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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 12 Issue: 04 | Apr 2025

p-ISSN: 2395-0072

www.irjet.net

Farm management System Software developed based on intelligence A. Patil Tejashri Vijay1, B. Ghadage Vaishnavi Navnath 2, C.3 Bansode Sneha Hanumant3, D. Sirsat Pratiksha Shriram 4, E. Khandekar Priyanka Ramchandra5 Patil Tejashri Vijay, Karmayogi Institute of Technology, Shelve-Pandharpur Ghadage Vaishnavi Navnath, Karmayogi Institute of Technology, Shelve-Pandharpur 3 Bansode Sneha Hanumant, Karmayogi Institute of Technology, Shelve-Pandharpur 4 Sirsat Pratiksha Shriram, Karmayogi Institute of Technology, Shelve-Pandharpur 5 Khandekar Priyanka Ramchandra, Karmayogi Institute of Technology, Shelve-Pandharpur 6 Vrunda Jayant Kulkarni, Karmayogi Institute of Technology, Shelve-Pandharpur Professor, Dept. of Computer Technology, Karmayogi Institute of Technology Shelve-Pandharpur, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------learning in preschool settings. Many researchers find it Abstract - We present an example of a smart agriculture 1

appealing to incorporate many aspects of research development in education, and they have developed creative teaching strategies that motivate students and meet the advancement requirements of numerous fields. Other scholars focus on the tools, technologies, and teaching strategies that are used during the learning process, and students are encouraged to improve their learning levels when technology is used in the classroom. To fulfill instructional goals, pupils and sophisticated educational instruments (software) must interact. Evaluating how well technological tools contribute to the learning process is the purpose of this study. New research has led to substantial advancements in artificial intelligence (AI), as it has in many other areas. AI is being applied in education to highlight personalized and dynamic learning approaches for students. Students can now obtain education that is personalized to fit their requirements thanks to developments in research, programming, technology, instructional materials, and teaching methodologies.

application and analyze its features, as well as introduce an algorithm that facilitates communication between farmers, technology, and the management system. This study shows that farmers can better manage their agricultural processes by being guided according to their job efficiency. The intelligent agriculture management system that forms the basis of this research enables farmers to monitor the condition of their crops and use technology to make timely decisions about various agricultural activities, including choosing crops that are appropriate for their land, managing water resources, and using fertilizers and pesticides. The first part talks about communicating with farmers, the second part talks about dynamic assessment of agricultural management and productivity, and the third part presents a formula that uses technology-based analysis methodologies. Key Words: Digital Assistant System, Agriculture Technology, Smart App for Farmers, Dynamic Assessment, Agricultural Management

1. INTRODUCTION

The application of AI in student assessments at the conclusion of classes has been the subject of recent study. In education, dynamic assessment lowers the problems that children confront. Our work focuses on dynamic assessment employing an intelligent system that enables teachers to alter scientific instruction in real time based on students' competency levels.

Three key sections relevant to the analysis technique form this study. The first portion explains the interactions involved, the second discusses the dynamic evaluation of various tests, and the third piece presents the formulas for studying scientific subjects. Many researchers are very interested in the use of technology in education. Ken Fisher developed methods for using technology in the classroom that support successful learning outcomes. In order to help educators fulfill their duties with confidence, Marcel Lebrun and colleagues created three resources.

A. The Impact of Mobile Technology Agriculture Brown, L. (2022):

The first, second, and third tools in the SAMR model (Substitution, Augmentation, Modification, Redefinition) are the teaching system (knowledge content and learning), technology use, and Lemke and Coughlin's "Entry, Adaptation, Transformation" model—which considers mental and educational conditions. Natalya V. Koltsova and Yelena V. Yakovleva discussed how ICT (information and communication technology) might be used to promote

A Plantix Case Study. Agricultural Technology Journal, 15(3), 45–60. This article looks at the Plantix app, which diagnoses crop problems by using image recognition. It examines how well mobile technology works to give farmers real-time answers while emphasizing user experiences and results. Instant Access to Crucial Data: Farmers now have access to a multitude of data thanks to mobile applications, which have completely changed how they engage with technology and

Impact Factor value: 8.315

2. LITERATURE SURVEY

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