The use of real prototyping systems allows implementing real-world deployments which permit evaluating new protocols, algorithms and network solutions. This study covers the problem of 3D indoor redeployment of connected objects in DL-IoT collection networks. The objective is to choose the right positions in which connected objects are added to an initial configuration, while optimizing a set of objectives. The approach used to solve this problem is based on a new hybrid optimization algorithm that combines a strategy of incorporation of user preferences (PI-EMO-VF) with a recent variant of the genetic algorithms (NSGA-III). The obtained numerical results and the real experiments on our testbed prove the effectiveness of the proposed approach compared to another recent optimization algorithm (MOEA/DD).