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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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              <text>Applications of Classification and Recommendation Techniques to Analyze Soil Data and Water Using IOT</text>
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              <text>Data analytics; IoT; Soil fertility</text>
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              <text>As we are moving to a computerized and scientific world, data becomes an intrinsic part of our life. Agriculture sector is still unorganized with regard to automation and data analytics. This task is accomplished through sensors, data mining and analysis. In this paper, we propose real-time sensors to detect the soil features and predict the suitable crop cultivation using trained dataset. This would help the farmers to predict the type of cultivation to be done depending on the soil features. Today, the farmer can understand what type of cultivation will be prepared in the soil. Also, people of the upcoming generation will be using that sensor, different plant can be make. The cost of cultivation can be improved. Water level of the soil can be easily predicted. Which type of plant will be produced in the different soil can be predicted. So, this new type of cultivation followed by the next generation also. This paper has presented an improved by the pH sensor, water level sensor.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <text>Thaiyalnayaki S.; Sambandam R.K.; Reddy T.H.S.; Reddy A.H.V.; Sai K.N.; Srinivas V.</text>
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              <text>Smart Innovation, Systems and Technologies, Vol-334, pp. 215-223.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-19-8497-6_22" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-8497-6_22&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164934297&amp;amp;doi=10.1007%2F978-981-19-8497-6_22&amp;amp;partnerID=40&amp;amp;md5=39148412a457f824cf2e95481ef9a06d" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164934297&amp;amp;doi=10.1007%2f978-981-19-8497-6_22&amp;amp;partnerID=40&amp;amp;md5=39148412a457f824cf2e95481ef9a06d&lt;/a&gt;</text>
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              <text>ISSN: 21903018; ISBN: 978-981198496-9</text>
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              <text>Thaiyalnayaki S., Department of Computer Science and Engineering, School of Computing, Bharath Institute of Higher Education and Research (Deemed to be University), Selaiyur, Chennai, India; Sambandam R.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Kengeri Campus, Karnataka, Bangalore, India; Reddy T.H.S., Department of Computer Science and Engineering, School of Computing, Bharath Institute of Higher Education and Research (Deemed to be University), Selaiyur, Chennai, India; Reddy A.H.V., Department of Computer Science and Engineering, School of Computing, Bharath Institute of Higher Education and Research (Deemed to be University), Selaiyur, Chennai, India; Sai K.N., Department of Computer Science and Engineering, School of Computing, Bharath Institute of Higher Education and Research (Deemed to be University), Selaiyur, Chennai, India; Srinivas V., Department of Computer Science and Engineering, School of Computing, Bharath Institute of Higher Education and Research (Deemed to be University), Selaiyur, Chennai, India</text>
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