racteristics with network topology, which is more relevant in the case of indoor scenarios. This is once again given by the lower clearance conditions of wireless links within the indoor scenario, usually limited by the presence of walls and higher density of clutter. Different effects such as signal guiding within the central corridor or predominant shadowing effects within lateral locations of the scenario can be seen. Similar results have also been obtained for vertical cut planes within the indoor warehouse scenario for unloaded and loaded pallets, which are shown in Figs. 8.15 and 8.16, respectively. Implementation of Context-Aware Environments with Massive IoT Systems Location A. h=1.5m Location B. h=1.5m Location c. h=8.9m Delay (ns) Location D. h=1.5m Location E, h=1.5m Location F. h=1.5m Delay (ns) Location G. h=8.9m Location H. h=1.5 5m Location I, h=1.5m Delay (ns) Fig. 8.11 Estimation of power delay profiles for three different transceiver locations, considering frequency of operation of f@868MHz. The location for each one of the transceiver locations is given by a red dot within the scenario I. Picallo et al. 32.16m 52.15m Fig. 8.12 Representation of the warehouse scenario implemented in order to perform wireless channel analysis based in 3D RL approach. The scenario is a logistic operator warehouse, in which a varying density of pallets with variable loads of assets can be located at different height levels within the scenario [dBm] [dBm] [dBm] X-axis (m) X-axis (m) X-axis (m) Fig. 8.13 Estimation of distribution of received power levels for the indoor warehouse scenario, considering frequencies of operation f@ 868 MHz, f@2.4 GHz, and f@3 3.5 GHz, for constant height horizontal planes at a cut-plane height of 1.5 m in the case of unloaded pallets within the scenario As in the previous cases, linear TX-RX radial distributions of received power levels have been obtained for the scenario, considering both unloaded and loaded pallets within the warehouse, depicted in Fig. 8.17. Three different link heig