AgriNexus: A Next-Gen IoT-Driven Autonomous Ecosystem for Smart Agriculture
In the agriculture sector, various difficulties include resource depletion, workforce deficiencies, and climate change. Outdated IOT assembled resolutions for conservation in powering and observing farming operations, but still impose an enormous amount of human engagement. Now, we familiarize Agri Nexus, a cutting-edge IoT-powered self-sufficient ecosystem that trusts blockchain, edge computing, artificial intelligence, and drone technology. Agri Nexus's energetic resource allocation, modernized farm management, and predictive analytics have made real-time decision-making possible. This technique originates significantly in pesticide routines while augmenting yield proficiency by using drones operational with biosensors for scattered insect control and crop fitness monitoring. By reducing latency and enhancing real-time processing, edge computing succeeds in faster responses to environmental changes. Furthermore, supplies are nontoxic and translucent to blockchain-based smart contracts. On a 50-acre smart farm, our pilot research has shown a 40% reduction in pesticide use, a 25% boost in crop output, and a 30% lessening in water use. The decisions suggest that Agri Nexus meets a transformative approach to workable and independent agriculture, demanding minimal human intervention while exploiting efficiency. Upcoming efforts goals to augment AI models and enlarge blockchain claims for broader scalability. Agri Nexus indicates a significant bound toward self-sustaining, data-driven agricultural ecosystems that elevate efficiency and sustainability.
Authors
- Rebecca Ape
- G. Amirthayogam
- Raghav Sundar (ORCID: https://orcid.org/0000-0001-9423-1368)
- G. Arunkumar
- Sheela Pitta
- Krishna Manam
Institutions
- Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN)
- National Institute of Technology Andhra Pradesh (IN)
- Rajiv Gandhi University of Knowledge Technologies (IN)
Publication Details
- Published
- 2025-05-21
- DOI
- https://doi.org/10.1109/icaiss61471.2025.11041820
- Citations
- 2
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 3.50