With the rapid development of cloud computing technology, more and more users choose to outsource image data to clouds. To protect users’ privacy and guarantee data’s confidentiality, images need to be encrypted before being outsourced to CSP, but this brings new difficulties to some basic yet important data services, such as content-based image retrieval (CBIR). In this paper, a privacy-preserving image retrieval method based on an improved BoVW model is proposed. An improved BoVW method based on Hamming embedding can provide binary signatures that refine the matching based on visual words; therefore, retrieval precision is improved significantly; orthogonal transformation is utilized to implement privacy-preserving image retrieval, where image features are divided into two different fields with orthogonal decomposition, for which encryption and distance comparison are executed separately, and two kinds of operation results are fused in the final vector with orthogonal composition. As a result, cloud server can extract components from encrypted features directly and compare distance with those of query image, without violating the privacy of images and features. Any algorithm can be used to encrypt features, which enhance the practicability of the proposed method. The security analysis and experimental results prove its security and retrieval performance.

Motivation: Life Cycle Assessment (LCA) is a valuable tool for quantifying environmental impacts in construction. However, inconsistencies between software outputs may compromise effective decision-making. Knowledge Gap: In New Zealand’s construction sector, practitioners have limited guidance in selecting suitable LCA tools due to gaps in software scope, data transparency, and the quality of result interpretation. Aim and Objectives: This study investigates inconsistencies in results produced by eight widely used LCA software tools and identifies the key factors contributing to these variations. Research Method: This study uses a comparative analysis with data from a timber-framed warehouse project in Auckland, New Zealand. Eight software tools (SimaPro V9.0, openLCA V2.0, LCAQuick V3.5, Building Carbon Calculator V1.0, CCaLC2 V3.1, eTool V5.0, One Click LCA, and Athena Impact Estimator for Buildings V5.4) were evaluated across 14 environmental impact categories using standardised inputs. Preliminary Findings: Substantial inconsistencies were observed even with standardised inputs, although SimaPro V9.0 and openLCA V2.0 provided the most consistent results. These findings highlight the importance of software selection for reliable environmental assessments. Research Significance: This study aids industry practitioners in selecting effective LCA tools for sustainable construction practices.