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In India, climate change has a huge impact on the agricultural sector. It directly affects crop yield, nutritional quality and productivity. In this paper, a model is devised to correctly predict the crop yield only from past data including factors like rainfall so that appropriate measures can be taken in the future. Machine Learning is one such tool which can be used to solve this issue. Random Forest Algorithm, XGBoost and K-Nearest Neighbor (KNN) Algorithm are the machine learning algorithms used for crop yield prediction in this paper and the one with higher accuracy can be used for future work. Further discussion includes how much impact each factor related to crop yield has on the predicted value so an ordinary farmer can plant and take care of his crops according to it and use this model for his daily work. In doing this, modernization of the agricultural sector is made possible and a boost is given to crop yield in India. [ABSTRACT FROM AUTHOR]

The vast majority of individuals in India rely on agriculture as their main source of income. Precision agricultural advancements, thus, become more significant as a result of their economic impact. The paper offers a novel smart roof-based irrigation system as an advancement in the field of precision agriculture. This system can be deployed over any agricultural land holding. The area of agricultural land and crops will be protected by the smart roof, which is equipped with a rain sensor, in the event of unexpected or heavy rain. The slanted roof would direct rainfall into a tank adjacent to the rain cover. A moisture sensor would monitor the crops and the soil around them, and stored rainfall would be sent to the plants as needed. The proposed arrangement would not only benefit the cultivators by preventing the agricultural produce from going to waste but would also reduce groundwater consumption through rainwater harvesting. With water supply automation, crops would receive the precise amounts of water they require, considering various aspects including breed, season, and moisture retentivity. Through the introduction of such an innovation, an improvement in crop quality, as well as crop yield, is anticipated. [ABSTRACT FROM AUTHOR]

Agriculture is an integral part of people's living in India, whose economy is mainly based on farming. People cultivating crops have a significant problem identifying environmental conditions and factors that require their attention. In this paper, the authors present system integration utilizing Internet of Things (IoT) modules that monitor the farms and control the temperature in the traditional cultivation method. In work, we included the sensors to monitor the crops to acquire the details of farming conditions using which the farmer can retain healthy crop cultivation. The proposed work includes sensors to monitor temperature, humidity, soil moisture, rain using a Peltier sensor to control the temperature according to the crop needs. [ABSTRACT FROM AUTHOR]

In today's modern era, most developing countries like INDIA depends on agricultural fields for around 70 to 75%. In this period, drones or UAVs are becoming an integral part of farming fields. The paper introduces the types of drones and their agricultural motive. The UAV can also operate on the relay drive and commands given by the transmitter. In agriculture, most of the economic loss occurs due to insects and pests. The paper stresses the methodology, specifications and controlling techniques for the UAVs in the agricultural field. It also shows us the different applications of UAVs for agricultural purposes. The main concern is designing drones using recent technology to avoid human involvement. It is also important to consider the specifications of the components while designing the drone. With the help of correct components, the right cameras and detectors, agricultural drones have contributed to the accurate, economical, simple and structured way of modern technology in an agricultural enclosure. [ABSTRACT FROM AUTHOR]

Presently the perception of sustainability has been dominant in the field of agriculture. Sustainable agriculture means economical agriculture by following the practices which are eco-friendly. This results in increasing the attention of the stakeholders for monitoring as well as evaluating the practices being used in agriculture. It is realized that there are many limitations to creating a commonly accepted term for sustainable agriculture. So many opinions are there with reference to the realization of sustainable agriculture. In this work, we present the concept of sustainable agriculture and the methods as well as practices that are economically feasible, eco-friendly and shield public health. A special attention is given towards the use of nanotechnology for sustainable agriculture. As such, most of the rural people, particularly the young generation, are not interested in farming as there is no certainty in the output and if at all output becomes favorable, getting the appropriate price is a point of concern. Existing farmers in India are using fertilizers and pesticides which are not cost-effective owing to the price and usage of improper quantum. Moreover, they are also becoming the main source of pollution and health hazards. The dual problem of the usage of fertilizers and pesticides can be addressed by nanoscience by way of providing nanomaterials like nano fertilizers and nano pesticides having better potential to perform. The use of nano fertilizers like N, P, K, Fe, Mn, Zn, Cu, Mo and carbon nanotubes facilitates more efficiency as they stand for enhanced action and targeted delivery efficiency. Similarly, the use of nano pesticides like Ag, Cu, SiO2, ZnO and nano formulations also has the potential for escalated performance as compared to traditional pesticides. Considering the potential of the nanomaterials, this paper is highlighting how nano fertilizers and nano pesticides can help the Indian agriculture to be sustainable. For this purpose, existing literature has been the base. Similarly, this paper also unfolds the level of acceptability of nanomaterials by the Indian farmers which have been ascertained by way of personal interaction with 100 farmers of Odisha. It is inferred that, with the immense potential of the nanomaterials and the positive perception of Odisha farmers on them, Indian agriculture can be sustainable with the help of nanotechnology. It is a fact that sustainable agriculture can turn the Indian rural economy around. [ABSTRACT FROM AUTHOR]

Living in the 21st century, Technology has acquired an immense prevalence around the world which assists people with being more productive. Innovation has been spread all around the world securing outrageous importance on streams like Education, Industry, Trade as well as Agriculture. India being a critical Agriculture arranged country, it lacks on different benefits of new advancements which assist them with being more productive. Utilization of more current advancements are not found in farming fields. This paper predominantly points on making an Automatic talk bot model by applying Artificial Intelligence on the fundamental necessities of Farmers and Agriculture such as soil type, crop, environment, assessed benefit, Government advantages and Workshops conducted on giving Agricultural guidance to farmers. The bot is prepared with various sorts of inquiries. It replies to any queries or questions raised by a farmer based on the preparation dataset given. It applies Naive Bayes Algorithm to distinguish fitting response from rundown of prepared questions and even figures out how to respond to inquiries on which the bot has not been prepared and gives a response on most extreme capability. [ABSTRACT FROM AUTHOR]

This paper mainly deals with the design and analysis of Agriculture data using Machine Learning (ML) techniques. Agriculture includes cultivating the soil and we can grow different types of crops. In India there are 28 states and 8 Union Territories. In each and every state people are farming and they are developing our agriculture in so many ways. Every state has its own farm for example: - Andhra Pradesh-Rice, Bazra, maize, ragi, pulses etc; the other name for agriculture is "Back Bone of India ". The sediment pressure is due to erosion and soil loss. Diffusion in nature occurs in the fine-grained sediments. Statistical analysis is being carried out for effective solution based on different parameters. This helps to get more information for farmers to make critical farming decisions. Researchers focused on agriculture and found an optimal option to increase production. Experimental data is analyzed and the production is optimized for agriculture such that it is more resilient to climatic change. [ABSTRACT FROM AUTHOR]

India is an Agriculture based country and about 60% of the population depends on agriculture for their living. But there is a substantiable reduction in agricultural production has happened due to unstable climate conditions and global warming. Indian farmers are always lacking the support of advanced technologies for improving and maximizing their yield. If they get explicit information about soil type, nutrients, pH value, changes in climatic factors, previous year yield etc., they can optimize their work and yield. With the advancement of machine learning, big data analytics and cloud computing technologies, the climate and crop yield can be got predicted to the farmers. Prediction of yield in advance can help the farmers to take corrective decisions about fertilization, storage and marketing to increase their production and revenue. A huge number of studies have been conducted worldwide, on agriculture sector for the prediction of crop yield, plant diseases etc. This paper presents a brief study of different researches in India on crop yield prediction based on Machine Learning and deep learning. Most of the researchers used environmental parameters like temperature, rainfall and soil type as the main features for prediction. A number of machine learning algorithms are employed in this field and it is really a complex task to identify the best algorithm. The researchers tried to accurately predict the crop yield and thereby suggesting ways to improve production and efficient use of fertilizers. [ABSTRACT FROM AUTHOR]

In India more than 50% of total population depends on agriculture. Mainly The conventional method of ploughing and seed sowing are laborious processes and involves drudgery. Though mechanized equipment is available in the market, they are costly and small-scale farmers are not able to buy. In this paper focuses on design and fabrication of a low-cost agriculture utility vehicle for multipurpose operations such as sowing, seeding, spraying, and levelling of land. In this vehicle, a solar panel of silicon type 12v/5watts is used to automate the processes of seeding and spraying by using PMDC motors of 12v/1amp. The objective of this concept is to reduce the manpower and also avoid the time consumption utilizing solar energy. [ABSTRACT FROM AUTHOR]

Farming adds to a significant bit of India's GDP. Two significant issues in present day agriculture culture are water shortage and high work costs. These issues can be settled utilizing agribusiness task mechanization, which supports accuracy farming. Thinking about wealth of daylight in India, this paper examines the plan and improvement of an IoT based sunlight based fueled Agribot that robotizes water system task and empowers far off ranch checking. The Agribot is created utilizing RASBPBERRY PI. It harvests sun-oriented quality while now not acting water system. While executing the undertaking of water system, it developments close by a pre-chosen course of a given ranch, and faculties soil dampness substance and temperature at ordinary focuses. Further, Agribot goes about as an IOT gadget and sends the insights amassed from more than one sensor to a distant utilizing Wi-Fi connect. At the distant worker, crude realities are handled the utilization of sign preparing tasks, for example, sifting, pressure and expectation. As needs be, the examined records data is shown the utilization of an intelligent interface, as steady with client demand. [ABSTRACT FROM AUTHOR]

Indian economy is contributed heavily by agriculture. Most of the Indian farmers rely on their instincts to decide the crop to be sown at a particular time of year. They do not realize that the crop output is circumstantial, and depended heavily on the present-day weather and soil conditions. A single uninformed decision by the farmer can have undesirable consequences on the economic conditions of the region and also mental and financial impacts on the farmer himself. Applying systematic Machine Learning models will effectively help to alleviate this issue. The dataset used in the paper is built by adding up the datasets of India's rainfall, climate, and fertilizer. Machine learning models will be used on the dataset to get the highest accuracy model to recommend a crop for the farm's location. This recommendation will help the farmers in India to make learned decisions about the crops. The recommendation will take into account the parameters like the farm's location, sowing season, soil properties, and climate. [ABSTRACT FROM AUTHOR]