tagless long/distance capacitive sensors for indoor human localization

Indoor Human localization:it’s main idea is to identify the location of a person inside a house as the person operates his/her daily routines. In smart homes and assisted living environments (like health centers) knowing the location of a person is important for different services that require locational information like heating, turning on lights, opening doors or behavioral recognition and notification of abnormalities. There are different technologies that are used for indoor human localization. Applications based on pressure, infrared RFID, bluetooth and ultrasonic sensors can be found each with its own advantage and limitations in-terms of precision and infrastructure cost. Capacitive sensing is especially interesting in the area of indoor human localization due to it’s many complementary characteristics to other same kind application sensing systems. Capacitive sensing system work in different modes. Our interest is the loading operating mode, where only one electrode is required. The capacitance coupling between the human-body and electrode keeps varying as the distance between them is varied. The output capacitance interfaced with data acquisition and localization algorithm is used to infer/estimate the position of the person. This thesis tries to optimize an ongoing project:tag-less human indoor localization mainly by working on two topics: The first is to characterize commercial ultrasonic based indoor navigation systems. To see if they are dependable to use them as a reference positions (real time) data input for training and checking the localization algorithm. In previous experiments synthetic data were used as a sensor readings to infer the location of the person under tracking. The second aim of this project is optimizing frequency measurement as a proxy of capacitance measurement for ATmega328p micro-controller: by reducing the time taking to measure frequency (which in turn increase speed and reduce power consumption) and by increasing the resolution so that small (fractional) changes of frequency is taken in to account. Because at long distance the change in capacitance is very small which leads to a small changes of frequency even when the person makes a large movement. In characterizing the ultrasonic based indoor navigation systems, the analysis of the experiments/tests shows that the accuracy was in the expected range. However some spikes were observed. This could be because the experiment is conducted in a lab environment where there are many instruments that could interfere with the ultrasonic sensors. The way the sensors are installed is also an important factor in getting better accuracy (a line of sight and a specific amount of distance between adjacent beacons is required). Moreover the accuracy of the sensor is affected by temperature and humidity variations. If the sensor is tested in controlled enviroment by avoiding the listed limitation, better accuracy can be obtained In designing the frequency meter, an algorithm is developed for measuring the frequency from capacitive sensor nodes by counting the exact full periods of the signal being measured (which is correlated with the capacitance between human body and the sensor, converted using a relaxation oscillator) for 40ms. The output frequency from the relaxation oscillator is measured by using ATmega328p micro-controller. The accuracy of the frequency measuring firmware around 100kHz is 0.305Hz. Compared to the previous measuring method which took one second, in this system higher speed and accuracy is achieved.