A systematic literature review of low-cost 3D mapping solutions

Abstract

In "low-cost" solutions, ensuring economic accessibility and democratizing the availability of emerging technologies stand as pivotal considerations. This study undertakes a systematic literature review of low-cost 3D mapping solutions. Leveraging SCOPUS as the primary database, a comprehensive bibliometric analysis encompassing 1380 publications was conducted, subsequently narrowing the focus to 87 recent publications for detailed review. This research endeavors to delineate the defining characteristics of low-cost systems, elucidate their principal applications and preferred platforms, assess accessibility level, gauge the extent of innovation in both hardware and software development, explore the contributions of Deep Learning and data fusion, evaluate the consideration of data quality, and examine the contemporary relevance of photogrammetry within low-cost context. The findings demonstrate that many authors subjectively use the term low-cost to highlight qualities of a technology, methodology or sensor, but challenges arise from data quality comparisons with high-cost systems.