An Integrated GIS and Knowledge-Based Automated Decision Support System for Precision Agriculture Using IoT

Lavanya, R.; Ganesan, Vinoth Chakkaravarthy; Alli, P.

doi:10.4018/978-1-5225-9004-0.ch006

Cited by 5 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The "same" crop may have been planted by village farmers for many years, weather patterns and pests and illnesses have changed in soil circumstances. Using the suggested approach, updated received information allows farmers to handle and even benefit from these changes (Lavanya et al 2020). Hu et al (2020) proposed the implementation of combining operational management theories with IoT-based smart agriculture systems to expand quickly, allowing stakeholders and lift the extensive improvement of the whole agribusiness industry chain.…”

Section: Introductionmentioning

confidence: 99%

Review on implementation of IoT for environmental condition monitoring in the agriculture sector

Kumar

Karthikeyan

2021

J Ambient Intell Human Comput

View full text Add to dashboard Cite

In the development of the nation agriculture plays a significant role. IoT technology helps gather knowledge about environments such as wind, precipitation, temperature, and soil fertility. IoT allows farmers to get connected to their farm from anywhere at any time. Difficulty regarding agriculture has been always hampered; slow down the development of the country. These patterns benefit people in many respects, such as analysis using IoT and artificial intelligence, data sharing, and analytics in an unparalleled way. In this paper, we review IoT implementation in monitoring the environmental conditions of the crops and farms in various agriculture sectors. Additional IoT monitoring, control, and optimization functionality may be used to remotely monitor the control systems or actuators attached to the microcontrollers to ensure that the crop can react promptly as required. In this article, today's climatic change scenario aims to establish a comprehensive vision of IoT implementation in the farming sector to improve agricultural production in the future, as well as to guarantee the constant supplier of food. We describe the advantages of applying IoT on livestock, weather surveillance, the agricultural warehouse, and the intelligent irrigation technique. KeywordsInformation and invention scheme in agriculture (AKIS) • Program of operational groups (OGs) • Decision support systems (DSS) • Food Reserve Agency (FRA) • Rural Development Program (RDP)

show abstract

Section: Introductionmentioning

confidence: 99%

Review on implementation of IoT for environmental condition monitoring in the agriculture sector

Kumar

Karthikeyan

2021

J Ambient Intell Human Comput

View full text Add to dashboard Cite

show abstract

AGRO: A smart sensing and decision-making mechanism for real-time agriculture monitoring

Koteish

Harb

Dbouk

et al. 2022

Journal of King Saud University - Computer and Information Scie

View full text Add to dashboard Cite

Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review

et al. 2023

View full text Add to dashboard Cite

Due to the increasing global population and the growing demand for food worldwide as well as changes in weather conditions and the availability of water, artificial intelligence (AI) such as expert systems, natural language processing, speech recognition, and machine vision have changed not only the quantity but also the quality of work in the agricultural sector. Researchers and scientists are now moving toward the utilization of new IoT technologies in smart farming to help farmers use AI technology in the development of improved seeds, crop protection, and fertilizers. This will improve farmers' profitability and the overall economy of the country. AI is emerging in three major categories in agriculture, namely soil and crop monitoring, predictive analytics, and agricultural robotics. In this regard, farmers are increasingly adopting the use of sensors and soil sampling to gather data to be used by farm management systems for further investigations and analyses. This article contributes to the field by surveying AI applications in the agricultural sector. It starts with background information on AI, including a discussion of all AI methods utilized in the agricultural industry, such as machine learning, the IoT, expert systems, image processing, and computer vision. A comprehensive literature review is then provided, addressing how researchers have utilized AI applications effectively in data collection using sensors, smart robots, and monitoring systems for crops and irrigation leakage. It is also shown that while utilizing AI applications, quality, productivity, and sustainability are maintained. Finally, we explore the benefits and challenges of AI applications together with a comparison and discussion of several AI methodologies applied in smart farming, such as machine learning, expert systems, and image processing.

show abstract

An Integrated GIS and Knowledge-Based Automated Decision Support System for Precision Agriculture Using IoT

Cited by 5 publications

References 1 publication

Review on implementation of IoT for environmental condition monitoring in the agriculture sector

Review on implementation of IoT for environmental condition monitoring in the agriculture sector

AGRO: A smart sensing and decision-making mechanism for real-time agriculture monitoring

Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review

Contact Info

Product

Resources

About