REVIEW 2 cited by
Sustainable and Precision Agriculture with the Internet of Everything (IoE)
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Sustainable and Precision Agriculture with the Internet of Everything (IoE)
read the original abstract
Agriculture faces critical challenges from population growth, resource scarcity, and climate change, driving a shift toward advanced, technology-integrated farming. Mechanization has transformed agriculture, enhancing sustainability and crop productivity. Now, technologies like artificial intelligence (AI), robotics, biotechnology, blockchain, and the Internet of Things (IoT) are advancing precision agriculture. The concept of the Internet of Everything (IoE) has gained traction due to its holistic approach to integrating various IoT specializations, called IoXs with X referring to a specific domain. This paper explores the transformative role of IoE in agriculture, expanding beyond traditional IoT applications to integrate niche subdomains like molecular communication (MC), the Internet of Nano Things (IoNT), the Internet of Bio-Nano Things (IoBNT), designer phages, and the Internet of Fungus (IoF). Our study provides a detailed review of how these IoE subdomains, in conjunction with 6G, blockchain, and machine learning (ML), can enhance precision farming in areas like crop monitoring, resource management, and disease control. Unlike prior IoT centric reviews, this work uniquely focuses on IoEs potential to advance agriculture at molecular and biological scales, achieving more precise resource utilization and resilience. Key contributions include an exploration of these technologies applicability, associated challenges, and recommendations for future research directions within precision agriculture.
Forward citations
Cited by 2 Pith papers
-
Estimating the Diameter at Breast Height of Trees in a Forest from RGB
A 360 RGB video pipeline using SfM, Grounded SAM, and RANSAC achieves 5-9% median relative DBH error, only 2-4% above LiDAR, on 61 acquisitions of 43 trees.
-
Information and Communication Theoretical Foundations of the Internet of Plants, Principles, Challenges, and Future Directions
A tutorial that reframes four plant communication modalities as ICT links and outlines an Internet of Plants research agenda.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.