American International Journal of Research and Innovation

E-ISSN: XXXX-XXXX   •   Impact Factor: -

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 5
September-October 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Data-Driven Agricultural Decision Systems for Rural Innovation

Author(s) Peter Dorward
Country United Kingdom
Abstract Agricultural systems in rural regions face increasing challenges related to climate variability, resource limitations, market uncertainty, productivity demands, and limited access to timely information. Data-driven agricultural decision systems have emerged as important approaches for improving rural innovation by enabling evidence-based planning, intelligent resource management, and technology-supported farming decisions. This conceptual research article examines the role of data-driven decision systems in supporting agricultural transformation through the integration of artificial intelligence, machine learning, Internet of Things (IoT), remote sensing, agricultural analytics, and digital advisory platforms. The study adopts a conceptual research methodology based on the synthesis of scholarly literature, digital agriculture frameworks, agricultural decision-support models, and rural innovation approaches.
The analysis indicates that data-driven systems can enhance agricultural productivity by improving forecasting, crop monitoring, resource allocation, risk assessment, and knowledge accessibility among rural communities. However, challenges related to digital infrastructure, data quality, technology accessibility, farmer skills, affordability, and institutional support continue to influence adoption. The study concludes that data-driven agricultural decision systems can strengthen rural innovation when supported by inclusive digital strategies, reliable information networks, farmer-oriented solutions, and sustainable technology governance.
Keywords Data-Driven Agriculture; Agricultural Decision Systems; Rural Innovation; Artificial Intelligence; Digital Farming; Precision Agriculture; Agricultural Analytics
Field Engineering
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-10-11
View / Download PDF File

Share this



E-ISSN XXXX-XXXX
CrossRef

CrossRef DOI prefix of AIJRI is 10.00000/AIJRI

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About AIJRI
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +1-872-302-3851 editor@aijri.com