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

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
A.K. (Danny) Singh is a Professor of Agronomy and G.F. Sprague Chair in Agronomy at Iowa State University. I serve as co-director of the Iowa Soybean Research Center and Associate Chair of Discovery and Engagement in the Department of Agronomy. He holds a courtesy appointment as a Professor in the Department of Agricultural and Biosystems Engineering at Iowa State University. Upon receiving a Ph.D. degree from the University of Guelph in 2007, Danny joined Agriculture and Agri-Food Canada as a durum wheat breeder. In 2013, he moved to Iowa State University as a soybean breeder. His group’s research interests are machine learning applications in breeding and automation of breeding pipelines to develop competitive and climate-resilient varieties. He collaborates with experts from several disciplines, including plant sciences, engineering, and computer sciences. He was instrumental in establishing the concept of Cyber-Agricultural Systems with applications in plant breeding and crop production. Danny’s 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. Our breeding efforts focus on soybean and millets. He has participated in the development of >75 cultivars (annually grown in >10 million acres) and 13 germplasm lines, published >160 peer-reviewed publications, and served as a PI/co-PI on projects from multiple agencies in Canada and the U.S.A. He has given >75 invited talks nationally and internationally. He has co-authored the textbook “Plant Breeding and Cultivar Development” ISBN: 978-0-12-817563-7. [] He leads two graduate courses at ISU. He is passionate about advancing plant breeding and interdisciplinary sciences to solve farmer production issues, improve sustainability, and enhance profitability. He maintains extensive interactions with farmers to understand the complex problems, soliciting feedback and developing partnerships with farmers and the industry to create timely solutions, primarily through genetics, breeding, phenomics, genomics and cyber-agricultural systems methods and tools. He is an elected fellow of the Crop Science Society of America.
Performance Period: 10/01/2020 - 09/30/2024
Institution: Iowa State University
Award Number: 1952045