Enhancing The Performance Of Biological Sensor Validation Using Fusion Technique
Sensors are used for providing a system with needed data considering some features of interest in the environment of system. Multi-sensor fusion would provide more accurate and reliable information. Key words: multi-sensor fusion, biological sensor, data fusion approach, fused sensor, neural network approach, simulated fused sensor and simulated stated sensor. The main purpose of the research is to examine the biological sensor performance validation using data fusion technique. Glucose sensor and sucrose sensor were used as the biological sensor. Fusion method used is the state-vector fusion method and a Kalman filter and H-infinity based filter are implemented for enhancing the performance of data fusion algorithm. Simulate the sensor network and deploy the algorithm of data fusion and use neural network for validating the faulty of the sensor network. From the analysis, it was noticed that simulated fused sensor output and target performs well. It was also observed that error rate also minimal in the simulated fused sensor.
Keywords: multi-sensor fusion, biological sensor, data fusion approach, fused sensor, neural network approach,