Enhanced Solar Potential Analysis: Separating Terraced House Rooftops Using Convolutional Neural Networks

Zhang, Kai and Ouarbya, Lahcen. 2024. 'Enhanced Solar Potential Analysis: Separating Terraced House Rooftops Using Convolutional Neural Networks'. In: 9th IEEE International Conference on Computational Intelligence and Applications (ICCIA 2024). Haikou, China 9-11 August 2024. [Conference or Workshop Item] (In Press)

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Abstract or Description

Solar power, a clean and renewable energy source, plays a pivotal role in achieving sustainable development goals by offering affordable, reliable, modern energy solutions and mitigating energy-related emissions and pollutants. Current studies predominantly focus on solar potential analysis derived from machine learning-based rooftop area segmentation. However, these studies reveal an overestimation of usable area for solar output calculations in terraced houses, due to failing to distinguish individual households within terraced structures. This research delineates state-of-the-art Machine Learning and computer vision techniques applied on remote-sensing images obtained via the Google API. The dataset, manually annotated and augmented to include 5000 training images and 1000 validation images, is focused on the UK, particularly terraced house areas. The stand-alone Convolutional Neural Network used to segment terraced-structure rooftop areas reaches an intersection over union of 69.11%. The model uniquely addresses the segmentation of contiguous terraced houses in the UK, which is pivotal for the solar installation assessments in the UK’s residential landscape.

Item Type:

Conference or Workshop Item (Paper)

Additional Information:

“© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”

Keywords:

Solar Potential, Renewable Energy, Roof Segmentation, Terraced Houses, Convolutional Neural Network, Remote Sensin

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Departments, Centres and Research Units:

Computing

Dates:

DateEvent
24 June 2024Submitted
10 July 2024Accepted

Event Location:

Haikou, China

Date range:

9-11 August 2024

Item ID:

37186

Date Deposited:

11 Jul 2024 10:38

Last Modified:

11 Jul 2024 15:43

URI:

https://research.gold.ac.uk/id/eprint/37186

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