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Today's rapidly growing different technologies including agriculture is act as a major part of our India. Farming innovates the massive growth in the economy of India. In recent years, the government of India has launched a digital agriculture mission for projects based on new technologies such as artificial intelligence, blockchain, remote sensing, and GIS technology, the use of drones and robots, and so on. Waleed et al. (2021) enforced the multi-class supervised machine learning techniques for classifying the agriculture farm machinery. IoT and machine learning algorithms have been widely used for automation and analysis (Gomez-Chabla et al., 2019; Jha et al., 2019). Kumar et al. (2015) developed Crop Selection Method for maximizing crop net production rate throughout the season. Design a crop field control system based on node sensors, with data management via smartphone and a web application (Muangprathub et al., 2019). In Agriculture, crop production depends on the season, biological, and economic cause. So, predicting agricultural yield is a challenging and desirable task for every state of India (Sujatha, 2016). Crop Advisor is a user-friendly web page that forecasts the impact of climate variables on crop output (Veenadhari et al., 2014). Son (2020) presented the Random Forest and SVM models for large-scale rice yield projections were found to be successful. Suganya et al. (2020) proposed a method using supervised learning techniques for the recommendation of Crops to be farmed based on soil, weather, and previous year's production data to the farmers. Droughts with lower geographical extents have become more common as a result of recent climate changes (Mohammed et al., 2018). Conservation agriculture has long been viewed as a cost-effective and environmentally friendly method of increasing crop yield (Xiao et al., 2020). Shukla (2018) in her research compares the performance of various machine learning methods for large-scale crop classification. It is found from the literature review that the crops like Wheat, paddy, red tensils, etc were used in most of the places in the southern districts of Tamilnadu. Machine learning approaches, for example, can improve decision-making by providing better risk and variability management to achieve maximum yields and improve economics (Antonopoulos et al., 2020).
Farmers face challenges during the cultivation of specific crops by unpredictable climatic changes and a drastic reduction in water resources. In India, New technologies had been implemented in the agricultural sector and it is being spread out throughout our nation. This new technology could help the farmers to accurately find the climate forecast, low level of water usage, maximize the yield, and get more profits. The most important techniques of agriculture equipment have led to efficient tilling, harvesting, and a reduction in physical work. Modern farm machinery has increased in size, speed, and productivity, allowing for more efficient cultivation of greater land. Seed, irrigation, and fertilizers have all improved significantly, allowing farmers to enhance yields.
Figure 1.
Types of agriculture equipment used in farming