Development of an Automated Management System for Agricultural Technologies in Horticulture

The implementation of intelligent technologies in industrial horticulture is possible with the help of an automated system for managing production processes. (Research purpose) To develop and substantiate the parameters of an automated management system for agricultural technologies in horticulture with the ability to conduct land inspections using a mobile application. (Materials and methods) ADO.NET driver Npqsql was used for work with the database. Dapper was used as Object Relational Mapping. The web application used the Model View Controller design pattern, and Bootstrap as the css framework. Data visualization from the database was carried out using cloud technology, placing the site using a set of Internet Information Services. Jquery (a set of JavaScript functions) served as the main framework for working with the client-side of the program code. The authors also used the PostgreSql database management system. The mobile application was created in the Android studio integrated environment. (Results and discussion) The authors developed an automated system for managing agricultural technologies. They formed the structure of the hardware and software base. They created the system ability to operate in a dialogue mode with the user through forms, based on the algorithm for choosing the optimal options for technological processes in the horticultural products production. A mobile application was implemented to conduct digital land inspections. They determined the procedure for conducting land inspections by agronomists using a mobile application. (Conclusions) The authors developed a system for the automated technologies formation and management in horticulture, which provided operational processing of information flows in real time, reflecting the characteristics of the plants’ growth and state in critical phases of development. They provided modern recording devices and a mobile application operation. They showed that the system automatically optimized machine technologies for the cultivation of horticultural crops according to biological (realization of the potential biological productivity of crops) and economic (increasing the efficiency of using production resources) criteria.

Implementation of a Decision Support System and Business Intelligence Algorithms for the Automated Management of Insurance Agents Activities

Data processing is crucial in the insurance industry, due to the important information that is contained in the data. Business Intelligence (BI) allows to better manage the various activities as for companies working in the insurance sector. Business Intelligence based on the Decision Support System (DSS), makes it possible to improve the efficiency of decisions and processes, by improving them to the individual characteristics of the agents. In this direction, Key Performance Indicators (KPIs) are valid tools that help insurance companies to understand the current market and to anticipate future trends. The purpose of the present paper is to discuss a case study, which was developed within the research project "DSS / BI HUMAN RESOURCES", related to the implementation of an intelligent platform for the automated management of agents' activities. The platform includes BI, DSS, and KPIs. Specifically, the platform integrates Data Mining (DM) algorithms for agent scoring, K-means algorithms for customer clustering, and a Long Short-Term Memory (LSTM) artificial neural network for the prediction of agents KPIs. The LSTM model is validated by the Artificial Records (AR) approach, which allows to feed the training dataset in data-poor situations as in many practical cases using Artificial Intelligence (AI) algorithms. Using the LSTM-AR method, an analysis of the performance of the artificial neural network is carried out by changing the number of records in the dataset. More precisely, as the number of records increases, the accuracy increases up to a value equal to 0.9987.

STUDENT MICRO LOAN MANAGEMENT SYSTEM

In the daily transmuting scenarios of the financial world, lenders and students are searching for new, modern and digital techniques to manage their loans through an automated management system that can ease their effort. The need of this system is to make the process flexible, scalable, agile and fast while being more affordable and reliable. Student Micro Loan Management System is an application which will provide users information with different types of loan available for students. This application gains the headway of an understudy and moneylender simple in giving the confirmed data about student micro loan. This project provides the information about various details of Student micro (Tuition and facilities) loans which are allocated for students. This task accumulates all the data of the advances. This project provides the information about various details of education loans and makes it available to users in user-friendly website/app.