Volume 10 | Issue 8

 Abstract

India is the agriculture-based country. Our ancient people completely depended on the agricultural harvesting. Agriculture is a source of livelihood of majority Indians and has great impact on the economy of the country. In dry areas or in case of inadequate rainfall, irrigation becomes difficult. So, it needs to be automated for proper yield and handled remotely for farmer safety. Increasing energy costs and decreasing water supplies point out the need for better water management. Irrigation management is a complex decision-making process to determine when and how much water to apply to a growing crop to meet specific management objectives. If the farmer is far from the agricultural land he will not be noticed of current conditions. So, efficient water management plays an important role in the irrigated agricultural cropping systems. A low-cost alternative solution for efficient water management currently in use is drip irrigation systems that consist of an automated controller to turn on & off the control values, which in turn helps the farmers by managing the water supply to the crop fields and further maintains the moisture levels of soil that helps in better crop production. This project probes into the design of the automated irrigation system based on Arduino. This Embedded project is to design and develop a low-cost feature which is based on embedded platform for water irrigation system. This project uses temperature and soil moisture sensors to detect the water quantity present in agriculture. The project uses Arduino micro controller which is controller to process the information. The aim of the implementation was to demonstrate that the automatic irrigation can be used to reduce water use

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 Keywords

GSM: Global system of mobile

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 Abstract

Agriculture is India's economic backbone. Scientists are tirelessly striving to improve the cultivation of crops. This system combines all the factors like nutrient requirements, moisture content monitoring, animal intrusion and early crop disease detection methods to alert farmers. Soil nutrients are critical for achieving high crop yields and producing high- quality products. This system is used to design and develop a working system that uses Ph sensor to monitor the Ph values and to maintain the amount of alkalinity and acidity in soil for the efficient plant growth. It uses soil moisture sensor to regulate the moisture levels of the soil preventing less yield due to inadequate and nutrients erosion due to excess soil moisture. It gives an effective suggestion system for the crops using NPK sensor to prevent crop dehydration due to excess and stunted growth, discoloring on the edges to leaves due to insufficient supply of nutrients. It uses camera module to avoid the animal intrusion using alarm alert system using computer vision algorithms. Plant infections may be detected early, which helps farmers prevent losses using deep learning algorithms. After recognizing the symptoms of leaf diseases, automatic approaches for classifying plant diseases can also help with decision-making also to create a user-friendly mobile application for easy access to all the information required and deploy it on cloud so that it can be accessible from anywhere. Hence, Automatic detection and monitoring is very much important for the sustainable agricultural revenue.

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 Keywords

Agriculture, NPK, Ph, CNN, crop recommendation

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 Abstract

People get to know one another through sharing their ideas, thoughts, and experiences with others around them. There are several ways to accomplish this, the best of which is the gift of "Speech." It will be unjust if we overlook those who are denied this priceless gift: the deaf and dumb. The usage of "Sign Language" is the only mode of communication available to the deaf and dumb. Mute people can make hand gestures with their fingers, which will be transformed into speech so that regular people can understand them. The deaf and dumb communicate through sign language, which is difficult to decipher for those who are not familiar with it. As a result, software for the phone that can translate motions into text and speech is required. This will be an innovative step toward allowing deaf and dumb people to communicate with the general population without the use of a secondary device other than a Smartphone. We'll be working on an app that will make it easier for people who are deaf or hard of hearing to communicate. Flutter is used for the front end, and Python script is used for the backend. It attempts to provide dumb people with an effective and economical means to express them by converting motions to text and deaf people's speech to text and gestures. This application will create a better society where community sees them as one and people will look into their abilities than disabilities. This application will create a better society where community sees them as one and people will look into their abilities than disabilities.

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 Keywords

Flutter, Python, Decipher

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 Abstract

A brain tumour is a misshapen cell growth that can be malignant or non-cancerous in nature. The most deadly condition is a brain tumour, which can be detected with automated procedures on MRI images and identified quickly and accurately. Several methods of diagnosis and segmentation of brain tumors have been suggested by many researchers for effective tumor detection. Because of the high diversity in tumor tissue of different patients, automating this process could be a challenging risk. Medical resonance imaging is a challenging and innovative field in the medical science field. In the medical field, the techniques of ML( Machine learning ) and Deep learning holds a significant stand. Brain tumor detection using MRI images have many applications. Brain tumor detection from MRI images is one in all the emerging fields in medical science. There are different brain tumor detection methods. Detection and segmentation methods are used to detect the brain tumor from the MRI images. Here a brief review of the different brain tumor detection methods has been discussed. The different methods include Convolution Neural Network, Artificial Neural Network, Resnet - 50 and CNN with Transfer Learning.

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 Keywords

Brain Tumor, MRI images, Convolution Neural Network, Artificial Neural Network, Resnet - 50, CNN with Transfer Learning

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 Abstract

The Areca nut, often known as betel nut, is a tropical crop. India is the world's second-largest producer and consumer of areca nut. A multitude of illnesses afflict it throughout its life cycle, from root to fruit. The current method of disease detection is simple observation with the naked eye, and farmers must thoroughly study each crop on a regular basis to detect diseases. We proposed a method that uses Convolution Neural Network (CNN) and Support Vector Machine (SVM) algorithm to detect whether the given areca nut is of bad quality or good quality. We created our own dataset comprising of 208 photos of good and bad quality areca nuts to train and test the model. By using CNN we have obtained the accuracy of 97.12% and by using SVM we obtained the accuracy of 93.68%.

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 Keywords

Areca nut, Convolution Neural Network, Support Vector Machine

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 Abstract

Lives of animals are valuable. As global citizens, we must work to ensure the survival and development of animals in order to maintain the ecosystem's balance and stability. Wildlife monitoring collects data on wildlife species, numbers, habits, quality of life and habitat conditions to aid researchers in understanding the status and dynamics of wildlife resources and to serve as a foundation for effective wildlife resource protection, sustainable use and scientific management. Continuous hunting has resulted in the extinction of many animal species and the government has enacted legislation and is undertaking surveys to conserve certain species. Conducting surveys is a difficult undertaking, especially if don't have the necessary resources are not available. Conducting Survey is the Challenging undertaking, especially without the assistance of technology. To address this, Species Classification wireless camera implementation is carried out. The smart camera is combined with a phython based programming that includes a pretrained Tensor Flow model Some species are rare to find and even when they are, predicting their classification is challenging. From a human perspective, various species present in various settings appear in various sizes, shapes, colours, and angles. Superior choice of technique for detecting and classifying distinct species is to be carried out in order to better conserve and preserve them.

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 Keywords

LIDAR, FSP, SVM, CNN, Forest stand

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 Abstract

Adders are an essentially universal component of today's integrated circuits. The constantly developing computing industry demands not just faster arithmetic units, but also smaller and less power consumption arithmetic circuits. The adder must be quick and also efficient in chip area to meet its requirements. In order to construct an adder of 32-bit using eight 4-bit adder for our project, we used the Carry look ahead adder. It is also known as fast adders because it consumes less time over other adders by propagating carry before the sum output is obtained, resulting in brilliant performance. We designed the schematic and layout of CLA using LT spice simulation programmed in Electric binary using 45nm technology.

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 Keywords

Adder, CMOS, Electric, CLA

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 Abstract

Transportation-related greenhouse gas emissions are one of the most serious environmental concerns, and they are increasing at an alarming rate. As a result, solar energy for transportation may be able to alleviate this issue. The goal of the proposed effort is to offer a technology that promotes green energy; for example, assume a situation in which we might utilize solar energy to charge an electric vehicle, with solar panels built-in, but the next question is if this is practical during the rainy season. During the rainy season, charging internal solar panels is problematic. The SPEV system includes a charging wire that connects to both the car and a 230v wall outlet. A security system, drive guiding system, route detection, and other features are included into the electric car. Support for Android apps, Wi-Fi, Battery Update, and LoRa. Our research findings are thoroughly examined. Hence The use of a solar-powered electric vehicle (SPEV) results in fewer pollution. The majority of automobiles are powered by gasoline. Hazardous gases are emitted by these vehicles. This contributes to global environmental contamination. In recent years, academics have proposed the use of hybrid vehicles to minimize pollution. Many countries have chosen to reduce pollution by employing electric vehicles as one of their answers (EV). EVs have been rising in popularity in recent years. The electric vehicle's battery is a critical component. The efficient utilization of battery is a critical parameter for electric vehicles. The efficiency of electric vehicles can be improved by using renewable energy sources such as solar energy could be increased In electric vehicles, the energy management system (EMS) is crucial. Because the number of subsystems and components in electric vehicles is growing, enhancing EV efficiency through the use of EMS is desirable. Various EMS systems are explored in this research, and an energy model for effective battery use to increase EV performance is proposed

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 Keywords

SPEV; Solar powered Electric Vehicle EV; Electric Vehicle EMS; Energy Management System

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 Abstract

Digit recognition is a suitable model issue for learning about the Neural Networks, and it will pave the way for sophisticated Deep Learning techniques.Manymethods are found in literature to recognize and classify the digits which are written by hand (handwritten digits).ThispaperexplainshowtorecognizeandclassifyhandwrittendigitsusingCNNandMATLABforenhancedperformance. A deep convolutional neural network (CNN) is a type of neural network that is used to recognise images. This method determines how important the deep layer improvements are for processingthe image byusing MATLAB, we provide the implementationof necessary for constructing and applying Convolution Neural Network to a high-quality data set known as MNIST which is a collection of more than 60,000 handwritten digits dataset for training purpose and 10,000 digitsdatasetfortesting purpose.Whentestedthedevelopedmodelforclassification, we got 99.60% accuracy and prove to be betterthanotherclassifier. Many hidden convolution layers and more hidden artificial neurons could improve the accuracy of the outcome.

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 Keywords

Convolution, Padding, Stride, Softmax, Maxpooling, ReLU

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 Abstract

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 Keywords

Internet of Things, Biometric, Finger print authentication, Embedded system, Voting system

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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 Keywords

Agro-voltaic, Hydroponics, Agriculture, Farming, Automated, Nutrition, TDS, pH, crops plants, Soil less, NFT- Nutrition Film Technique, Hydroponic Farm

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 Abstract

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 Keywords

Convolutional Neural Networks (CNN), NPDR, PDR, Deep Learning, DR.

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 Abstract

Electricity has evolved as an essential source over the years. This progressive world today, has become so much dependent on electricity, such that it is impossible to live without it. In this case, generation of more and more electricity is much important to meet the needs. Usually, electricity is produced using nonrenewable sources such as petrol, diesel, coal, etc., which unfortunately creates lot of pollution to our environment. But what is the alternative? Electricity is present everywhere in limitless quantities and can drive the world's equipment without the need of non- renewable sources. Yes. Generation of electricity using flywheel is one among them. The aim of our project is to generate electric energy using flywheel. The main reason to develop this idea of producing electric energy using a flywheel and magnet is that it is clean and does not cause pollution. The gravity wheel or flywheel is coupled with magnets and the gear-train in order to produce energy. Flywheel are usually manufactured by casting process with single materials with high strength. Along with flywheel, magnets are used in such a way that it delivers mechanical force for the flywheel to overcome the frictions on the flywheel. This helps the flywheel to rotate longer which in turn increases the time of generation of electric energy. The friction can be further reduced using smooth bearings. The outcome of this project is that the power is generated and can be stored using flywheel, magnets and generator

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 Keywords

Flywheel,Generator,Pedal,Magnet

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 Abstract

Agriculture is a major source of income for the country. Leaf diseases in agriculture are a major concern for many countries, as food consumption is increasing rapidly owing to population growth. The early and precise detection and diagnosis of leaf diseases are critical to preventing their spread. Image processing techniques including mathematical equations and mathematical transformations can be employed for disease identification. For human eyes, an image is a mixture of RGB colours from which we can extract the features. Modern computers, on the other hand, store images in a mathematical structure, which means the computer views the image as numbers. After evaluating the image as a numerical array or matrix, we may apply various transforms to it to extract specific features. However, before the picture can be transformed, it must first go through different procedures such as transformation. K-Means Clustering and the Support Vector Machine Algorithms are used in MATLAB to identify and classify several forms of leaf diseases.

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 Keywords

Algorithm; Classification; Feature extraction; Plant Leaf Diseases; Segmentation; Training

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 Abstract

In recent times changes in weather are unpredictable due to drastic changes in solar activity, greenhouse gas emissions etc. A system to monitor the changes in the weather conditions in industry, agriculture etc. in real time is facilitated by a Weather Monitoring system. Monitoring temperature and relative humidity by using the sensor helps for weather forecasting. Our aim is to outline a low power electric circuit to be implemented along with a Field programmable gate array for functional verification and performance estimation. For real time weather monitoring a device is presented to report relative humidity and real-time temperature using FPGA board

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FPGA (field programmable gate array)

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 Abstract

According to global statistics, deaths among women due to breast cancer (BC) are the leading cause out of all the several types of cancers. Hence treating breast cancer as early as possible, and even relatively complicated to detect and analyse at the beginning stage. The conventional method is time-consuming and not efficient and very less accurate. Henceforth an efficient technique to diagnose the cancerous cell, not including human association close to accuracy. CT scan is a particular case of Mammography, which adopts the X-ray technique & uses superior-resolution pictures such that, it perceives fine tumors in the breast. The review paper elaborates on the recognition of the BC by employing various image processing (IP) application and techniques

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 Keywords

Cancer, Breast Cancer, Machine Learning, Mammogram, Histopathology image, Pre-Processing, Segmentation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The decline of agricultural land and the rapid development of technologies in the latest agricultural programs such as the NFT System, have presented a major challenge for farmers. The NFT system requires special attention to several parameters such as water temperature, water level, acid (pH), and nutrient concentration (PPM). Sadly, it's still controlled by mistreatment the manual manner, for example in controlling the nutrient concentrations has to be done many time in a day, so much time is wasted. To address these issues, we need a system that can be used and easily deployed and that should be affordable. We have built a hydroponic monitoring system and automation that can monitor using sensors connected to a small Arduino mega 2560 controller, Wi-Fi module and advanced features such as a web server with the Internet of Things, Web used as a visual interface system that allows the user to monitor and control Agrovoltaic farming The Agrovoltaic System is fully utilized by Solar power .So the project name is AGROVOLTAICS

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 Keywords

Internet of Things; Agrovoltaics; Arduino mega 2560; ;pH sensor;PPM sensor;Temperature sensor

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT,NodeMCU,Sensors

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Solar Energy, Solar Panel, Arduino Uno, RTC, NodeMCU

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Creative Commons Attribution 4.0 and The Open Definition

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Hexapod Robot is built with six legs so it is capable of performing basic mobility tasks. A Line Following Hexapod Robot is an automatic robot which is able to follow a black line that is drawn on a contrasting color surface. It is designed in such a manner so as to move automatically and follow the line. The robot uses signals from the IR module to identify the line, thus assisting the robot to stay on the track. The code written based on the sensor input makes its movement precise and flexible. The robot is driven by servo motors to control the movement of the legs. if there is a obstacle blocking the path of the robot, the robot changes its path moves forward and then keeps on following the black line

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT,Mqtt,Pothole

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