A wireless data collection network (DCN) is the key constituent of the IoT. It is used in many applications such as transport, logistics, security and monitoring. Despite the continuous development of DCN, communication between nodes in such network presents several challenges. The major issue is the deployment of connected objects and, more precisely, how numerous nodes are appropriately positioned to attain full coverage. The current work presents a hybrid technique, named DTABC, combining a geometric deployment method, called Delaunay Triangulation diagram DT, and an optimization algorithm named the Artificial Bee Colony (ABC) algorithm. In the centralized approach, this hybrid method is executed on a single node while, in a distributed approach, it is executed in parallel on different nodes deployed in a wireless data collection network. This study aims at enhancing the coverage rate in data collection networks utilizing less sensor nodes. The Delaunay Triangulation diagram is utilized to produce solutions showing the first locations of the IoT objects. Then, the Artificial Bee Colony algorithm is used to improve the node deployment coverage rate. The developed DTABC approach performance is assessed experimentally by prototypingM5StickC nodes on a real testbed. The obtained results reveal that the coverage rate, the number of the objects' neighbors, the RSSI and the lifetime of the distributed approach are better than those of the algorithms introduced in previous research works.