TY - GEN
T1 - Potential roles of artificial intelligence in the lci of renewable energy systems
AU - Adedeji, Paul A.
AU - Akinlabi, Stephen A.
AU - Madushele, Nkosinathi
AU - Olatunji, Obafemi O.
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd 2020.
PY - 2020
Y1 - 2020
N2 - Energy revolution from the conventional fossil fuels to clean energy is fast gaining traction with renewable and clean energy sources blazing the trail on the global scale. This has consequentially reduced electricity prices in certain countries and reduced carbon footprints in both manufacturing and service industries. Asides the advantages of these clean energy technologies, the assessment of their life cycle has recently gained more attention with life cycle inventory playing a major role. Life cycle inventory is a critical component in life cycle assessment. However, a life cycle inventory study is as accurate as the data used. This study presents a roadmap to the use of artificial intelligence (AI) techniques in life cycle inventory (LCI). The data chain for efficient local resident data availability for LCA studies was considered with a focus on AI integration. In addition, a framework for the use of AI in LCI was developed. The study concluded that it was possible to proffer solution to LCI data unavailability problem using AI with the joint support of public and private partners.
AB - Energy revolution from the conventional fossil fuels to clean energy is fast gaining traction with renewable and clean energy sources blazing the trail on the global scale. This has consequentially reduced electricity prices in certain countries and reduced carbon footprints in both manufacturing and service industries. Asides the advantages of these clean energy technologies, the assessment of their life cycle has recently gained more attention with life cycle inventory playing a major role. Life cycle inventory is a critical component in life cycle assessment. However, a life cycle inventory study is as accurate as the data used. This study presents a roadmap to the use of artificial intelligence (AI) techniques in life cycle inventory (LCI). The data chain for efficient local resident data availability for LCA studies was considered with a focus on AI integration. In addition, a framework for the use of AI in LCI was developed. The study concluded that it was possible to proffer solution to LCI data unavailability problem using AI with the joint support of public and private partners.
KW - Artificial intelligence
KW - Energy systems
KW - Life cycle assessment
KW - Life cycle inventory
KW - Renewable energy sources
UR - http://www.scopus.com/inward/record.url?scp=85091313888&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-5753-8_26
DO - 10.1007/978-981-15-5753-8_26
M3 - Conference contribution
AN - SCOPUS:85091313888
SN - 9789811557521
T3 - Lecture Notes in Mechanical Engineering
SP - 275
EP - 285
BT - Advances in Manufacturing Engineering - Selected Articles from ICMMPE 2019
A2 - Emamian, Seyed Sattar
A2 - Yusof, Farazila
A2 - Awang, Mokhtar
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Conference on Mechanical, Manufacturing and Plant Engineering, ICMMPE 2019
Y2 - 19 November 2019 through 21 November 2019
ER -