VOLUME 10, ISSUE 11, NOVEMBER 2021

Abstract: As SARS COVID is continues to spread in the world also in India as well, the growth rate of detection of COVID cases might be non-exponential but the actual cases and data and its effect towards the new generation especially in the case of children, the impact is a very serious issue. The current situation not only affects the economic and health condition of the country but also in the psychological context to the whole society across the nation. In the situation of a complete lockdown, a kind of restriction to the children for there open movements may be restricted from playing, schooling, any kind of physical contact with outsiders, socialization are all directly or indirectly leading to a more isolated behavioral impact towards the brain or mindset of the children. In this paper, we have shown some real-time experiments and observations with the help of some predictive analysis and algorithms which clearly shows the impact of COVID in children as a real case of Psychosocial Disorder.

Keywords: Algorithm, COVID, Education, Machine Learning, Psychosocial Disorder.

Abstract: Education is the major aspect and basis of foundation development in any country. Education directs the right path as well as to build a good human character with all aspect of life. In 2018, India ranked 40th with the score 41.2. In the year 2019, India was on 35th rank on the overall index with a score of 53. This score was based on policy environment, teaching environment and socio-economic environment. National Education Policy NEP-2021 is mainly focused on skill based education system with more flexible learning for the students. Digitization is a way for speed up of the learning process of the students. In this paper, we have analyze the Indian education system in the context of auto digitization and decentralized control through different machine learning data analysis, prediction, feature extraction, classification, visualization tools.

Keywords: Algorithm, Decentralized Education, Digitization, Machine Learning.

Abstract: "Fashion is the field where we create dreams" And " Photography is something that inspires dreams". To get along with the dreams , we are in a time span where we get technological support the most.The technology is playing a major role in our everyday lives. With this technological development, big opportunities are being created for many industries to grow economically in a short span. When coming to the world of fashion and photography, after the debut of the digital era there is a huge decline in the use of old production methods. We are living in the period where time values more than money and the people are progressing behind technology. This helps in the frugality of both money and time. Currently, most of the people prefer online platforms rather than face to face meet ups. Especially,the ongoing pandemic has constructed a great path to this digitalism. In such a manner that an individual can connect worldwide with the concept of networking. This clearly indicates that the future of fashion and photography depends on technological advancements like 4.0.

Keywords: Fashion, Photography, Technology, Future

Abstract: Routing in Mobile Ad hoc NETwork (MANET) is an important and researched problem in the world. Routing significantly affects network performance. In this paper, we compare performance of the Optimized Link State Routing Protocol with Link-layer Feedback(OLSR-FB) that is an improved protocol of OLSR and the Ad hoc On-Demand Distance Vector Routing (AODV) in terms of Packet Delivery Fraction, Routing overhead and Nomalize Routing Load. Simulation results show that AODV’Packet Delivery Fraction is more than OLSR_FB in some cases. Our results also show that OLSR-FB’Routing overhead and Nomalize Routing Load are less than AODV.

Keywords: Mobile Ad Hoc Networks; Routing Protocol; AODV; OLSR-FB.

Abstract: Over the previous years, electric power systems have experienced progressively visit stress condition because of consistently expanding power request, wasteful utilization of electric power age and transmission assets. Transmission line blackouts have been a typical reason for system stress conditions, which are conceivable to happen amid critical peak hours. Such occasions will cause a supply limit circumstance where falling disappointments and extensive territory power outages are conceivable. This research develops an intelligent task scheduling system for electrical appliances using particle swarm optimization. Object-oriented design methodology was used for system development. Particle Swarm Optimization (PSO) has been used to schedule domestic appliance to reduce consumption rate. PSO technique helps to balance load for each domestic appliance by scheduling load to the appliances. The load balance of domestic appliances such as freezer, water pump, water heater, tumble dryer and washing machine (energy consumption appliances), was modelled based on scheduled operation of several appliances at specific time according to customer lifestyle and priority of devices. System was implemented in Java programming language. The system was evaluated using weekly, monthly and yearly timeframe. The consumption rate of domestic appliances before and after optimization for weekly, monthly and yearly shows that optimization of the power consumed by domestic appliances reduced in all time frames, weekly with 12.8KWH, monthly with 51.2KWH and yearly with 665.6KWH.

Keywords: Energy consumption scheduling, inclining blockrates, price prediction, real-time pricing, wholesale electricitymarket, Task scheduling, Electrical appliances, Particle swam ptimization

Abstract: The present study deals with the comparison of Frustration and conflict between male and female students at the end of 2012-2013 academic year in their study. Exclusion criteria were the presence of chronic medical conditions or any other condition that would put the subjects at risk when performing the tests. The subjects were free of smoking, alcohol and caffeine consumption, antioxidant supplementation and drugs. They completed an informed consent document to participate in the study. The significant deference of frustration (t=p<.05), conflicts (t=p=<.05) Male Students reported higher frustrations as compared to female students.

Keywords: Frustration , Conflicts, student , Gender

Abstract: In this fast growing modern technology driven world, the internet is one of the most important technology not only for individual users but also for organization and online business. Nowadays, there are phishers who steals sensitive information like username, password, credit card, personal data etc. Several researchers have design rule-base system for phishing detection which are credited to help people who cannot understand which Uniform Resource Locator(URL) is real or fake address. This paper concentrates on an improve Model for Detecting Phishing URL using Deep Learning. Object oriented Design Methodology was used for system architecture and structure. The support Vector Machine has been used to extract the actual and the visual link from the domain name system(DNS) and compare the actual link and the visual link if they are same. The system uses the Deep Learning model (Generated Adversarial Network) in tensor flow and Keras framework to classify Website URL dataset containing 3207 URLwebsites, 1037 are Real URL websites and 2137 are fake. The dataset was read from directory using the pandas.read_csv function. The dataset was cleaned to make sure there are no null values present. The results of the test showed accuracy of 99.8% of all input website URL classified as either Fake or Real to verify if it’s actually a Fake website or Real Website. Keywords- Machine Learning, Deep Learning, Phishing, Generated Adversarial Network and Uniform Resource Locator.

Abstract: Smoking is the leading cause of early mortality in the world that may be prevented. However, there is a lack of evidence on the quality and efficacy of smartphone apps for smoking cessation. Mobile phone health interventions have made therapy more accessible than ever before thanks to the ubiquity of smartphones. Tobacco kills one person every six seconds. The use of machine learning techniques in the study assisted in reaching a conclusion on the cessation of tobacco consumption. Moreover, it provided a solid framework for dealing with cognitive dissonance via the use of a mobile application, among other things. This research article examines the relationship between the adoption of HCI and Support Vector Regression (SVR). Also, it makes use of K-means clustering to target specific groups of chain smokers. Furthermore, this study article delineates a comparison of the replacements that are now accessible in the application sector.

Keywords: HCI, Cognitive dissonance, Smoking cessation, Support vector regression, K-means clustering, application’s efficiency

Abstract: The next-generation of cloud computing will thrive on how effectively the infrastructure are instantiated and available resources utilized dynamically. Load balancing which is one of the main challenges in Cloud computing, distributes the dynamic workload across multiple nodes to ensure that no single resource is either overwhelmed or underutilized. This can be considered as an optimization problem and a good load balancer should adapt its strategy to the changing environment and the types of tasks. This paper proposes a novel load balancing strategy using Genetic Algorithm (GA). The algorithm thrives to balance the load of the cloud infrastructure while trying minimizing the make span of a given tasks set. The proposed load balancing strategy has been simulated using the CloudAnalyst simulator. Simulation results for a typical sample application shows that the proposed algorithm outperformed the existing approaches like First Come First Serve (FCFS), Round Robing (RR) and a local search algorithm Stochastic Hill Climbing (SHC).

Keywords: Cloud Computing; Load balancing; Genetic Algorithm.

Abstract: The performance of signal processing circuits at very high frequencies is very poor. At such higher frequencies that is in the order of GHz range active components like transistors cannot deliver much gain. Therefore, the signal is shifted to lower frequency band. Another problem is that higher frequency signal needs waveguides and strip lines. If we use intermediate frequency, signal can be easily carried through ordinary coaxial cable. The lower frequency transistors generally have higher gains so fewer stages are required. It's easier to make sharply selective filters at lower fixed frequencies. RF upconverters and RF downconverters are integrated assemblies that convert microwave signals to another frequency range for further processing. Generally, they are designed to produce an output signal frequency for a particular frequency band. RF upconverters are designed to convert microwave signals to a higher frequency range. By contrast, RF downconverters are designed to convert microwave signals to lower frequency range. In this paper we present a downconverter for frequency range of 870 MHz - 2000 MHz. This downconverter will convert 870 MHz to 2GHz frequency to 45 MHz to 870MHz using MMIC.

Keywords: upconverter, downconverter, intermediate frequency, mixer etc.

Abstract: Over the past two decades, the financial sector has seen a shift in how individuals and businesses operate. The adoption of AI and Big Data analytics has transformed the manner in which financial institutions operate, and how they interact with customers and other institutions. Several researchers opine that the financial sector will see further transformation due to the increased adoption of technologies that enable humans to dedicate more time in innovating and performing sophisticated tasks. On a daily basis, the financial sector tracks billions of market events and generates massive and diverse amounts of data that falls under the category of Big Data. AI models and algorithms that utilize Big Data to spot patterns and glean insights in order to make decisions in areas such as portfolio strategy and fraud detection have become increasingly common in the finance sector. Organizations in the financial sector have a varying level of capability and competency with respect to the adoption and utilization of these technologies. The utilization of these technologies and the implications of their use has become the subject of debate in the financial sector. The goal of this paper is to report on the applications of AI and Big Data analytics in finance, and the ethical, organizational, and legal repercussions of the use of these technologies.

Keywords: Big data analytics, AI in finance, Implications of Big data, Fintech, Challenges of Big data and AI in finance, Applications of Big data and AI in finance.

Abstract: In the field of VLSI research in electronic circuitry. Memory is the basic demand of most electronic devices. These memory components are designed specifically using a CMOS transistor. When we talk about CMOS power, the area and speed of each transistor is a big deal. But we know there is a trade-off between these three things. Engineers and researchers are still working on these questions. Various methods have been used to reduce water leakage within the designed circle. As a result, the praise capacity in the SRAM cell is reduced and it works better. The computing power in the SRAM bitcell is reduced and its performance is better. The designed SRAM bitcell showed nearly 3 times the purging power of the SRAM 6T bitcell. Read and write times access to SRAM bitcell intended to increase and decrease volume. RAM is used as main memory for small value devices that do not have a cache. Therefore, the construction of memory using an optimized SRAM cell in terms of process parameters, i.e. power consumption, quantity, area and delay, is a domain of concern. Critical analysis and the same are presented in a functional way. The SRAM 6T to 10T was found to have better performance in terms of power consumption and power model, but has a higher access time than other existing SRAM components when compared to the results obtained in mode CMOS with Micro wind Tools.

Keywords: VLSI, Memory, SRAM, DRAM, Power Consumption, Power Reduction, Power Dissipation, CMOS Technology, Delay.

Abstract: Data Analytics and Predictive analysis is essential on medical records, because the extent of spread of COVID-19 disease is huge and is already declared as a pandemic. Coronaviruses are a group of viruses which have been said to have originated from Wuhan, China belonging to the family of Coronaviridae. Human coronaviruses can cause lung infections which can be fatal if left untreated. COVID-19 death is defined for surveillance purposes as a death resulting from a clinically compatible illness in a probable or confirmed COVID-19 case, unless there is a clear alternative cause of death that cannot be related to COVID disease.[1] There should be no period of complete recovery between the illness and death. In our paper we have published the results based on a survey conducted by our team and, used Data Analytic tools and Predictive Analysis on the acquired data. Vital questions have been asked and opinions have been collected from around 500 residents of each area in Bangalore Urban zone. Visualization tools using Python libraries have refined our data visualization process. Sampling rate is fixed not to overfit or under fit during supervised learning using Artificial Intelligence (AI).

Keywords: Data Analytics and Predictive analysis, Coronaviruses, Coronaviridae, COVID-19, Data Analytic tools and Predictive Analysis, Visualization tools, Python libraries, supervised learning using Artificial Intelligence (AI).

Abstract: The motive of our work is to connect people to the unexplored regions of our country which will make people aware of what actual India is and will indirectly uplift or will help in development of underdeveloped regions of the country, we will be using Natural Language Processing to analyze the polarity of the comments of the visitor which will be helpful to the new visitors. Key words: Sentiment Analysis, Machine Learning , Web Development, Polarity, Natural Language Processing.

Abstract: Object recognition is the task of recognizing the object and labelling the object in an image or video scene. The proposed method seeks to implement an object recognition model for climatic data. Accurate characterization of objects in climate simulations and observational data archives is critical for understanding the trends and potential impacts of events in the climate. An object in an image can be recognized by extracting the features like colour, texture, or shape. Based on these features, objects of large-scale weather patterns are classified into various classes and each class is assigned a name. This paper presents an overview of object recognition methods by including two classes of object detectors. Two stage detectors such as Faster R-CNN focus more on accuracy, whereas the primary concern of one stage detectors such as YOLOv3 is speed. Faster Region-based Convolutional Neural Network method (Faster R-CNN) and You Only Look Once (YOLO) are the algorithms used for object recognition in this project. The results obtained from the two prominent approaches Faster R-CNN and YOLOv3 are compared Keywords - Object recognition, climatic data, Convolutional neural network, Yolov3, Faster RCNN.

Abstract: A sensor is a device which detects or measures a physical property and records, indicates, or otherwise responds to it. The sensor used in a particular application is sensitive to one or more sources, and when the sensor is exposed to that stimulus/stimuli, this affects the physical, chemical or electromagnetic properties of the sensor which is further processed to a more usable and readable form. Sensor is the heart of a measurement system. It is the first element that comes in contact with environmental variables to sense and generate an output. A sensor can be classified into various categories like active and passive sensors, analog and digital sensors, mechanical sensors, bio sensors, etc. In this paper we are using an array of sensors, and reading data from the sensors simultaneously and displaying it using an android application called “sense_graph” which is a scientific third party application developed by our team. We are using an array of similar sensors- Force sensors, which are capable of measuring force applied per unit area. In this paper, we are interested in measuring force/area on the bottom of the human foot and framing conclusions. The measurements are made in N/m² at a particular time interval and a graph of N/m² v/s time (sec) is plotted. There are regions in the foot where pressure could be very high or negligible for a specific posture or movement of the human body.

Keywords: measures, indicates, responds, active and passive sensors, third party applications, analog and digital sensors, posture or movement, heel, toe mounds, inner arch, outer arch and android application interface.

Abstract: Garbage bins are found at all the places in a particular collage, school, hospital, bank, shopping malls etc. Every time it is not possible to check whether the bin is full or empty, so in this paper we come up with a solution to monitor the status of every bin inside the campus area of any school, collage or any other place. Here we actually use arduino board connected to an ultrasonic sensor and a Wi-Fi module and this entire system is connected to every single bin inside the campus area. The ultrasonic sensor is directed towards the face of the bin and whenever the bin is less than 5 cm empty the status of the bin will be shown as full, otherwise it will be shown as empty. We actually aim to implement the system inside the campus of the VIT University. There will be a webpage displaying the status of the bin.There will be a centralized server which will access the status of the bins at regular intervals and inform the sweepers accordingly. The WiFi module will actually send the data to the nearest router and it is expected to route through the routers and send the correct data to the server every time. This is an IOT-Based Garbage system , and as a part of future work we hope to implement the payment module in this system, where the users using the bin have to pay online maybe weekly or monthly.

Keywords: Arduino UNO, Ultrasonic Sensor, Wifi ESP module, Garbage.

Abstract: We propose a system for a virtual mental health assistant Diagnose owing to time and space constraints and shortage of resources related to in-person therapy. Oftenly, disturb mental health is a snowball effect built up over time and requires continuous attention and conscious efforts to improve. This is possible with the help of a virtual mental health Diagnosis. For detection and classification of various mental health problems, machine learning algorithms are utilized via training of various models which work in question-answer manner. The purpose of Diagnostic will have a Test regarding your problems which can determine the level of problems and accordingly provide solutions, psychological assessment, an emotion detection module and a recommendation system for improving the mood of the user. User will have to answer some particular questions related to mental health.

Keywords: Mental health , Virtual mental health assistant, Virtual Diagnosis, Classification, Machine Learning

Abstract: The sign language is used widely by people who are hearing impaired as a medium for communication. A sign language is the composition of various gestures formed by different shapes of hand, its movements, orientations as well as the facial expressions. There are around 466 million people worldwide with hearing loss and 34 million of these are children. ‘Hearing impaired’ people have very little or no hearing ability. Hence, they use sign language for communication. Different sign languages are used by people in different parts of the world. Compared to spoken languages they are very less in number. India has introduced its own sign language called Indian Sign Language (ISL). In developing countries there are only very few schools for deaf students. In developing countries, the unemployment rate of sensory impaired people is very high. Data from Ethnologue states that among deaf population in India, which is about one percent of total population, literacy rate and number of children attending school is very less. It goes on to state that official recognition of sign languages, increasing the availability of interpreters and providing transcription in sign languages greatly improve accessibility. Signs in sign languages are the equivalent of words in spoken languages Signed languages appear to favour.

Keywords: Indian Sign Language (ISL), Sign Language Recognition, Sign to Text, Convolutional Neural Network (CNN), Hand gesture, OpenCV.

Abstract: Agriculture is the basic source of food supply in all the countries of the world whether under-developed, developing or developed. Besides providing food, this sector has contributions to almost every other sector of a country. According to the Bangladesh Bureau of Statistics (BBS), 2017, about 17% of the country’s Gross Domestic Product (GDP) is a contribution of the agricultural sector, and it employs more than 45% of the total labor force. In light of the decreasing crop production and shortage of food across the world, one of the crucial criteria of agriculture now-a-days is selecting the right crop for the right piece of land at the right time. Therefore, in our research we have proposed a method which would help suggest the most suitable crop(s) for a specific land based on the analysis of the data of previous years on certain affecting parameters using machine learning. In our work, we have implemented Random Forest Classifier, Gaussian Naïve Bayes, Logistic Regression, Support Vector Machine, k-Nearest Neighbor, and Artificial Neural Network for crop selection. We have trained these algorithms with the training data and later these were tested with test dataset. We then compared the performances of all the tested methods to arrive at the best outcome.

Keywords: Agriculture, Crop yield, Logistic Regression, k-Nearest Neighbors, ANN

Abstract: A trend of significant increase in municipal solid waste generation has been recorded worldwide. This has been found due to over population growth rate, industrialization, urbanization and economic growth which have ultimately resulted in increased solid waste generation. Final destination of solid waste in India is disposal. Most urban solid waste in Indian cities and towns is land filled and dumped. Proposed project deals with the most blistering topic i.e. waste segregation. An efficacious management needs to be materialized for better planet to live in. Hence, cost effective project proposal; try to bring in the change. It deals with the minimization of blue-collar method utilization for exclusion of waste into an automated panache. An automation of this style not only saves the manual segregators of the numerous health issues, but also proves to be economical to the nation. Besides, this system utilizes low cost components for the successful segregation of most types of waste. When installed in apartments or small colonies, it proves to be beneficial in sorting the waste at the site of disposal itself. Here we propose the use of an Auto Waste Segregator (AWS) which is cheap and also an easy to use solution for segregation of household waste. It is designed to segregate the waste into three categories viz. metallic, dry and wet waste. The system makes use of moisture sensor for the segregation of wet and dry waste and inductive proximity sensor for the detection of metallic waste and an LCD display for displaying the result of segregation. It is evident from experimental reports that segregation of waste using AWS has been successful.

Keywords: Waste segregation, Solid waste, Water pollution etc.

Abstract: First, take a look at a traditional voting system. Large space and manpower are required to set up voting booths in multiple areas around a city or village. High security has to be maintained on the date of an election. Voters have to visit the voting booth and need to stand in a long queue. Again, manpower is required for volunteering and assistance of voters at the place of voting. The Voting process is done on a manual voting machine. Vote counting is done with the manual process. Then there is a gap of a few days for results to be displayed. So if we see, here in a traditional voting system, we need a lot of manpower, energy, and time to conduct this process. Now to overcome the above-mentioned problems, we are going to develop an application called Online Voting System. Like Money transfer, Shopping, Booking, Teaching, Data sharing, Admissions, Job search, etc. So with the easy access and use of the internet, we are going to take this existing voting system to an advanced level. We are going to develop an online platform with high security so that the same process could be done easily without the waste of time, afford, and energy. The main responsibility of this project is to give simple and easy access to the election process for both the election committee as well as participants.

Keywords: Voter, Platform, Web application, Online, Election, Voting, Results.

Abstract: Pandemic has led to a global health crisis and people are forced to move in. People may face the need for equipment or utilities for a temporary period. In such a case, purchasing the tool or item may not be an appropriate solution. The proposed system helps you find local people from the neighborhood who may make use of the item required for some time in exchange for a small rental fee. People can connect and bargain for a better price and rent the item. So, the system plays the role of a portal to rent items. People with spare items can list it on the app to generate a small amount of passive income by renting it out to neighbors. On the other hand, people who need items for a short time may search for the item on the portal and possibly find someone who can rent it to them. The feature to look forward to here is the security against scams.

Keywords: Flutter, Rental, Money, Scams, Bargain, Exchange.

Abstract: Water scarcity is one of the most important natural resource problems to be paid more attention to. Traditional agriculture methods required more water supply due to which irrigation was introduced in 6000 B.C. in the Middle East's Jordan Valley. Due to the development of new technology and introduction to Internet of Things (IoT) many problems can be efficiently handled. Embedded and microcontroller systems provide solutions for many problems. The smart irrigation system has become a new trend in the field of agricultural irrigation. This paper proposes a soil moisture sensor-based smart irrigation system. This can be implemented by installing soil moisture sensors in the agriculture field to monitor the moisture level in the soil which in turn transfers the data to the microcontroller to evaluate the water demands of plants.

Keywords: Soil Moisture Sensor, Microcontroller, Smart Irrigation, Arduino Uno

Abstract: In today’s world, as Covid-19 pandemic has made everyone stay at home, it has impacted education sector a lot. Students now have to attend classes online and many software were introduced to enable online teaching. Similarly, for taking exams there were many technologies introduced, but students are able to cheat in the exam. This type of practice needs to be stopped. The project aims to provide the solutions to catch the students and avoid the cheating during exams. I have created an Online Examination Portal for giving exams. It can be used by students to give exams and track their progress, and used by institutions to conduct examinations. I have used HTML, CSS for layout of the portal; JavaScript to decide what action will happen on user’s inputs to the portal; and MySQL to store the question and answers for the test and Artificial Intelligence to track the face of the student.

Keywords: Artificial Intelligence, Covid-19, HyperText Markup Language, Image processing, JavaScript, Online Examination Portal.

Abstract: This paper is based on a method of recommending movies to the user after assuming the priorities set/entered by the user. We now live in what some call the “era of abundance”. For any given product, there are sometimes thousands of options to choose from. Think of the examples above: streaming videos, social networking, online shopping; the list goes on. Recommender systems help to personalize a platform and help the user find something they like. The algorithm used segregates the list of movies from the dataset according to the inputs provided by user and finally displays the list of the recommended movies. The work in this project focuses on user-based collaborative filtering algorithm which is implemented in java. A bright feature of allowing the user to rate movies has also been provided in the system.

Abstract: The main aim of this paper is to address the problem of generating a plausible colored photograph given a grayscale image and how it can be automated. Previous approaches to coloring grayscale images often heavily relied upon human input and often produce desaturated colorizations. Inspired by [1, 2, 4], we built a convolutional neural network model over a set of images to colorize images without human input. In image processing, the availability of deep learning has allowed us to build models that can automate the rigorous tasks such as detection, classification etc.

Abstract: Traffic congestion may be a major downside in several cities of Asian nation along side different countries. Failure of signals, law social control and dangerous traffic management has cause traffic congestion. one in every of the key issues with Indian cities is that the prevailing infrastructure can not be distended more, and so the sole possibility offered is best management of the traffic. holdup incorporates a negative impact on economy, the atmosphere and also the overall quality of life. thence it's time to effectively manage the traffic congestion problem. There are numerous ways available for traffic management similar to video knowledge analysis, infrared devices, inductive loop detection, wireless sensor network, etcetera of these ways are effective methods of good traffic management. however the matter with these systems is that the installation time, the price incurred for the installation and maintenance of the system is extremely high. thence a replacement technology known as frequency Identification (RFID) is introduced which may be as well as the prevailing signal system that may act as a key to smart traffic management in real time. This new technology which will need less time for installation with lesser prices as compared to different methods of holdup management. Use of this new technology can cause reduced traffic congestion. Bottlenecks are going to be detected early and thence early preventive measures may be taken so saving time and cash of the driver.

Keywords: RFID, GSM, Traffic congestion.

Abstract: Internet of things (IOT) is a worldwide system of “Smart Devices” which senses and connects with their surrounding and interacts with users. And other systems. Air pollution is one of the major concerns of our era all over the globe. The level of pollution is increasing day by day, and this is due to increase in amount of gases like carbon dioxide, smoke, alcohol, benzene, NH3 and NO2, some of the main causes for air pollution are increasing population , increased vehicle use, industrialization and urbanization these all factor ends up affecting wellbeing and health of population causing various harmful diseases In order to analyses we are developing an IOT Based mobile pollution Monitoring System which we can take with us to different locations as it is able to move easily and will monitor the Air Quality over an internet server. Existing monitoring systems have inferior precision, low sensitivity, and need laboratory analysis. Therefore, improved monitoring systems are needed. To overcome the issues of existing systems, we have used machine learning and analyzing. It will show the accurate reading of air quality in PPM on the LCD and also as on webpage in order that we will monitor it very easily. In this IOT project, you can monitor the pollution level from anywhere using your computer or mobile device. The system uses MQ2, MQ135 and MQ7 sensor for monitoring Air Quality. It measures their amount exactly and finds out harmful gases.

Keywords: IOT, sensors, Population, Mobile, Smart Device, Pollution, Air Quality, Machine Learning, Monitoring, Arduino.

Abstract: Cloud computing has grown dramatically in recent years. Because of the low cost and pay-as-you-go nature of the cloud, many organizations are shifting away from traditional computing models. Despite the fact that the Cloud Service Provider (CSP) guarantees that the data stored in their remote cloud server will be intact and secure. However, there are numerous data integrity issues that must be addressed. Data integrity is a major concern in the cloud environment. In this paper, we reviewed several previous studies that identified issues with cloud data storage security, such as data theft, unavailability, and data breach of cloud server data. We also provided a detailed analysis of the various types of data integrity attacks such as SQL injection attacks, Unauthorized access attack, Authentication attack.

Keywords: Data integrity, Cloud security, Cloud services, Data privacy, Attacks on cloud.