Hybrid Conferencee

International Conference on AI in Data Science for Agriculture (ICIADSA - 26)

31st - 1st January 2027 | Venice, Italy
Sample Abstract
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Conference Brochure
Sample Full Paper
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Venice. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Venice event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Venice conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Venice, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Venice."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICIADSA aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Artificial Intelligence,Data Science,Machine Learning, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
AI applications in precision agriculture
02
Data science for crop yield prediction
03
Machine learning in soil health analysis
04
AI-driven pest detection systems
05
Data analytics for sustainable farming practices
06
Remote sensing data in agriculture
07
Challenges in agricultural data collection
08
AI for optimizing irrigation systems
09
Predictive analytics for agricultural markets
10
Data-driven decision making in farming
11
AI-enhanced livestock management techniques
12
Ethics of AI in agricultural practices
13
AI for climate impact assessment in agriculture
14
Integrating IoT with agricultural data science
15
AI applications in food supply chain
16
Data visualization for agricultural insights
17
Future trends in agri-tech and AI
18
AI for enhancing biodiversity in agriculture
19
Data science in agricultural policy making
20
Collaborative farming through data sharing