Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3289
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dc.contributor.authorMagenthirarajah, V-
dc.contributor.authorGamage, A-
dc.contributor.authorChandrasiri, S-
dc.date.accessioned2023-03-03T08:44:17Z-
dc.date.available2023-03-03T08:44:17Z-
dc.date.issued2022-12-09-
dc.identifier.citationV. Magenthirarajah, A. Gamage and S. Chandrasiri, "Carbon Emission Optimization Using Linear Programming," 2022 4th International Conference on Advancements in Computing (ICAC), Colombo, Sri Lanka, 2022, pp. 494-498, doi: 10.1109/ICAC57685.2022.10025276en_US
dc.identifier.isbn979-8-3503-9809-0-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3289-
dc.description.abstractIn this fast-growing modernization, excess carbon emission plays a crucial role in climate change. Targeting and experimenting with sustainable ways of Carbon neutrality and management is the pathway toward a greener society. Data show that factories and industries take a high market stake in carbon emission and management. In actions, Governments defined a limit for carbon emissions to each organization which is called carbon credit. Every organization must focus on reducing carbon emissions. This is a critical task for each organization, In some cases, it is still not possible to explore other sustainable options. An innovative solution proposed for the above scenario is to implement a real-time platform that can provide insights into the most up-to-date emission statistics of the organization. This paper provides advanced analytics and precise proactive planning and actions in the simplest form and a discussion on future elaborations and insights about conclusions. By finding the minimum optimal emission values of each emission source, organizations can maintain carbon emissions without exceeding their carbon credit. Also, how industries and factories can create a smart carbon optimization system that can create an even greener society.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2022 4th International Conference on Advancements in Computing (ICAC);-
dc.subjectOptimizationen_US
dc.subjectLinear Programmingen_US
dc.subjectCarbon Emissionen_US
dc.titleCarbon Emission Optimization Using Linear Programmingen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC57685.2022.10025276en_US
Appears in Collections:4th International Conference on Advancements in Computing (ICAC) | 2022
Department of Information Technology
Research Papers - IEEE
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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