Exploiting Automated Planning to Compute Carbon Footprint Mitigation Plans for the Agricultural Sector

Exploiting Automated Planning to Compute Carbon Footprint Mitigation Plans for the Agricultural Sector | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploiting Automated Planning to Compute Carbon Footprint Mitigation Plans for the Agricultural Sector Angela María Rodríguez, Julian René Muñoz Burbano, Jose Adrián Alvarado Imbachí, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7934964/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The agricultural sector has experienced significant benefits at all its stages (planning and preparation, planting, crop maintenance, harvesting, post- harvest, and commercialization) thanks to Artificial Intelligence advances. Combined with the Internet of Things, Artificial Intelligence algorithms pro- vide detailed information on crop health, enabling early detection of diseases or pests. Although the applications of Artificial Intelligence to transform agriculture practices are vast, there are no studies on how to exploit these al- gorithms to mitigate the carbon footprint generated by agricultural activities, which contribute to 14% of global greenhouse gas emissions. In this paper, we present AP4CF, an approach that models the problem of mitigating the carbon footprint generated by agricultural activities using a State Transition System. Our model enabled us to apply the Artificial Intelligence technique known as Automated Planning to generate carbon footprint mitigation plans automatically from a series of mitigation activities collected during a thor- ough literature review. AP4CF was evaluated in terms of planning time, plan length, and estimated cost of computed plans. The results demonstrate the flexibility and scalability of AP4CF to new products, extending beyond the agricultural sector. Agricultural Engineering Carbon Footprint Mitigation GreenHouse Gas Emissions Automated Planning State Graph State-Transition System Agricultural Activities Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7934964","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":534142525,"identity":"2db105da-c732-46a9-967d-5ea75be27244","order_by":0,"name":"Angela María 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Combined with the Internet of Things, Artificial Intelligence algorithms pro- vide detailed information on crop health, enabling early detection of diseases or pests. Although the applications of Artificial Intelligence to transform agriculture practices are vast, there are no studies on how to exploit these al- gorithms to mitigate the carbon footprint generated by agricultural activities, which contribute to 14% of global greenhouse gas emissions. In this paper, we present AP4CF, an approach that models the problem of mitigating the carbon footprint generated by agricultural activities using a State Transition System. Our model enabled us to apply the Artificial Intelligence technique known as Automated Planning to generate carbon footprint mitigation plans automatically from a series of mitigation activities collected during a thor- ough literature review. AP4CF was evaluated in terms of planning time, plan length, and estimated cost of computed plans. 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