학술논문

Data-Driven Decision Making for Smart Cultivation
Document Type
Conference
Source
2021 IEEE International Symposium on Smart Electronic Systems (iSES) ISES Smart Electronic Systems (iSES), 2021 IEEE International Symposium on. :249-254 Dec, 2021
Subject
Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Transportation
Temperature sensors
Temperature measurement
Costs
Decision making
Medical services
Sensor phenomena and characterization
Sensor systems
Smart Agriculture
Internet of Things
E-Agriculture
Machine Learning
Language
Abstract
With the advancement of modern technology, traditional agriculture is drastically changing, especially with the utilization of Information and Communication Technology (ICT). Ubiquitous sensors and the Internet of Things (IoT) are being used independently for helping the farmers to understand better the condition of overall field condition targeting to monitor soil characteristics, climatic conditions, humidity, temperature, etc. These sensors and systems work individually and produce different data that requires analysis to understand. The typical process is time-consuming, and farmers should have technological knowledge. Contrary, most of the farmers are not technologically advanced to understand the term. A ready-made result can help farmers quick decision-making. In this paper, we have developed a remote field monitoring and controlling IoT system architecture. The system process and analyze the collected data to prepare a ready-made report for farmers with suggestions for further steps. It leverages the management process with real-time monitoring, nursing (i.e., irrigation, pesticide distribution, etc.), ultimately increasing productivity. The overall system records every successful case, and machine learning-based prediction helps further nursing guidelines.