The Internet of Things (IoT) has the vision to interconnect everything of the physical world and the virtual world. Advanced automated and adaptive connectivity of objects, systems, and services is expected to be achieved under the IoT context, especially in the industrial environment. Industry 4.0 with the goal of intelligent and self-adaptable manufacturing is driven by the IoT. The Object Layer, where real-time and reliable information acquisition from the physical objects carried out, is the basic enabler in the 3-layer industrial IoT system. Such acquisition system features deterministic access, reliable communication with failure resistance mechanism, latency-aware real-time response, deployable structure/protocol, and adaptive performance on various QoS demands. This thesis proposes a reliable RFID communication system for acquisition in the industrial environment. A discrete gateway structure and a contention-free communication protocol are designed to fulfill the unique system requirements. Such gateway structure offers a flexible configuration of readers and RF technologies. It enables a full duplex communication between the objects and the gateway. The designed MF-TDMA protocol can enhance the failure resistance and emergency report mechanism thanks to the separation of control link and data link in the gateway. Specifically, an optional ARQ mechanism, an independent/uniform synchronization and control method, and a slot allocation optimization algorithm are designed besides time-division and frequency-division multiplexing. Protocol implementations for different industrial situations illustrate the system ability for supporting the demands of various QoS. Finally, a 2.4-GHz/UWB hybrid positioning platform is explored based on the introduced RFID system. Taking advantage of the UWB technology, the positioning platform can achieve positioning accuracy from meter level to centimeter level. Hybrid tag prototype and specific communication process based on the MF-TDMA protocol are designed. An SDR UWB reader network, capable of evaluating multiple algorithms, is built to realize accurate positioning with an improved algorithm proposed. / <p>QC 20161109</p>