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| S.No | Existing work | Findings | Drawbacks |
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| 1 | Huang and Chang [5] | By developing an adaptive approach for determining the image index, the optimum multiattribute composite index is developed | A composite index is altered when any one of its attributes is updated. Large entries frequently make up composite indexes |
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| 2 | Khettabi et al. [6] | The acquired data were divided into clusters during the clustering phase using DBSCAN (density-based spatial clustering of applications with noise), allowing for the creation of parallel indexes with minimal overlap | The DBSCAN method does not work with clusters of different densities. It fails while dealing with high-dimensional data |
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| 3 | Limkar and Jha [7] | The new method for sequentially creating R-trees with Apache spark. The usage of the IoT zetta platform depends on how real-time data is indexed in R-tree and its variants, enabling real-time responses to geographical range queries | It is quite expensive and lacks real-time data processing |
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| 4 | Nashipudimath et al. [8] | Probabilistic feature patterns | It is quite expensive and lacks real-time data processing |
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| 5 | Zhu et al. [9] | Hierarchical multidimensional hybrid indexing | The clustering in image makes more complex n images |
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| 6 | Benrazek et al. [10] | Fuzzy clustering model | The segmentation of image is not precise |
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| 7 | Wan et al. [11] | Voronoi-based algorithm | It is very energy consumption |
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| 8 | Yu et al. [12] | Geospark-R tree | It more complex in indexing large data sets |
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| 9 | Krishnaraj et al. [13] | Radix tree indexing (RTI) | It lacks in data processing |
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| 10 | Xia et al. [14] | Distributed access pattern R-tree (DAPR-tree) | It has numerous tree nodes |
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| 11 | Alkathiri et al. [15] | Multispectral raster data | It is more complexity and cost expensive |
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| 12 | Abdullahi et al. [16] | B + tree data structure | The drawback is difficulty of traversing the keys sequentially |
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| 13 | Xie et al. [17] | Double-bit quantization | This method is more complexity during clustering |
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| 14 | Liu et al. [18] | Common representation model | It has low level features that are not able to describe |
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