Efficient agricultural disaster financing using satellite data and artificial intelligence

Chen, Shijun; Lin, Huabin; Yang, Guang

doi:10.1016/j.compeleceng.2022.108394

Cited by 4 publications

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The burgeoning volume of agricultural data presents another challenge, requiring robust analytics and interpretation frameworks to extract meaningful insights. Additionally, the accessibility and affordability of advanced technologies pose barriers for small-scale farmers, necessitating inclusive solutions to ensure equitable benefits 26 .…”

Section: Literature Reviewmentioning

confidence: 99%

A fusion approach using GIS, green area detection, weather API and GPT for satellite image based fertile land discovery and crop suitability

Balasundaram,

Abdul Aziz,

Gupta

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Proper utilization of agricultural land is a big challenge as they often laid over as waste lands. Farming is a significant occupation in any country and improving it further by promoting more farming opportunities will take the country towards making a huge leap forward. The issue in achieving this would be the lack of knowledge of cultivable land for food crops. The objective of this work is to utilize modern computer vision technology to identify and map cultivable land for agricultural needs. With increasing population and demand for food, improving the farming sector is crucial. However, the challenge lies in the lack of suitable land for food crops cultivation. To tackle this issue, we propose to use sophisticated image processing techniques on satellite images of the land to determine the regions that are capable of growing food crops. The solution architecture includes enhancement of satellite imagery using sophisticated pan sharpening techniques, notably the Brovey transformation, aiming to transform dull satellite images into sharper versions, thereby improving the overall quality and interpretability of the visual data. Making use of the weather data on the location observed and taking into factors like the soil moisture, weather, humidity, wind, sunlight times and so on, this data is fed into a generative pre-trained transformer model which makes use of it and gives a set of crops that are suitable to be grown on this piece of land under the said conditions. The results obtained by the proposed fusion approach is compared with the dataset provided by the government for different states in India and the performance was measured. We achieved an accuracy of 80% considering the crop suggested by our model and the predominant crop of the region. Also, the classification report detailing the performance of the proposed model is presented.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A fusion approach using GIS, green area detection, weather API and GPT for satellite image based fertile land discovery and crop suitability

Balasundaram,

Abdul Aziz,

Gupta

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…(1) Sensitive data leakage: customer data of financial institutions involves a great deal of sensitive information, such as personal identity information, financial status, and transaction records. [43,44] In the process of AI technology www.md-journal.com application, customer data could potentially be leaked, leading to personal privacy rights violations. For example, a bank may provide customer data to third-party institutions for data analysis and mining, but these institutions may use the data for other purposes or suffer data leakage during data transmission due to hacker attacks.…”

Section: Potential Hazards Of Artificial Intelligence In Financial Da...mentioning

confidence: 99%

Ethical perspective on AI hazards to humans: A review

Chen,

Luo

et al. 2023

Medicine

View full text Add to dashboard Cite

This article explores the potential ethical hazards of artificial intelligence (AI) on society from an ethical perspective. We introduce the development and application of AI, emphasizing its potential benefits and possible negative impacts. We particularly examine the application of AI in the medical field and related ethical and legal issues, and analyze potential hazards that may exist in other areas of application, such as autonomous driving, finance, and security. Finally, we offer recommendations to help policymakers, technology companies, and society as a whole address the potential hazards of AI. These recommendations include strengthening regulation and supervision of AI, increasing public understanding and awareness of AI, and actively exploring how to use the advantages of AI to achieve a more just, equal, and sustainable social development. Only by actively exploring the advantages of AI while avoiding its negative impacts can we better respond to future challenges.

show abstract

PCB-integrated embedded planar magnetorquers for small satellites intelligent detumbling

Khan

Yang

Ali

et al. 2023

Computers and Electrical Engineering

View full text Add to dashboard Cite

Efficient agricultural disaster financing using satellite data and artificial intelligence

Cited by 4 publications

References 16 publications

A fusion approach using GIS, green area detection, weather API and GPT for satellite image based fertile land discovery and crop suitability

A fusion approach using GIS, green area detection, weather API and GPT for satellite image based fertile land discovery and crop suitability

Ethical perspective on AI hazards to humans: A review

PCB-integrated embedded planar magnetorquers for small satellites intelligent detumbling

Contact Info

Product

Resources

About