ABSTRACT
Climate change is one of the biggest issues we face, besides Covid [6], we head into the future. Many strive to live more sustainably so that the choices made in our daily lives don’t adversely impact our planet. Food is one area of sustainability that is focused on, especially the impact of what we eat and how we can make choices that do not negatively affect the environment. The problem is how to effectively model the environmental impact of food production in a way that is useful to consumers, food manufacturers, and other individuals concerned about sustainability. To address this, an ontology and a knowledge graph are developed to capture CO2 emissions emitted by the various stages involved in the manufacture and distribution of food as a barometer for environmental impact, potential alternatives, and how the CO2 emissions measure up. The scope of our work is limited to the environmental impact of food production as measured by CO2 emissions and categories including feeding animals, land use, and transportation.
- Shivansh Gupta, Sanju Tiwari, Fernando Ortiz-Rodriguez, and Ronak Panchal. 2021. KG4ASTRA: question answering over Indian missiles knowledge graph. Soft Computing 25 (2021), 13841–13855.Google ScholarDigital Library
- Elisa F Kendall and Deborah L McGuinness. 2019. Ontology engineering. Synthesis Lectures on the Semantic Web: Theory and Technology 9, 1 (2019), i–102.Google Scholar
- L Thorne McCarty. 1989. A language for legal discourse i. basic features. In Proceedings of the 2nd international conference on Artificial intelligence and law. 180–189.Google ScholarDigital Library
- Jose Melchor Medina-Quintero, Demian Abrego-Almazán, and Fernando Ortiz-Rodríguez. 2018. Use and usefulness of the information systems measurement. a quality approach at the mexican northeastern region. Cuadernos de Administración 31, 56 (2018), 7–30.Google Scholar
- Fernando Ortiz-Rodriguez, Jose Melchor Medina-Quintero, Sanju Tiwari, and Vicente Villanueva. 2022. EGODO ontology: sharing, retrieving, and exchanging legal documentation across e-government. In Futuristic Trends for Sustainable Development and Sustainable Ecosystems. IGI Global, 261–276.Google Scholar
- Sanju Tiwari, Onur Dogan, MA Jabbar, Shishir Kumar Shandilya, Fernando Ortiz-Rodriguez, Sailesh Bajpai, and Sourav Banerjee. 2022. Applications of machine learning approaches to combat COVID-19: a survey. Lessons from COVID-19 (2022), 263–287.Google ScholarCross Ref
- Boris Villazón-Terrazas, Fernando Ortiz-Rodríguez, Sanju M Tiwari, and Shishir K Shandilya. 2020. Knowledge graphs and semantic web. Communications in Computer and Information Science 1232 (2020), 1–225.Google Scholar
Recommendations
Double Counting in Supply Chain Carbon Footprinting
<P>Carbon footprinting is a tool for firms to determine the total greenhouse gas (GHG) emissions associated with their supply chain or with a unit of final product or service. Carbon footprinting typically aims to identify where best to invest in ...
Comparative Carbon Footprint and Environmental Impacts of LiFePO4 - LiCoxNiyMn(1-x-y)O2 Hybrid Batteries Manufacturing
Intelligent Robotics and ApplicationsAbstractAlthough the electrification of the transportation sector is crucial to mitigating climate change and the energy crisis, understanding the carbon footprint and environmental impact of the manufacturing process for the power batteries used in ...
Low carbon chance constrained supply chain network design problem
A chance constrained programming based sustainable supply chain network design model has been proposed.Benders based solution methodology has been proposed.Carbon emissions & Cap and trade issue have been addressed.Performance of the algorithm has been ...
Comments