# Determination of Point-to-Point 3D Routing Algorithm Using LiDAR Data for Noise Prediction
## 6 Future Scope
Source (S1) is the source point at ground and Source (S2) at some height (which can vary) and Destination (D1) is the destination point at ground and Destination (D2) at some height (which can vary). Finding the reflection point \"R\" for a general case where source at \"h1\" height and destination at \"h2\" height is taken with incident angle \(\alpha\) and reflected angle \(\beta\). Figure S11. Image classification is done to determine the ground type of an area for reflection. Figure S12. (a) Here, the plane between the source and destination is non-uniform. There exist number of point data defines the non-uniformly. Point 1 to Point 29 defines random points on the source-destination plane. \"h1\" is height of source from the plane at S1 and \"h2\" is height of destination from the plane at D1. (b) Point number \"1\" is taken to check the difference between angle incidence \(\alpha\) and angle of reflection \(\beta\). Where \"T\" defines the intersection point of line between the S1 and the point \"1\" with Line D1-D2. (c) Here, point number \"12\" is taken and calculate the \"T\" point which is an intersection of line S1-point 12 and Line D1-D2. After that a normal is drawn at point number 12 per perpendicular to S1-T line to calculate difference between \(\alpha\) and \(\beta\). (d) \"S\" is source and \"D\" is destination R is reflection point found by applying law of reflection between S and D. Figure S13. (a) Triangulation of buffer region near the R point found for uniform plane. This process is done to find the accurate reflection on ground which is affected due to non-uniform plane, (b) Checking every point in buffer to check at which point angle difference between incident angle and reflected angle is least and the route difference is least, (C) In this figure Reflection point (R') is found after checking all points in buffer region near the reflection point first find between source and destination, (d) Reflection from the plane on ground and the arrow indicates the path from source to destination, (e) \"S\" is source and \"D\" is destination, R' is new reflection point received. Figure S14. (a) Source and destination at height h1 and h2 is given. \"jkl\" is the cutting plane (XY) which is perpendicular to Z (between source and destination). Plane \"jkl\" cuts the building at \"m\" and \"n\", (b) Length of k to l is equal to the line length between S2 and D2. Number of points from 1 to 15 are taken between k-l and check the difference if incidence and reflected angle for every point. Difference value least with minimum route length will be the point of reflection on wall, (c) Point of reflection where difference between incident angle \"\(\alpha\)\" and reflected angle \"\(\beta\)\" is minimum. Point that has the minimum route length is the point number 10, (d) \"S\" is source and \"D\" is destination and R' is the new reflection point found on wall of building. Figure S15. Source at S (4,4,5,4) and destination at D (11,4,5,8), building has A, B, C, D ground corner points of building and height of building is 15 m. Here 1, \(\alpha\) are point of intersection on building which forms top way path. Similarly, s1, s2, s3, s4 are points on building forming path around the sides. Figure S16. (a) Building LiDAR points with Accuracy (\(\pm\)3 cm), (b) Point accuracy is (\(\pm\)3 cm) means in all directions the maximum error is 6 cm, From the least square method 1, 2, 3 pairs of lines intersect to find a building corner, (c) With (\(\pm\)3 cm) Accuracy at each point, there may be a shift of 3 cm in both directions while calculating the building corner, (d) For the Building corner points due to LiDAR point accuracy is (\(\pm\)4.5 cm). Table S1: Noise level calculation with error or without error at destination location. Supplementary SectionS1: Literature Review; Section S2.1 (LiDAR Data acquisition); Section S2.2 (Building Edges and corner extraction); Section S2.3 (Indirect Route determination); Section S3 (Results and Discussions).