AI BASED FARM ACCOUNT TRACKING AND PREDICTION SYSTEM

OZOUGWU, DAVID EBUBECHI (2026) AI BASED FARM ACCOUNT TRACKING AND PREDICTION SYSTEM. Other thesis, Godfrey Okoye University, Enugu.

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Abstract

The increased need of efficient farm monetary management also signifies the incapability of older techniques in keeping farm’s financial records. Majority of farmers keeping their accounts by a piece of paper and by diary. This technique results in numerous mistakes like mathematical errors, lost documents, messy and unstructured data and poor planning of agricultural ventures. However most of the farmers rely upon their intuition to predict future investment and earn. Therefore the study on risk is also higher. This project design and development of AI-Based Farm Account Tracking and Prediction System, to enhance effective financial management among crop farmers. The system is capable to store the financial details of the farm, such as cost of input and profit. The project automates the process of calculating profit and loss, generation of report, and predicts the farm’s future profit based on AI techniques. This project implemented using the client-side framework HTML, CSS, JavaScript as user interfaces while server side frame work, such as flask, python as backend, MySQL for the database, and Scikit-learn as the Machine learning Model. Based on a supervised learning-based approach which involved regression models was utilized to investigate patterns in past farm data for the purposes of predicting future earnings. To make sure of the success of this project, performance of the system was evaluated. Which is tested and assessed using; System Testing: to ensure the validity of software’s functionality in expenses and profits calculation and report generation, Model Evaluation: to evaluate the performance of the machine learning models used to predict the farm’s income, using statistical measurements of error like the Mean Absolute Error, and R-squared metrics. User Testing: To measure the system's usability by the end users who actually are crop farmers. The system’s testing and evaluation results clearly indicated a successful record of the entire process of expenses and income management of the farm and also proven its efficiency to calculate profit and loss, create reports and accurately predict farm’s income with greater degree. From the outcome, it can be concluded that AI-Based Farm Account Tracking and Prediction System helps to boost the recording quality of the farmers in their respective farms and to take accurate decisions to reduce investment risk for more sustainability crop cultivation and farming system.

Item Type:	Thesis (Other)
Subjects:	Q Science > Q Science (General)
Divisions:	Faculty of Computing And Information Technology (FACIT)
Depositing User:	Uchenna Eneogwe
Date Deposited:	29 Jul 2026 15:27
Last Modified:	29 Jul 2026 15:27
URI:	http://eprints.gouni.edu.ng/id/eprint/6082

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