Smart Integrated Farm Network for Rural Agricultural Communities (SIRAC)
Lead PI:
Asheesh Singh
Co-Pi:
Abstract

With a goal to form a community of Smart and Connected Farms (SCFs), this innovative project aims to establish a Smart Integrated Farm Network for Rural Agricultural Communities (SIRAC). The goal is to improve timely data sharing and knowledge exchange among farmers community for coordinated responses to production threats (weed, disease, insect, pest, weather), ensuring profitability. The project will develop a flexible, scalable and efficient communication infrastructure for SCFs; provide privacy-preserving data analytics across farms for community-level decision-making; establish community of practice to facilitate learning and feedback among farmers/scientists, trusted data and technology acceptance; and demonstrate economic benefit to SCFs.

The novelty of SIRAC project lies in the holistic integration of multiband dynamic spectrum access (DSA) technology for rural connectivity and community decision-making, with social translational research to address adoptability, trust, and risk preferences, and economics research to benefit farmers. Mobile crowd sensing will improve trustworthiness and decision accuracy of information spread. Fundamental contributions involve the development of novel routing algorithms, privacy-preserving machine learning techniques, and affordable communication infrastructure with unlicensed multiple spectrum bands to create SCF community for efficient data sharing. Translational research model with behavioral experiments will identify social and economic incentives for farmers/stakeholders leading to technological innovations.

The SIRAC framework has the potential to provide tremendous impacts, as it can be adapted and replicated in different rural areas. The proposed (rural) communications technology will apply to a broad range of smart and connected communities. The assessment of social and economic incentives for farmers and other stakeholders will facilitate participation in SCF network. The project will motivate next generation of scientists and farmers to contribute to smart agricultural communities with innovative solutions. Results will be disseminated via web lecture series, invited talks, a dedicated project website, participants and other communities, extension field days, conferences and workshops, and peer-reviewed journals.

The SIRAC repository will maintain computational codes, models, real world and simulation data, experimental results for two years after the project period is over. The project website will provide two levels of access: Public and Login Required. An account can be created via registration with no charge. Additionally, developed codes and simulation models will be available to the community through the Iowa State University’s digital repository. Permission will be granted to freely use and distribute the anonymized data from simulations and field experiments with due acknowledgement of the copyright notice and the authors.

Asheesh Singh
My professional interest is to help improve agricultural production and use research/breeding activities to benefit farmers and the agriculture industry by developing superior soybean cultivars and germplasm for farmers and other stakeholders. We also work on small millets. I have participated in the development of >75 cultivars (annually grown in >10 million acres) and 13 germplasm lines, published >150 peer-reviewed publications (and additionally >200 conference/meeting abstracts or posters), served as a PI/co-PI on >60 funded projects from multiple sources, and given >70 invited talks nationally and internationally. I have co-authored the textbook “Plant Breeding and Cultivar Development” (Academic Press, USA; 2021) [https://www.elsevier.com/books/plant-breeding-and-cultivar-development/singh/978-0-12-817563-7]. I lead AGRON 521 (Principles of Cultivar Development) and AGRON 522 (Field Methods in Plant Breeding) at ISU.
Performance Period: 10/01/2020 - 09/30/2024
Institution: Iowa State University
Award Number: 1952045