance of our approach using various metrics such as precision, recall, and F1 score. Our experimental results show that our approach achieves high accuracy in detecting spam messages, with an F1 score of over 90%. We also compare our approach with other state-of-the-art methods and demonstrate its superior performance. Our machine learning-based spam filtering approach can help social media users to have a cleaner and more relevant feed, save time, and protect against potential phishing attacks. The proposed approach can be extended to other social media sites and can be integrated into existing social media platforms to provide users with a seamless spam filtering experience.

Keywords: Support vector machine, Phishing attacks, Random Forest, Naïve bayes, Microblogging, Computer-aided, Artificial neural network

Abstract: By obtaining capital and making loans, banks' core business model relies on financial intermediation (mortgage, real estate, and consumer and company’s loans). The latter is the biggest contributor to credit risk and is made up of two key components: loan approval and fraud. We will concentrate on loan approval using machine learning models in this post. Although banks can sell various items in our financial system, their main source of income comes from lines of credit. Therefore, they can benefit from interest on the credited loan. A bank's profit or loss is largely determined by the loans it makes, i.e. whether its customers repay the loans. Banks can reduce their non-performing assets by predicting defaults. This highlights the importance of studying this phenomenon. Based on previous research from this time, there are several ways to study the problem of default prevention. But since accurate predictions are key to maximizing returns, understanding how the different methods of work.

Keywords: Big Data, Machine Learning, Python, Logistic Regression, SVM, Decision Tree, Naive Bayes, Loan Prediction.

Abstract: Electronic voting (e-voting) is a digital method of casting and counting votes in an election. Blockchain, a decentralized digital ledger technology, has been suggested as a potential solution to the challenges of e-voting, such as security, transparency, and trust. This comparative analysis examines the use of blockchain technology in e-voting systems, comparing it with traditional e-voting systems and highlighting the advantages and disadvantages of each. First, we discuss the basic concepts of blockchain technology and e-voting; we analysed the advantages and disadvantages of blockchain-based e-voting compared to traditional e-voting. We also examine the challenges of implementing blockchain-based e-voting, including scalability, interoperability, and regulatory compliance. Finally, we consider the potential for blockchain-based e-voting to enhance the democratic process by increasing voter turnout, reducing fraud, and improving the integrity of elections.

Keywords: Blockchain, edge computing, network, storage, computation.

Abstract: Blockchain, the technology that powers cryptocurrencies, has garnered much interest. Numerous applications, including the smart grid and the Internet of Things, have embraced it. However, a sizable scalability hurdle constrains Blockchain's ability to support services with frequent transactions. On the other hand, edge computing was developed to expand cloud resources and services distribution to the network's edge. Still, it presently faces difficulties with decentralized management and security. The combination of blockchain technology and edge computing can provide a large scale of network servers, data storage, and validity computation close to the end while maintaining secure access to the network, computation, and storage spread at the edges. Despite the potential of integrated blockchain and edge computing systems, new security issues, problems with scalability improvement, self-organization, function integration, and resource management need to be resolved before wide-scale deployment. In this survey, we examine some of the work done to support the integrated blockchain and edge computing system and discuss the research issues. We list several crucial elements of the merger of blockchain and edge computing, including drivers, frameworks, enabling features, and difficulties. Finally, some more comprehensive viewpoints are investigated.

Keywords: Blockchain, edge computing, network, storage, computation.

Abstract: In day today’s World pollution is major issue in the country and also whole world. This paper presents a machine learning (ML)- based approach for forecasting air quality. Governments primarily employ air quality monitoring systems to regulate the release of harmful substances into the atmosphere. In addition to ensuring the population's general welfare and quality of life, this also helps to support the agricultural and industrial sectors. Based on the amount of PM2.5 in the gathered dataset, air quality Predicted.ML techniques such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and Neural Network (NN) are examined. A model is built using training data, and its performance is assessed using test data. Precision, recall, F1 score, and support are utilized as performance evaluation metrics. In places with a high population density, such major cities, air pollution is a serious issue. A range of emissions caused by human activities have an impact on the quality of the air, including driving, using electricity, and burning fuel. All businesses, from early-stage startups to major platform providers, have made machine learning and its components one of their main areas of Concentration. In the realm of machine learning, an artificial intelligence device gathers sensor data and learns how to behave.

Keywords: Air Quality Index, Machine Learning, Regression, Random Forest, Particulate Matter.

Abstract: Fracture is caused by a loss of bone mass (osteoporosis) that occurs as part of ageing. Lifting heavy- weighted things or falling from higher altitude will cause crack in back bone. Spinal cord is first seven bone of our neck region. Fracture in spinal cord may lead to loss of sensory functions or lead to death. These factures are suspected by computed tomography (CT) which is critical to patient management. This paper is a review on various methods required for detecting cervical spine fracture in a most efficient and effective manner using deep learning. It provides a brief description about the popular techniques available for detecting fracture and also gives comparison on various classification methods that can be used in the process.  

Keywords: Medical imaging, Deep learning, Object detection, Classification, Cervical spine fracture, Convolutional Neural Network (CNN)

Abstract:  A desktop voice assistant is an artificial intelligence technology that enables users to interact with a computer using spoken commands. Similar to mobile voice assistants, desktop voice assistants use natural language processing (NLP) and speech recognition technology to understand and respond to user queries and commands. Desktop voice assistants are typically installed on personal computers, laptops, or other desktop devices, and can be used for a variety of tasks, such as searching the web, open emails, writing notes, and controlling other software on the computer. One of the main benefits of a desktop voice assistant is that it can increase productivity by allowing users to perform tasks hands-free and more efficiently. Desktop voice assistants can also help users with disabilities to navigate and interact with their computers more easily.

Keywords: Voice user interface, Speech recognition, Natural language understanding, Conversational AI, Virtual assistant, Smart assistant, Personal assistant.

Abstract: Land registry in India as well as in many parts of the world is very slow and cumbersome process. There are an also many intermediaries involved in the process of land registration. Developing a system that not only accelerate the process of land registration, but also make it easier for Buyers, Sellers and Government registrars to transfer the land ownership from seller to a new buyer, is only possible by creating a distributed system that store all the transactions made during the process of land buying. In this paper we'll try to explore the possibilities and problems solved by using a block-chain based system for land ownership transfer. The system that we are trying to implement is based on Ethereum's Block-chain that will store all the transactions made during the process of land ownership transfer. Using the concept of smart contracts of block-chain technology we can triggers various events like access of land documents to a land inspector and fund transfer event from buyer to seller after successful verification of the land ownership transfer. This system will solve the problems faced by all the three parties during the land registration and will also remove the intermediaries like property dealers. This system makes the process of land registration resilient and decrease the cases of fraud in the process. Using the system, validation of the lands is also possible as immutable transactions are being stored in the public ledger.

Keywords: Ethereum, block-chain, Secure Land Registy System.

Abstract: Vehicle Classification has wide applications in intelligent transportation and smart cities. Classification is crucial for an intelligent transportation system (ITS). Vehicle make and model classification technique is very useful. Make and model is a fine-grained information that can help officers uncover cases of traffic violations when license plate information cannot be obtained. Faster-RCNN and YOLO are two algorithms which are used for Object Detection and Classification. These algorithms work very well for classifying different types of vehicles. The various vehicles are classified into different vehicle classes. Initially, the dataset is made ready using the videos or converted images format. The dataset needs to contain the data which is of the predefined classes types. Secondly, the images or videos not used during the training are then used for the evaluation of vehicle classifier model. The main parameters that are used in the evaluation of the model include training time, the testing time, the vehicle classification accuracy, as well as the performance of the specific deep learning methods. Many of the datasets are used in the classification of datasets, it makes the evaluation of the classes of datasets more simpler and easier. The previous data could be pre-processed to generate the new datasets that could be used for the evaluation of datasets.  

Keywords: Vehicle classification; color classification; deep learning; convolutional neural network; Faster R-CNN, YOLO, VGG-16.  

Abstract: The term "virtual assistant" refers to a software agent that can carry out tasks or provide services on behalf of a person. Virtual assistants that may be accessed through online chat are occasionally referred to as "chatbots" in general or in relation to just those. The term "virtual assistant" (VA) refers to computer-simulated settings that can mimic physical presence in both the actual world and made-up universes. In order to construct an intelligent Virtual Personal Assistant (VPA), new technology could be used in a number of ways, with a focus on user-based data. The goal of this project is to provide technical information about virtual assistant technology, including its advantages and disadvantages in many contexts. The project focuses on virtual assistant types and structural elements of a virtual assistant system. This research paper explores the development and application of Personal Desktop Voice Assistants in various domains. The study focuses on the use of natural language processing and machine learning algorithms to enable voice-activated commands, and their ability to learn and adapt to individual user preferences. The paper reviews the current state-of-the-art in Personal Desktop Voice Assistants, including their capabilities, limitations, and potential applications. It examines the impact of these technologies on productivity, efficiency, and accessibility for individuals with disabilities. The research also considers the ethical and privacy implications of Personal Desktop Voice Assistants, including data collection, storage, and usage. It explores the need for transparency, consent, and accountability in the development and deployment of these technologies. The paper presents a case study on the integration of Personal Desktop Voice Assistants in healthcare, highlighting their potential to improve patient outcomes, reduce healthcare costs, and enhance patient satisfaction. Overall, this research paper provides a comprehensive overview of Personal Desktop Voice Assistants, their current state-of-the-art, and future directions. It highlights the potential benefits and challenges associated with the integration of this technology into various domains, and the need for responsible and ethical development and deployment.

Abstract: Since there are more and more cases of heart disease every day, it is important and concerning to anticipate any prospective problems. It takes accuracy and quickness to complete this difficult diagnosis. I will create a system that predict whether or not a patient will be diagnosed with heart disease based just on patient's medical history using a number of machine learning techniques, including such regression models, Random Forest, and KNN. The model is controlled in a very beneficial method to boost the accuracy of myocardial infarction prediction in each individual. Random Forest, KNN, and Logistic Regression are used in the suggested model, which has the advantage of predicting heart disease symptoms in a specific person with greater accuracy than previously used classifiers like naive bayes. These techniques will also show better accuracy than other classifiers like naive bayes. So, a great deal of pressure has been reduced by using the presented model to assess the possibility that the classifier will accurately and consistently detect cardiovascular disease. This experiment teaches us a lot that we can utilise to forecast who will develop heart diseases.

Keywords: Random Forest, KNN, Logistic Regression, Machine Learning, Prediction.

Abstract: Conventional network access is tedious, costly, and cumbersome in nature. The answer for this issue can be a distributed (P2P) document sharing framework. In distance, this interaction has an incredible breadth as it gives a solid organization between the understudies, scientists, and resources of a similar local area. These days far off schooling is exceptionally normal through which anyone can overhaul their capability or procure information in different fields from anytime and anyplace. This framework is especially made for individuals who are living in remote and provincial regions, actually tested and working individuals and so forth. Distributed document sharing framework being the least expensive will give them the right stage to assemble information, efficient and easy to use. This cycle would assume a significant part in future internet providers for distant training. Cell phones are becoming multifunctional and simple to utilize, so why not make a distributed document dividing framework among the cell phones making it simpler.

Keywords: Peer-to-peer, File Sharing, Android, File Transfer.

Abstract: DoCure is a digital health platform that provides patients with a secure and convenient way to maintain their health records. With DoCure, patients can easily store and access their medical history, lab results, and other important medical documents. By having all of their health information in one place, patients can make informed decisions about their health and work with their healthcare provider to develop effective treatment plans. DoCure is designed with privacy and security in mind, ensuring that patient data is kept safe and confidential.

Keywords: health records, digital health platform, medical history, lab results, healthcare provider, informed decisions, privacy, security.

Abstract: Users can talk in real time via the internet using software tools called real-time chatting programs. Because of social media’s growth and the demand for immediate communication, these applications have grown in popularity. Users of real-time messaging apps have access to several capabilities, such as the ability to send text messages, emoticons, and multimedia files. Users of these programs can also build groups where several users can converse with one another simultaneously. Real-time chat programs provide a lot of accessibility, which is one of their main advantages. Users may more easily connect with one another no matter where they are because of the fact that they can be utilized on a variety of devices, including smartphones, tablets, and desktop computers. Real-time chatting programs have also transformed how individuals communicate, allowing businesses to interact with clients in a more effective and efficient manner. Also, these programs enable people to maintain relationships with friends and relatives beyond geographical borders. Index Terms: Real time Chat Application.

Abstract: : Blockchain technology would make it possible for people to have ownership over their data, including their academic credentials, career history, and other relevant information. Employers and educational institutions can have confidence in the information provided since the validity and integrity of the data can be confirmed using blockchain technology. While there would be no longer be a need for middlemen like third-party verification services, blockchain technology also has the potential to boost efficiency. Verifying academic and job records would take less time and money thanks to this, improving the effectiveness and efficiency of the procedure. Blockchain technology may also improve the recruiting process by enabling businesses to swiftly and easily confirm the credentials and work history of prospective seekers. This may assist to simplify the hiring procedure, cutting expenses and empowering businesses to make wiser hiring choices.

Abstract: Underwater image processing has been always a very challenging problem. Under the effect of environmental factors, underwater images are exposed to some problems, such as colour cast, low visibility, and few edge details. Image Improvement includes numerous operations similar as discrepancy stretching, noise trimming, mock coloring, noise filtering etc. To improve the view of images. Underwater images bears mediocre because of nature of luminosity. When light enters into the water it got replicated , Noticed and scattered as water is denser medium then air, so the amount of luminosity sink when it enters from breeze to water and got dispersed in different tracks. Scattering causes the blurring and reduces the color contrast. So a novel approach is proposed to enhance underwater images by gamma correction to improve the brightness of dimmed images. The dark channel prior clear haze and noise effect, providing better observable quality. At the final stage, the contrast limited adaptive histogram equalization contrast and brightness of dehazed image. The enhanced fuzzy-free, natural appealing output can be used for display and analysis purpose.

Keywords: Pre-processing, Gamma correction, Dark channel prior, Contrast Limited Histogram equalization.

Abstract: In an intelligent transportation system, a vehicle detection and counting system is critical, especially for traffic management. Using computer vision technology, proposes a video- based method for vehicle detection and counting. To find foreground objects in a video sequence, the proposed method employs background subtraction. Several computer vision techniques, such as thresholding, hole filling, and adaptive morphology operations, are then used to detect moving vehicles more accurately. Finally, a virtual detection zone is used to count the number of vehicles.

Abstract: The issue of transparency and security is very paramount in any organization, therefore the intention to provide a reliable, secured, transparent and decentralized solution is achieved by developing a blockchain-based crowdfunding web application. This crowdfunding application is not just like any other application which just allows people to invest their money, but this platform also gives an assurance to the backers that returns will be guaranteed. This will be a multi-user application with three different types of users: Admin, Backers, and Start-up. Admin can approve start-ups for listing. Start-ups can view the status of approval of their projects and funds raised in real-time. Backers can view the progress of the projects that they are funding as well as the general information about other projects listed on the application.

Keywords: Crowdfunding, Blockchain, Decentralize, Smart Contract, Ethereum.

Abstract: This research paper provides an overview of the current state of machine learning in surface defect detection for industrial product quality inspection. The study examines traditional machine vision techniques, as well as the latest advancements in deep learning-based approaches. The paper also highlights common challenges faced in the field and presents potential solutions to these challenges. The study concludes with an overview of datasets used for evaluating industrial surface defect detection methods and a comparison of the latest research. This information serves as a valuable reference for future research and development in this field.

Keywords: Surface defect detection, Industrial product quality inspection, Machine vision techniques, Deep learning, Evaluation datasets.

Abstract: A keylogger is a type of software or hardware device that enables the recording of all keystrokes made on a computer or mobile device keyboard. Essentially, it allows for the monitoring and tracking of user activity, which can be used for security and surveillance purposes. Keyloggers have both legitimate and illegitimate uses. For example, some organizations use them to monitor employee activity, while others use them to steal sensitive information such as login credentials, credit card numbers, and other personal data. Unfortunately, keyloggers can be used for malicious purposes, as well, which means they can pose a significant security risk to individuals and organizations alike. One of the primary challenges with keyloggers is their ability to operate surreptitiously. They are designed to work in the background, without drawing any attention to themselves, and typically do not exhibit any visible signs of their presence. As a result, they can be challenging to detect and remove from an infected system.

Keywords: Keylogger, hooking, signature-based, malware rootkits, anomaly based, OS, API.

Abstract: Driver drowsiness is a major concern in road safety, leading to numerous accidents and fatalities worldwide. Consequently, the development of accurate and reliable drowsiness detection systems is critical to enhance road safety. Recently, various machine learning (ML) algorithms have shown great potential in detecting drowsiness using various physiological and behavioral signals. Several fatal and non fatal injuries can be prevented if the drowsy drivers are warned in time. According to many recent surveys, around 21% of road accidents take place due to the driver’s drowsiness. Many of these collisions lead to loss of life, property or infrastructure; endangering not only the driver but also other individuals. The transport businesses that employ overnight driving have been seen to be at the highest risk. Driving during the night can lead to severe fatigue and drowsiness even when the driver is well-rested. As a result, many automobile industries have begun to take steps to implement driver drowsiness detection systems. Existing systems implemented by top car brands consist of the ECG machines holstered within the sides of the driver’s seat. However, these have proved to be uncomfortable. Various Machine learning and deep learning models can be used to detect fatigue and drowsiness and potentially reduce the dependency on physical devices used in ECG.

Keywords: Drowsiness detection, Classification, Machine Learning, Deep Learning.

Abstract: Shortlisting qualified candidates from a large pool of resumes is a difficult problem for recruiters in the current recruitment process. Manual screening and keyword matching are the mainstays of traditional resume shortlisting techniques, which might result in biased judgements and leave out qualified candidates. In order to improve the efficiency of the resume shortlisting procedure, we suggest a resume shortlisting model in this research that makes use of text processing methods and TF-IDF. Our suggested model performs better than conventional approaches, offering greater accuracy and fewer false positives, making it a more economical and effective recruitment process solution.

Keywords: Machine Learning, Text Processing, Natural Language Processing, Tokenization, TF-IDF.

Abstract: Crypto system is responsible for encrypting the user’s data and provide a secure mechanism to store it in a virtual drive. This virtual drive will be created by the system for the particular user for the very first while using the system. This system will provide limited storage area where the data can be saved. As we can say that, it’s a cloud storage medium where data can be accessed from any location. This system will also enable you to synchronize your desktop or laptop while using this crypto system.

Keywords: Encryption, Decryption, Documents, Java, Cipher, Text.

Abstract: The goal of this project is to provide a service mechanism that generates revenue for both the cloud provider and its numerous consumers. We analyse the interaction between the cloud service provider and its customers from a game theoretic point of view. We presume that most every user's approach is influenced by the cloud provider's plan. The goal of the cloud provider is to choose suitable servers and set up a request allocation mechanism that satisfies consumers while using less energy. We add a controlling parameter and choose the best request allocation approach in order to approximate the server selection space. Based on the cloud provider's strategy, we create a utility function for each user that combines net profit and time effectiveness, and we aim to optimise this value. The suggested service mechanism has potential advantages for both the cloud service provider and its clients. The cloud provider may save energy expenses and boost revenue by picking the right servers and allocating requests effectively. Shorter job completion times and maximising net rewards are further advantages for users. Our approach considers the interdependence of the strategies of the cloud provider and its users and seeks to optimize the profits of both parties. By designing a service mechanism that incentivizes users to submit requests during off-peak hours and provides appropriate server resources, the cloud provider can increase profit while providing high-quality services to its users.

Keywords:  Cloud computing, Cloud providers, Multiple users, Game theory, Utility functions, Profit optimization, Server selection, Request allocation strategy, Energy efficiency, Time efficiency, Controlling parameter, Iterative algorithm, Numerical calculations, Service mechanism, Off-peak hours

Abstract: An NFT (Non-Fungible Token) image generator is a tool that allows users to generate unique, digital images that can be stored and traded as NFTs on blockchain technology. The images generated can range from simple illustration to complex digital artwork and can be bought and sold as one-of-a-kind collectibles, with their own secured and recorded on the blockchain. They are one-of-a-kind, verifiably owned and their ownership is recorded immutably on the blockchain. An NFT (Non-Fungible Token) image generator is a platform that creates unique, digital images or artworks that can be tokenized and traded as NFTs on blockchain technology. NFTs will hasten the expansion of cryptocurrencies outside the financial sector and provide fresh perspectives and ideas from a variety of producers, artists, digital goods collectors, developers, and others.

Keywords: Non-Fungible Token, Blockchain, Art Work, Artists, Cryptocurrency.

Abstract: An NFT (Non-Fungible Token) image generator is a tool that allows users to generate unique, digital images that can be stored and traded as NFTs on blockchain technology. The images generated can range from simple illustration to complex digital artwork and can be bought and sold as one-of-a-kind collectibles, with their own secured and recorded on the blockchain. They are one-of-a-kind, verifiably owned and their ownership is recorded immutably on the blockchain. An NFT (Non-Fungible Token) image generator is a platform that creates unique, digital images or artworks that can be tokenized and traded as NFTs on blockchain technology. NFTs will hasten the expansion of cryptocurrencies outside the financial sector and provide fresh perspectives and ideas from a variety of producers, artists, digital goods collectors, developers, and others.

Keywords: Non-Fungible Token, Blockchain, Art Work, Artists, Cryptocurrency.

Abstract: The Automatic Ventilator is a controllable, automated add-on solution to the existing and widely available Bag Valve Mask. The device compresses the BVM with a mechanical system that is able to provide consistent and accurate ventilation with positive-pressure. This solution exists within the top range of high-acuity limited-operability (HALO) ventilator solutions with an a priori design to produce volume and pressure cycled ventilation that includes positive end-expiratory pressure (PEEP) and enriched oxygen sources. In this situation of COVID 19, many people are being exposed to corona virus, resulting in difficulty in breathing and a drop in oxygen percentage of blood. A mechanical ventilator is playing a vital role in tackling this situation but the ventilation process is neither readily available nor affordable. The idea behind this work is to propose a simplified design of a mechanical ventilator to reduce the cost and automate the Mechanical ventilation process. The simplified design, it's working, and required components are elaborated in this paper. The simulation of the proposed design is made in MATLAB/Simulink platform which is also discussed below. Simulation results are promising and precise which allows the study on ventilator model without jeopardizing the life of human subjects as in clinical approach and hides the complexity of computational models from the user. Furthermore, advancements in this model are done by the machine learning approach.: Successful weaning from prolonged mechanical ventilation (MV) is an important issue in respiratory care centers (RCCs. This study aims to utilize artificial intelligence algorithms to build predictive models for the successful timing of the weaning of patients from MV in RCCs and to implement a dashboard with the best model in RCC settings. A total of 670 incubated patients in the RCC in Chi Mei Medical Center were included in the study. Twenty-six feature variables were selected to build the predictive models with artificial intelligence (AI)/machine-learning (ML) algorithms. An interactive dashboard with the best model was developed and deployed. A preliminary impact analysis was then conducted. Our results showed that all seven predictive models had a high area under the receiver operating characteristic curve (AUC), which ranged from 0.792 to 0.868. The preliminary impact analysis revealed that the mean number of ventilator days required for the successful weaning of the patients was reduced by 0.5 after AI intervention. The development of an AI prediction dashboard is a promising method to assist in the prediction of the optimal timing of weaning from MV in RCC settings. However, a systematic prospective study of AI intervention is still needed. Keywords: Ventilator, Bag Valve Mask, Sensors, Arduino Controller, IoT Module.

Abstract: Vehicular Ad-hoc networks are type of Mobile ad-hoc networks. In MANETs the vehicles moves in roads and their velocity depends on the road traffic and some restrictions that affected the network. The main aim of VANETs is to maintain the communication between vehicles so the data can be sent efficiently move from one node to another. Various types of Routing protocols are used for efficient routing of data from one place to another. One another technique is used for routing is Swarm intelligence. In this paper various swarm intelligence protocols are defined that should be used for efficient routing and produces better results. All protocols are compared and best routing protocols is chosen so the efficient results should be produced.  

Keywords: MANET, VANET, Vanet routing protocols, SI & their routing protocols.

Abstract: The Indian economy relies heavily on agricultural productivity. Hence, both the environment and people greatly depend on the contribution of food and cash crops. Many diseases claim the lives of crops every year. Many plants perish as a result of poor diagnosis of these diseases and lack of awareness of the symptoms and cure. The overview of plant disease detection using various algorithms is provided by this work. Here, a CNN-based technique for identifying plant diseases is suggested. On sample photos, simulation research and analysis are carried out in terms of time complexity and the size of the infected area. It is carried out using image processing methods Cases have been fed to the model, out of which some cases are of diseased plant leaves Test accuracy is obtained as 89.80%.

Keywords: CNN Algorithm, Open CV, Keras, TensorFlow, Image Segmentation

Abstract: In the past few years, e-commerce companies have taken control over the commercial sector. As a result the shipment business had to expand significantly to keep up with the e-commerce industries. Majority of customers prefer online method of ordering things and getting them delivered with minimum time period which cause excessive usage of traditional freight companies like FedEx or DHL, Amazon, or eBay. Concurrent increase in shipping and cyber related systems would affect the operations which in turn would require additional maintenance. Due to large-scale of operations ongoing, physical servers could hamper both the speed and quality of administration for such a vast amount of data. To improve the capabilities and features of the shipment management system cloud platform is used which will reduce the operating costs as well as increase the efficiency of the e-commerce industries. Shipment solutions are not fixed to a particular location and must be made accessible anywhere around the globe. Cloud solution will be more catered to meet the expanding shipping business management requirements and the security of data.

Keywords: Cloud, Shipment, Logistics, Cloud Shipping, Distribution.

Abstract: For data storage and sharing, cloud computing offers great performance, accessibility, and cheap cost, resulting in better resource usage. Cloud service providers compromise an abstraction of limitless storage space for clients to mass data in cloud computing. The patient's medical information and medical background are contained in the electronic health record. The owner of the data has the power to encrypt files and restrict access to only registered users. Users could be added, and keys could be distributed for user authentication. A random key generation process will be used to create the key. Data is encrypted before being stored in the cloud using AES, which is implemented to offer security measures. We offer role-based authentication for access to medical data.

Keywords: Medical Record Sharing, Advance Encryption Standard, Role Based Access Control, Attributes Based Access Control.

Abstract: In recently cloud data storage increasing interest from both industry and academia due to its efficient and affordable Management. Service providers take on storage data and sharing mechanism as services are provided over an open network that protects user privacy and data confidentiality. The Encryption method is used for prevent sensitive data from being compromised. However, the actual requirement to just encrypt the data (using AES for example) will not completely solve the data management needs. In addition, to prevent EDOS (Economic Denial of Sustainability) attacks, which are carried out to prevent users from using  the service, robust access control of download requests should be considered. The control access in the cloud storage here we can develop over control mechanism download requests as well as data access without compromising efficiency or security. This article      designs the two dual access control systems, each used for conscious environment. An experimental and safety analysis of system  is also presented.

Keywords: Cloud data sharing, Advantage of cloud capacity, Control, Attribute based encryption.

Abstract: Criminal investigations are complex and require law enforcement agencies to gather and analyze large amounts of data to identify suspects and solve crimes. Traditional approaches have relied on human intuition and experience, which can be time-consuming and prone to errors. With advancements in technology, there is an opportunity to improve criminal investigations by using data-driven approaches. This research proposes a criminal investigation tracker with suspect prediction using machine learning techniques to improve the accuracy and efficiency of criminal investigations. This paper reviews previous studies that have used machine learning algorithms in criminal investigations and presents our proposed methodology, which involves the use of a criminal investigation tracker that integrates data from various sources such as criminal records, social media, and crime scene evidence. We discuss the machine learning algorithms that will be used and the performance metrics that will be used to evaluate the system. Finally, we conclude that our proposed system has the potential to improve the accuracy and efficiency of criminal investigations.

Keywords: criminal investigations, machine learning, suspect prediction, data-driven, crime scene evidence

Abstract: The goal of this thesis is to address design and development issues in the e-commerce platform and its recommendation system. The fact that Recommendation Systems are used as part of more complex applications and affect user experience through a variety of user interfaces adds to their complexity. However, research has almost entirely focused on the ability of recommendation systems to produce accurate item rankings, ignoring the security breaches and privacy invasions that occur as a result of the use of user cache memory from various websites. We propose a new approach that uses only a small portion of the user's cache to recommend something to the user.  

Keywords: Machine learning, Recommendation system, E-Commerce, Web Development

Abstract: Vulnerability Assessment and Penetration Testing (VAPT) is an essential aspect of information security in today's increasingly digital world. As organizations rely more and more on technology to store and manage sensitive data, the risk of cyber-attacks increases. VAPT is a comprehensive approach to evaluate the security of an information system, identify its vulnerabilities and determine the potential impact of a potential attack. This study aims to provide a comprehensive overview of VAPT, its objectives, methodology, expected outcomes, and advantages. The objectives of VAPT are to identify potential security weaknesses, assess the risk of an attack and make recommendations to improve security. The methodology of VAPT typically involves several stages, including planning and preparation, scanning, analysis and reporting. Planning and preparation involves defining the scope of the assessment, identifying the target systems, and determining the testing methodologies to be used. Scanning involves using automated tools to identify potential vulnerabilities, while analysis involves manual verification of the findings and determination of their impact. The final stage of VAPT is reporting, which includes documenting the results and presenting recommendations for improvement. The expected outcomes of VAPT include improved security awareness, identification of potential security weaknesses, and identification of areas for improvement. The advantages of VAPT include improved risk management, cost savings through early detection of vulnerabilities, and improved compliance with regulatory requirements. In conclusion, VAPT is a critical aspect of information security, and organizations should prioritize it as part of their overall security strategy. By conducting regular assessments, organizations can minimize their risk of cyber-attacks, reduce their exposure to security threats, and improve their overall security posture. This study provides a comprehensive overview of VAPT and serves as a reference for organizations looking to improve their information security.

Keywords: Vulnerability Assessment, Penetration Testing, VAPT, Information Security.

Abstract: Nowadays, dependency on banking in the virtual world has been increased to the peak position. To make it consistent advanced technologies should be used. As OTP is currently used worldwide for security purposes, it can be overruled by QR code. Main advantage of QR code over OTP data storage.OTP can only confirm that the user is authorised user and not some third party is involved in this transaction while QR code not only confirms the authorised user but QR code itself can store information such as transaction id, transaction date, time and also amount of transaction. So, there is no need of explicitly keeping track of transaction every transaction. Aim of this paper to enhance the functionality of ATM machine using android application. Proposed system is combining the ATM and mobile banking and minimizes the time of withdrawing cash from ATM. This will increase the speed of transaction almost three times fast; could have excellent impact on customer's satisfaction. With the help of QR code information get encrypted so it also increases security. As the population increasing ATM queues will be longer day by day. By implementing proposed system current system will not hampered, by doing some minor changes in existing system it will be possible to get cash within seconds. According to analyst report, cost of transaction using mobile application is almost ten times less than ATM and about fifty times less, if physical bank branch used.

Abstract: The Inventory Management System aids us in streamlining the logistical management of our products and automates a variety of operations such as purchasing, ordering, pricing, storing, assembling, shipping, and delivery. It also eliminates the need for human labour while increasing productivity, decreasing costs, and saving time. It provides useful insights to help you accelerate your company's success. It is critical for any business to keep the right amount of inventory on hand. Tracing assets from storage, warehousing, dealing, transportation, and organisation takes a significant amount of time, labour, and effort. As a result, a cloud-based inventory management system aims to reduce costs, increase capital efficiency, and improve customer satisfaction, all of which benefit the supply chain in terms of operational effectiveness and cost savings. Although there are some concerns about cloud security, it is also true that the cloud has been safeguarded by network security experts to protect our data from catastrophic breaches. We can feel secure knowing that our data is safe behind a wall of data protection solutions and procedures while still being immediately accessible to those who require it by transitioning to cloud-based inventory management. It intends to keep all inventory data and assist them in more effective inventory management.

Keywords: Cloud, Inventory, Sales, Ordering, Pricing

Abstract: Quora question pair similarity is a common problem in natural language processing that can be tackled using machine learning techniques. The goal is to identify whether two questions on Quora are similar or not, based on their semantic meaning. One approach to this problem is to use a neural network-based model, such as a Siamese network, which can learn a feature representation of each question and then compute a similarity score between them. Another approach is to use traditional machine learning algorithms, such as logistic regression or support vector machines, to classify pairs of questions as either similar or not. To train these models, you will need a large dataset of question pairs labelled as either similar or not. You can obtain such a dataset from Quora itself, by extracting pairs of questions that have been marked as duplicates by Quora users. Once you have trained and validated your model, you can use it to predict the similarity between new pairs of questions on Quora, which can help improve the user experience and ensure that high-quality answers are provided to users.

Keywords: • log-loss • Binary Confusion Matrix

Abstract: : data compression is a type of data compression that preserves all of the original data. This is achieved by identifying and removing redundancies in the data without sacrificing any information. Lossless compression is often used for data that cannot afford to lose any information, such as medical records, legal documents, or financial data. This type of compression can also be beneficial for archiving large amounts of data or for transmitting data over networks with limited bandwidth.

Abstract: A security tool is called a honeypot help to spot and stop unwanted behavior on a computer or network. In essence, it is a trap that is set up to entice attackers by simulating weak systems or sensitive information, and then watching and analyzing their behavior. A honeypot's objective is to acquire details about the methods, tactics, and techniques used by attackers so that the network's overall security can be enhanced. In addition to identifying and isolating compromised systems, honeypots can be used to divert attackers away from more valuable systems. Security experts and researchers utilize honeypots to better understand the tactics and motives of attackers. They are able to acquire data that will help strengthen network security, as well as to detect and monitor novel sorts of threats. There are various kinds of honeypots, such as low-interaction ones that just imitate a tiny section of a system and high-interaction ones that simulate an entire system. Low-interaction honeypots are frequently simpler to install and keep up, but they reveal less about the attacker's activities. On the other side, high-interaction honeypots offer more comprehensive data but demand more resources and are more difficult to set up and manage. In general, a honeypot is a useful tool for enhancing network security and guarding against cyberattacks. IndexTerms – Honeypot, sockets, TCP, UDP Honeynet, Honeywall, Intrusion Detection

Abstract: Food waste has been increasing at an unprecedented rate in recent years, posing a threat to economic growth factors. This has a significant impact on the agricultural processing industries. Because food recycling is a difficult task, we are focusing on food waste in the workplace, weddings, and other events in this project. This web application is used to manage food waste in an efficient manner. People throw away a lot of food every day. As a result, we must address the issue of food waste online. In general, we are automating the food waste process. Food waste is a growing global problem that has negative consequences for the environment, economy, and society. To address this issue, a comprehensive food waste management system is required. This system involves reducing food waste at the source, recovering and redistributing edible food, and diverting non-edible food waste from landfills through composting and anaerobic digestion. The implementation of such a system necessitates collaboration among stakeholders such as governments, businesses, and individuals, as well as the adoption of innovative technologies and policies. We can help alleviate food insecurity and promote social equity by reducing food waste.

Keywords: Leftover Food, Food donation, Unused Food Supply

Abstract: This research paper explores the importance of metadata in data management and presents a metadata retrieving system designed to assist in the organization and retrieval of digital information. The paper discusses the challenges associated with metadata retrieval, including issues related to accuracy, completeness, and consistency. The proposed system utilizes machine learning algorithms to automate the metadata retrieval process, reducing the time and effort required to locate specific data within a large dataset. The paper also presents the results of a case study demonstrating the effectiveness of the system in retrieving metadata from real-world datasets. Overall, this paper provides valuable insights into the role of metadata in data management and offers a practical solution to the challenges of metadata retrieval.

Keywords: metadata, retrieval, data

Abstract: As an alternative method of informing law enforcement organisations about offenses, online crime reporting methods have developed. This paper's goal is to present a thorough analysis of recent research on the efficiency of internet crime reporting systems. The study centres on the benefits and drawbacks of online crime reporting systems, the elements that affect citizens' willingness to use such systems, and the implications of such systems for law enforcement and crime prevention. According to the study, online crime reporting systems have a number of benefits, including speed, accessibility, and simplicity. The reliability of these systems, the accessibility of technological assistance, and the kinds of offences that can be reported online are some of the variables that affect their efficacy. Additionally, some citizens might favour the more conventional ways of reporting crimes, like contacting the emergency services or going directly to the police office. The analysis also demonstrates that internet crime reporting methods benefit both law enforcement and crime prevention. Law enforcement agencies can react to events more quickly and effectively by giving people the tools to easily and rapidly report offenses, improving public safety. However, the collaboration and teamwork between law enforcement authorities and the general public are essential to the success of internet crime reporting systems. Overall, the study indicates that online crime reporting systems have the potential to improve law enforcement and crime prevention, but their success relies on a number of variables that must be taken into account. To fully understand the potential of internet crime reporting tools and to determine how to increase their efficacy, more study is required.

Keywords: law enforcement, Crime prevention, Simplicity.

Keywords: Chatbot, Healthcare, Artificial Intelligence, NLP.

Abstract: In our city many times we see that the garbage   bins or dustbins placed at public places are overflowing. It creates unhygienic conditions for people. Also it creates ugliness to that place. At the same time bad smell is also spread. To avoid all such situations, this system proposed Garbage collection bin overflow indicator using IOT technology and also segregate waste in separate compartments are metal, organic or wet, non biodegradable waste. In this project, ultrasonic sensor is placed top of the dustbin, when the distance reaches to the minimum value, a alert will be sent to the respective Municipal & Government authority person. Microcontroller AT89S52 is used to perform a specific tasks. The UART is used for communication. Segregation details are display in LCD display. Generally, we see that they have a regular schedule of picking up these garbage bins or dustbins. This schedule varies as per the population of that place. It can be once in a day or twice in a day or in some cases once in two days. However we see that in case there is some festival or some function, lots of garbage material is generated by people in a particular area.  

Keywords: Bin overflow indicator, Segregate waste, Ultrasonic sensor, Microcontroller AT89S52, UART, LCD display, Internet of Things

Abstract: In recent times, there have been significant advancements in techniques for storing data across multiple clouds. This has resulted in users having a certain level of control over information leakage, as data is spread out across several cloud storage providers. However, the chaotic distribution of data pieces can still result in severe data loss, even with the use of multiple clouds. This article highlights the issue of a data leakage caused by the chaotic distribution of data in multi-cloud storage systems and introduces a solution called Store Simulation. This system aims to minimize customer data leakage across multiple clouds by keeping syntactically related data on the same cloud. The efficient creation of similarity-preserving functions is a key aspect of Store Sim. These functions use signatures, such as Min Hash and Bloom filters, to compute information leakage. Additionally, the system utilizes a clustering-based storage plan creation method to efficiently distribute data chunks across multiple clouds. To test the efficacy of this strategy, two real datasets from GitHub and Wikipedia were used. The results show that the Store Sim blueprint can reduce information leakage by up to 60% compared to no-plan placement. Furthermore, our investigation into system vulnerabilities reveals that this approach makes information attacks more challenging. Keywords Multi-cloud storage systems, Information leakage, Data distribution, Syntactic similarity Min Hash, Bloom filters, Clustering-based storage plan creation, Real datasets, Information attacks Data loss prevention.

Abstract:   Handwritten signature identification and verification has grown to be an active region of research in latest years. Handwritten signature identification systems are used for identifying the person amongst all customers enrolled within the gadget even as handwritten signature verification systems are used for authenticating a consumer via evaluating a specific signature with his signature that is stored in the gadget. This paper affords an evaluation for commonly used methods for pre-processing, function extraction and classification techniques in signature identity and verification structures, similarly to an assessment between the structures implemente in the literature for identification strategies and verification strategies in on line and offline systems with taking into consideration the datasets usednd outcomes for every system.

Keywords: Handwritten signature, verified signature          

Abstract: The main purpose of this project is to build a face recognition-based attendance monitoring system for educational institution to enhance and upgrade the current attendance system into more efficient and effective as compared to before. The current old system has a lot of ambiguity that caused inaccurate and inefficient of attendance taking. Many problems arise when the authority is unable to enforce the regulation that exists in the old system. Thus, by means of technology, this project will resolve the flaws existed in the current system while bringing attendance taking to a whole new level by automating most of the tasks.

Keywords: Arm 11 controller, Attendance, IoT.

Abstract: live streaming is the process where an individual would usually broadcast the content using an external application. And that application is call live streaming application or software. In this application the streaming could be conducted both on mobile application as well as the desktop application. The Goal of this application is to make sure that every individual being able to provide a high quality stream even if one has a low end desktop or a smartphone device.

Keywords: Live Streaming, Cross-Platform Streaming, Live Sync.

Abstract: In the world, internet users’ numbers are increasing at the same time cybercrime is also increasing. Now, these days cyber-attack rate is high. There are various types of cybercrime. Steal the victim’s personal information like a username, password, credit details, users’ sensitive data, personal information, etc. Attacks by phishing emails, phishing messages, phishing URLs, and websites are the popular ways of the phishing attack. Social media and online gaming popularity increasing nowadays attackers are targeting these platforms for phishing- attacks.

Keywords: Cybercrime, Hacker, Target, Attack

Abstract: Natural language processing programs that detect duplicate queries have a requirement for an efficient way to determine how similar two very brief texts or sentences are. An illustration of this is a conversational agent or dialogue system with script methods, where the implementation of comparable sentences is crucial. Sentence similarity will also be used in internet-related contexts. Sentence similarity has proven to be one of the most effective methods for increasing the effectiveness of retrieving Web pages.

Keywords: Duplicate, Question, Paper, Detection, and NLP.

Abstract: This research paper explores the benefits of implementing SupremeWeb in web development for building responsive designs for high-end businesses. The paper begins by introducing SupremeWeb and its various features, including a responsive design, advanced search filters, personalized property alerts, online booking systems, and mortgage calculators. The paper then discusses the impact of SupremeWeb on businesses in various industries and highlights the key factors that need to be considered when implementing SupremeWeb in real-world scenarios. Specifically, the paper focuses on the implementation of SupremeWeb in High-End Real Estate Websites and discusses how it can be used to create visually stunning designs, advanced search filters, personalized property alerts, online booking systems, and mortgage calculators that cater to the unique needs and requirements of high-end buyers. The research paper concludes that SupremeWeb offers a powerful tool for businesses looking to build responsive websites that meet the needs of their customers. By leveraging the features offered by SupremeWeb, businesses can provide a superior user experience, attract more customers, and ultimately drive growth and profitability.

Keywords: SupremeWeb, web development, responsive designs, high-end businesses.

Abstract: Leakage and short circuit currents are common problems that can occur in electrical networks, including those found in household applications. These issues can lead to energy waste, leading to downtime in industries, damage to equipment, and even pose a risk of electrical shock or fire. Therefore, it is essential to identify and localize these issues in order to resolve them quickly and prevent further damage or hazards. RCD (Residual Current Device) and RCBO (Residual Current Circuit Breaker with Overcurrent Protection) are commonly used as safety devices to protect against leakage current and short circuit in electrical systems. However, these devices have limitations in their applications. This paper discusses the challenges associated with the diagnosis and prevention of leakage currents majorly and also short-circuit currents in electrical networks. Additionally, the survey paper explores prevention techniques using IoT (Internet of Things) and machine learning techniques to overcome these limitations.

Keywords: Leakage Current, RCD, RCBO, Micro-controller, IoT, Machine Learning.

Abstract: Abstract uses blockchain technology to reduce the efficiency and cost of fund transfers. Blockchain offers important properties such as record immutability and decentralization that apply to subsequent transactions. By eliminating intermediaries during transactions and speeding up the process, this process can represent a fundamental change in the way things are done. Ethereum aims to use blockchain technology to create a decentralized treasury transfer application. By following contract restrictions, the use of smart contracts facilitates the elimination of intermediaries. Index Terms: Blockchain, Smart-contract, Ethereum, Fund Transfer

Abstract: In police stations, there are records of crimes. Crime Records are unable to locate crimes and the offenders who committed them. To maintain the crime and criminal data under the current system, a FIR is used. It has less security and makes fraud simple to do. Each time, a manual update has been made to the record. This system's primary goal is to secure data utilising block chain technology. Using their authentication credentials, Crime Investigators can view the data form database. The reports, which are prepared by witnesses and police officers, are accessible to the investigator (writer). Investigators have the authority to edit data (i.e., update, remove, and so on), and this data aids investigators in speeding up their investigations and identifying offenders more quickly. Previous research has focused on the centralized handling of digital evidence, however if a centralized system server is breached, sensitive operational and investigation data may be exposed. As a result, there is a need to manage digital evidence and investigative information in a distributed system setting using block chain technology. Performance is reduced when massive amounts of data, such evidential films, are kept in a block chain because more data must be processed only once before being generated. As a result, we suggest three-tier block chain architecture, with hot and cold block chains for digital evidence. Information that changes regularly is stored on the hot block chain, whereas material that does not change, such as files, is saved in the cold blockchain. To assess the system, we compared the storage and inquiry processing performance of digital crime evidence across the multi-level block chain system's capacities. Keywords: FIR, Blockchain, Security, Cryptography.

Abstract: E- waste economy has been rapidly increasing across the world. A number of countries around the globe have already seen advancements in science and technology, which has resulted in the expansion of many economies. India is no unique. Speedy data processing, better corporate processes, and shortened turnarounds and distance hurdles, in addition to a higher standard of living are among the direct perks of these huge advances are A greater level of happiness is apparent in terms of convenience and simplicity, and the percentage at which day-to-day duties can be completed Digital devices, such as Laptops and smart phones have transformed the way individuals work. The devices are providing time and adaptability, letting us to remain connected throughout the day. These devices act as a link between the physical and the digital worlds. There are innumerable facilities available. Electronic gizmos have profoundly affected all of our daily lives and are considered as a symbol of luxury and deluxe. These phones are beneficial not only for career growth but also for individual growth. There aren't any major findings. Only a computer adept society could be born, advancements in areas like the medical field stretches beyond these aspects. The overview of various life-saving equipment is laying the foundation for a more happy and healthy existence. The underpinnings for Indian automated industry development began in the 1960s, when the country's space agency was being scheduled. Electronics was primarily utilized at the time. being employed to improve communications networks and complement defensive system in the nation's capabilities However, it starts early for this to get through.

Abstract: The kitchen is seen to be the heart of both traditional and contemporary residences. It's a place where people prepare their meals and where families gather to eat. Since the refrigerator is in the center of everything, it is crucial to our daily activities. The goal of this project is to transform an ordinary refrigerator into an intelligent one by enabling it to order food products and to establish a virtual environment where the user and the refrigerator may interact.

Keywords: ordering food, notifying the expiry date