Suman et al. (2026) Digital Twins in Agriculture: Revolutionizing Climate Resilience with AI and IoT

Identification

• Journal: Lecture notes in networks and systems
• Year: 2026
• Date: 2026-01-01
• Authors: Swati Suman, SUMIT RAY, Ajay Kumar Prusty, Umesha C, Girish Prasad Rath, S. Patnaik, Ankita Priyadarshini, Swagat Shubhadarshi, Pavan Kumar Pandey, Lalithamma M
• DOI: 10.1007/978-3-032-06688-6_43

Research Groups

• Centurion University of Technology and Management, Paralakhemundi, Odisha, India
• Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, UP, India
• Siksha ‘O’ Anusandhan University, Bhubaneshwar, Odisha, India
• MITs Institute of Professional Studies, Rayagada, Odisha, India

Short Summary

This paper explores how Digital Twins (DTs), Artificial Intelligence (AI), and the Internet of Things (IoT) can revolutionize agriculture by enabling real-time data-driven decisions to enhance climate resilience, productivity, and food security. It highlights the potential of these integrated technologies to predict climate impacts, optimize resource allocation, and improve farm output.

Objective

• To investigate the transformative role of Digital Twins, AI, and IoT in developing climate-resilient agriculture by enabling data-driven decision-making for crop development, productivity, and climate mitigation.

Study Configuration

• Spatial Scale: Conceptual and global, focusing on the broad application of technologies in agriculture, with mentions of micro-localized applications.
• Temporal Scale: Real-time data processing and future prediction of climate patterns, pest infestations, and disease outbreaks.

Methodology and Data

• Models used: AI-powered models for analyzing large volumes of data and forecasting.
• Data sources: Syntactic sensory data, drones, satellite data, and various integrated sources from IoT devices.

Main Results

• Digital Twins, powered by AI and IoT, can transform agriculture by providing real-time, data-enabled insights for crop development and high productivity.
• These technologies facilitate the prediction of drought periods, optimization of irrigation scheduling, and informed crop rotation strategies.
• AI analyzes vast datasets to forecast climate change consequences, pest infestations, and disease outbreaks, enabling proactive interventions.
• Precision agriculture, utilizing AI, IoT, and Big Data analytics, allows for improved resource allocation, optimized agricultural practices, and enhanced farm output, making DTs a potential game-changer for sustainable agriculture.

Contributions

• This article synthesizes the integration of Digital Twins, AI, and IoT as a comprehensive framework to address climate change challenges in agriculture, emphasizing their combined potential for revolutionizing climate resilience and sustainable farming practices.
• It highlights the practical applications of these advanced technologies across various agricultural domains, from animal monitoring to predictive maintenance.

Funding

• Not specified in the provided text.

Citation

@article{Suman2026Digital,
  author = {Suman, Swati and RAY, SUMIT and Prusty, Ajay Kumar and C, Umesha and Rath, Girish Prasad and Patnaik, S. and Priyadarshini, Ankita and Shubhadarshi, Swagat and Pandey, Pavan Kumar and M, Lalithamma},
  title = {Digital Twins in Agriculture: Revolutionizing Climate Resilience with AI and IoT},
  journal = {Lecture notes in networks and systems},
  year = {2026},
  doi = {10.1007/978-3-032-06688-6_43},
  url = {https://doi.org/10.1007/978-3-032-06688-6_43}
}