Spectral analysis of photonic crystal based bio-sensor using AdaBoost algorithm
Photonic is the study that includes the use of light, where the fundamental element is photon. The optics is the branch of the physics which deals with the properties of the light. In this paper the sensor is designed to detect the glucose content of human body and the spectrum from the output of the sensor is analyzed by using AdaBoost algorithm. The Adaptive Boosting in short considered to be AdaBoost algorithm. The classification of the multiple discrete weak classifiers allowing the formation of strong classifier by integrating, provides better improved performance using the concept of AdaBoost. The AdaBoost is used widely in almost all fields like physical sensing, chemical sensing, bio sensing etc. This paper primarily based on analyzing the spectrum from the bio sensors. The major role of the machine language is that it gives the accurate outputs which is easily understood by all the humans without having the knowledge on that particular field. Using the AdaBoost along with the photonic crystals based designs, the sensing technology can be improved in accuracy, sensitivity and specificity. Thus this can be successfully implemented in detection of Diabetic patient. The simulation tool that is used in the paper is MEEP, Mat Lab.