Noise and time-dependent fluctuations are usually undesirable signals. However, they have many applications. This dissertation deals with two kinds of sensing applications of fluctuation and noise: soil bulk density assessment and bacterium sensing. The measurement of Vibration-Induced Conductivity Fluctuations (VICOF) provides information about the bulk density and other parameters of soils. Bulk density is the physical property of soils that is important to both the agriculture and construction industries. The traditional measurements of soil bulk density are often time-consuming, expensive or destructive. To determine the soil bulk density without the above drawbacks, the VICOF measurement scheme was proposed. The research of VICOF in this dissertation includes two parts: the initial phase of study and the new methods and their theory. In the initial phase of study, the simple experiments, theory, and simulations of VICOF were tested for relations between the soil bulk density, wetness, salinity, and the VICOF data. Then, new measurement arrangements and their theoretical models were proposed to improve the weaknesses of the initial approach (such as large scattering of data due to loose and heavy contacts) and to calculate the relationship between the measured signals and the electromechanical transport parameters of the soils. The bacterium sensing study in this dissertation was proposed to explore simple, practical, rapid, sensitive, specific, portable, and inexpensive ways to detect and recognize bacteria by Fluctuation-Enhanced Sensing (FES). One such potential way of bacterium sensing is to analyze their odor. The research of bacterium sensing also includes two parts: the initial phase of study and the new methods and their theory. The initial phase study was proposed to explore the possibility of detecting and identifying bacteria by sensing their odor via FES with commercial Taguchi sensors. Then the subsequently developed new methods and their theory provide a simple way to generate binary patterns with perfect reproducibility based on the spectral slopes in different frequency ranges at FES. This new type of signal processing and pattern recognition is implemented at the block diagram level using the building elements of analog circuitries and a few logic gates with total power consumption in the microWatts range.

Nanostructures are nanometer scale structures (characteristic length less than 100 nm) such as nanowires, ultra-small junctions, etc. Since nanostructures are less stable, their characteristic volume is much smaller compared to defect sizes and their characteristic length is close to acoustical phonon wavelength. Moreover, because nanostructures include significantly fewer charge carriers than microscale structures, electronic noise in nanostructures is enhanced compared to microscale structures. Additionally, in microprocessors, due to the small gate capacitance and reduced noise margin (due to reduced supply voltage to keep the electrical field at a reasonable level), the electronic noise results in bit errors. On the other hand, the enhanced noise is useful for advanced sensing applications which are called fluctuation-enhanced sensing. In this dissertation, we first survey our earlier results about the limitation of noise posed on specific nano processors. Here, single electron logic is considered for voltage controlled logic with thermal excitations and generic shot noise is considered for current-controlled logic. Secondly, we discuss our recent results on the electronic noise in nanoscale sensors for SEnsing of Phage-Triggered Ion Cascade (SEPTIC, for instant bacterial detection) and for silicon nanowires for viral sensing. In the sensing of the phage-triggered ion cascade sensor, bacteriophage-infected bacteria release potassium ions and move randomly at the same time; therefore, electronic noise (i.e., stochastic signals) are generated. As an advanced model, the electrophoretic effect in the SEPTIC sensor is discussed. In the viral sensor, since the combination of the analyte and a specific receptor located at the surface of the silicon nanowire occurs randomly in space and time, a stochastic signal is obtained. A mathematical model for a pH silicon nanowire nanosensor is developed and the size quantization effect in the nanosensor is also discussed. The calculation results are in excellent agreement with the experimental results in the literature.

The master's thesis deals with the question of breath analysis using chemiresistors as detection elements for exhaled air analysis. Emphasis is placed on the application of fluctuation-enhanced sensing for chemiresistors for breath analysis, construction design of usable measurement system, and its calibration. Compared to the usual concept, which includes various methods ranging from DC processing in time to controlled impedance measurement, this method of signal analysis focuses on the evaluation of fluctuations and determination of indicators of its change in dependence of change in detected substance concentration.