Location-based Frequency Interference Management Scheme Using Fingerprinting Localization Algorithms

In an intelligent automated manufacturing environment, an administrator may use M2M (Machine-to-Machine) communication to recognize machine movement and the environment, as well as to respond to any potential dangers. However, commonly used wireless protocols for this purpose such WLAN (Wireless Local Area Network), ZigBee, and Bluetooth use the same ISM (Industrial Science Medical) band, and this may cause frequency interference among different devices. Moreover, an administrator is frequently exposed to dangerous conditions as a result of being surrounded by densely distributed moving machines. To address this issue, we propose in this paper to employ a location-based frequency interference management using fingerprinting scheme in industrial environments and its advanced localization schemes based on k-NN (Nearest Neighbor) algorithms. Simulation results indicate that the proposed schemes reduce distance error, frequency interference, and any potential danger may be responded immediately by continuous tracing of the locations.