Density Independent and Temperature Compensated Moisture Prediction Model for Agricultural Products Using Impedance Analyzer: A Review

Agricultural products play an essential role in stabilizing the country economy. Third largest sector of Indian economy is agricultural products. In agricultural products the important factor for post harvesting, processing, storage and transport, is moisture, which affect their quality. In modern agriculture fast, non-destructive and reliable sensing technique for determination of moisture content in agricultural crops is required to prevent the losses and to improve efficiency of production. Various techniques are available for moisture sensing in agricultural products and better results have been achieved with use for these techniques. The performance of developed method for moisture sensing is comparable with that of commercial moisture meter. The most reliable solution for measuring the moisture content of agricultural products and non-destructive method is use of bulk density dielectric function. This paper reviews the area of moisture determination methods for various agricultural products and summarizing the various electrical methods for moisture determination

Porous Alumina Based Capacitive MEMS RH Sensor

The aim of a joint research and development project at the BME and HWU is to produce a cheap, reliable, low-power and CMOS-MEMS process compatible capacitive type relative humidity (RH) sensor that can be incorporated into a state-of-the-art, wireless sensor network. In this paper we discuss the preparation of our new capacitive structure based on post-CMOS MEMS processes and the methods which were used to characterize the thin film porous alumina sensing layer. The average sensitivity is approx. 15 pF/RH% which is more than a magnitude higher than the values found in the literature. The sensor is equipped with integrated resistive heating, which can be used for maintenance to reduce drift, or for keeping the sensing layer at elevated temperature, as an alternative method for temperature-dependence cancellation.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Moisture Sensing in Baled Crops

This dissertation is comprised of three papers. The first paper describes in detail a planar dielectric probe design using finite element analysis to determine sensing range and efficiency. The probe is subsequently connected to a Keysight impedance analyzer to measure dielectric properties of raw cotton at controlled levels of moisture content, compressed densities, and source frequency sweeps. Sensitivity to compositional differences such as turnout (lint vs seed) and variety is also explored. The response to the different factors is shown graphically and further quantified statistically in the form of a predictive model for the complex permittivity (dielectric constant and loss tangent). The second paper extends the dielectric probe used in the first paper to real-time harvesting on a round-module cotton harvester by leveraging a packaged sensor with embedded impedance measurement circuit and probe all in one mobile unit. A moisture prediction model based on permittivity is developed from lab-measured data and adjusted based on field data collected during cotton harvesting in Fall of 2014 for pickers and Spring of 2015 for strippers. Verification of the prediction accuracy is performed on field data collected during cotton harvesting in 2016. Sources of variability and sensitivity to confounding factors are investigated and quantified. Finally, plots of diurnal trends of predicted and actual moisture content are overlaid for several days of harvesting. The third paper draws on the first two in applying capacitive-based moisture sensing to large-square bales of alfalfa. A lab characterization is performed on alfalfa over a wide range of moisture contents and densities using both the Keysight impedance analyzer and packaged sensor to measure permittivity. Field data (on-machine permittivity measurements of bales and corresponding ground truth moisture content) is subsequently collected during baling in 2015 and 2016 for alfalfa hay (\u3c30%) and silage (\u3e30%) and used for training and validation of prediction models. In following with the other two papers, sources of variability are discussed and sensitivity to factors quantified. Limitations in sensing range of the packaged sensor lead to multiple prediction models: a simple but limited model restricted to hay and another using modern fitting techniques (feature engineering and artificial neural network) for both hay and silage. Real-time filtering of the prediction signal is investigated using the simple model in light of what seems like mechanically induced oscillations, using a Kalman filter to isolate and remove them while minimizing delay. The real-time prediction signal is finally overlaid with actual moisture content found from core samples of the same bales

Field Measurements of Soil Water Content at Shallow Depths for Landslide Monitoring

Monitoring changes in soil saturation is important for slope stability analyses. Soil moisture capacitive sensors have recently been developed; their response time is extremely fast, they require little maintenance, and they are relatively inexpensive. The use of low-cost sensors in landslide areas can allow the monitoring of large territories, but appropriate calibration is required. Installation in the field and the setting up of the monitoring network also require attention. In the ALCOTRA AD-VITAM project, the University of Genoa is involved in the development of a system, called LAMP, for the monitoring, analysis and forecasting of slides triggered by rainfalls. Multiple installations (along vertical alignments) of WaterScout sensors are placed in the nodes of the monitoring network. They provide real-time water content profiles in the shallow layers (typically in the upper meter) of a slope. With particular reference to these measurements, the present paper describes the reliability analysis of the instruments, the operations related to the sensor calibration and the installation phases for the monitoring networks. Finally, some of the data coming from a node, belonging to one of the five monitoring networks, are reported

Electrical sensor development for the dielectric properties measurement and moisture content estimation of switchgrass and corn stover

The dielectric properties of material play a relevant role when developing moisture content sensors of agricultural products. However, little is known about the permittivity of switchgrass and corn stover in a wider frequency band. Thus, this research goal was to determine their dielectric constant and loss factor at different moisture contents and frequency range of 5 Hz to 13 MHz. Also, an electrical sensor system was developed to predict the amount of water in agricultural products with the material static and in movement. The dielectric properties of switchgrass and corn stover were calculated by measuring their admittance using an impedance analyzer at three different moisture content levels, approximately between 9 and 30.5% and a fixed bulk density of 0.133 g/cm3. Overall, it was observed that the dielectric properties of these materials increased with moisture content but decreased with frequency. Prediction models were developed using the data of a frequency range of 10 kHz to 5 MHz. These models R2\u27s were higher than 0.90 in general; however, the R2 was 0.9811 for a model in a frequency range from 100 kHz to 5 MHz for the loss factor of switchgrass in movement. A sensor system was designed to generate and read a super-imposed multi-frequency signal that was sent and received from a device under test (DUT) with switchgrass. These input and output signals were analyzed to estimate the moisture content at four levels. Overall, the attenuation between the input and output waves increased with moisture. Two models were created to estimate water from switchgrass. They had an R2 of 0.7901 and 0.9976 for the material static and in movement, respectively. The permittivity of switchgrass and corn stover were successfully estimated for the frequency range of 10 kHz to 5 MHz at three moisture levels. Additionally, the developed sensor system was capable of sensing the moisture of switchgrass, but more investigation is necessary. This study helps to comprehend the influence of the electric field at different frequencies on these materials

New autonomous sensor system for the continous monitoring of the composting process from the inside

The composting process is Nature's way of recycling organic wastes with a good quality organic fertilizer as a result. This process, though, needs of a thoroughly monitoring of temperature and humidity for a good resulting material. During this Ph.D thesis we developed a wireless temperature and humidity autonomous system that monitored from the inside of compost. The fact of measuring and transmitting from the inside implies the need of a protection for the circuit and an issue in the measure. Temperature suffers delays when measuring from the inside of a protection and, as such, we developed an algorithm, implementable on microcontrollers, to counteract the effects of first order step responses. The conditioning has been optimized in terms of components and consumption, obtaining a theoretical and experimental comparative between the classic conditioning and the use of direct interfaces. Commercial humidity sensors need to be in direct contact with the environment they are measuring, but that is not possible in compost since they can get damaged. That is why we designed a humidity sensor based on coplanar capacitive electrodes that can measure through a protection layer. Some theoretical models have been obtained for the physical optimization of both the sensor and the influence of the protective layer. Compost has never been characterised as a transmission environment, and as such, communications in compost are innovative. The heterogeneity of the material and its changes in humidity, temperature and density made the transmission complex. We found the proper frequency band to commercially work in compost and the RF transmission model in compost to estimate attenuation vs distance.El procés de compostatge és la forma que té la natura de reciclar els residus orgànics amb un fertilitzant orgànic de bona qualitat com a resultat. Aquest procés, però, necessita d’una monitorització de la temperatura i la humitat per a obtenir un bon material resultant. Durant aquesta tesi doctoral s'ha desenvolupat un sistema autònom sense fils de mesura de temperatura i humitat des de dins del compost. El fet de que la mesura i la transmissió s’hagin fet des de dins comporta la necessitat d’un material protector per l’electrònica, la qual cosa esdevé un problema en la mesura. La temperatura pateix retards quan es mesura des de dins d’un material protector, i per això, s’ha desenvolupat un algoritme implemetanble en microcontroladors per contrarestar els efectes de respostes esglaó de primer ordre. S'ha optimitzat el condicionament des del punt de vista de components i consum, obtenint una comparativa teòrica i experimental entre els mètodes de condicionament clàssic i l'ús d'interfícies directes. Els sensors de humitat comercials necessiten estar en contacte directe amb l’ambient a mesurar. Això no és possible en el compost ja que es poden malmetre. Per això s’ha dissenyat un sensor d’humitat basat en elèctrodes capacitius plans que poden mesurar a través de capes de protecció. S'han extret models teòrics per l’optimització física tant del sensor com de la influencia de la capa protectora El compost no ha estat mai caracteritzat com un medi de transmissió, i per tant, les comunicacions dins del compost suposen una novetat. La heterogeneïtat del material i els seus canvis en temperatura, humitat i densitat fan de la transmissió un tema complex. S’ha trobat, a més, la banda de freqüència òptima per treballar comercialment i el seu model de transmissió RF estimant l’atenuació en funció de la distànciaPostprint (published version

Quasi-Distributed Fiber Optic Temperature and Humidity Sensor System for Monitoring of Grain Storage in Granaries

Mildew is an important issue in grain storage, due to the very expensive losses that can arise due to grain spoilage by mildew. Monitoring the conditions which allow mildew to develop is important and current monitoring technology cannot readily, or safely, be used for internal humidity monitoring of the very large quantities of grain kept in storage. In this work, a quasi-distributed, tailored fiber optic temperature and humidity sensor system suitable for use in the large granaries has been developed. Dust from the grain is a major issue and the sensor system copes well with this. Various sensor designs have been evaluated and building on prior work, a design with a humidity sensitivity of 5.8pm/%RH, a measurement error of 2%RH, and response time of 4.3 minutes, which is more than adequate for the applications discussed has been developed. Field-testing of the sensor system was carried out at a major storage facility in China, monitoring over an extended period of 4 months, giving results consistent with the outputs from other point sensors currently used in the granary. The fiber optic sensor system developed shows the additional advantages that as a quasi-distributed system, it can be used to record the temperature and humidity distribution across a longitudinal section of the large size of the grain pile, in real time, reflecting the changes in the internal moisture content. The results obtained showed the sensor system has broad market application prospects in this and other important areas of agricultural and food storage

Hybrid Nanostructured Textile Bioelectrode for Unobtrusive Health Monitoring

Coronary heart disease, cardiovascular diseases and strokes are the leading causes of mortality in United States of America. Timely point-of-care health diagnostics and therapeutics for person suffering from these diseases can save thousands of lives. However, lack of accessible minimally intrusive health monitoring systems makes timely diagnosis difficult and sometimes impossible. To remedy this problem, a textile based nano-bio-sensor was developed and evaluated in this research. The sensor was made of novel array of vertically standing nanostructures that are conductive nano-fibers projecting from a conductive fabric. These sensor electrodes were tested for the quality of electrical contact that they made with the skin based on the fundamental skin impedance model and electromagnetic theory. The hybrid nanostructured dry electrodes provided large surface area and better contact with skin that improved electrode sensitivity and reduced the effect of changing skin properties, which are the problems usually faced by conventional dry textile electrodes. The dry electrodes can only register strong physiological signals because of high background noise levels, thus limiting the use of existing dry electrodes to heart rate measurement and respiration. Therefore, dry electrode systems cannot be used for recording complete ECG waveform, EEG or measurement of bioimpedance. Because of their improved sensitivity these hybrid nanostructured dry electrodes can be applied to measurement of ECG and bioimpedance with very low baseline noise. These textile based electrodes can be seamlessly integrated into garments of daily use such as vests and bra. In combination with embedded wireless network device that can communicate with smart phone, laptop or GPRS, they can function as wearable wireless health diagnostic systems

Design and Evaluation of a Non-Intrusive Corn Population Sensor

Specific objectives of this study were to develop, prototype, and test a corn population sensor. Both intrusive mechanical and non-intrusive capacitive techniques have been used to develop the stalk population sensors in previous research. However, neither could generate consistent performance. The mechanical method required high maintenance and resulted in significant underestimations of stalk counts. The performance of capacitive systems was limited by inadequate sensing distance, especially at low stalk moisture levels. In this research, the sensitivity of the capacitive sensor was optimized for corn stalks. This system utilized a single-sided capacitive sensor, Wien bridge oscillator, phase-locked loop, and an operational amplifier to transform stalk presence to a change in electrical potential signal. The capacitive sensor patterns were simulated using the finite element method, which provided useful conceptual information. A number of different detection element patterns were modeled and tested. The patterns examined included single-sided two-plate, interdigital, polarized interdigital, semi-interdigital, and solid ground electrode. The key parameters affecting pattern sensitivity were investigated. The most promising pattern, the solid ground electrode, was selected for further evaluation and development. The solid ground electrode detection element was incorporated into circuitry including Wien-Bridge oscillator, a phase-locked loop used as a high-speed frequency-tovoltage converter, and an operational amplifier to provide impedance matching and maximize data acquisition resolution. The operational configuration, optimum operating parameters, and associated component sizes were determined using both modeling and laboratory testing. With an acceptable signal-sided pattern and signal-to-noise ratio, this sensing system was investigated in a realistic production environment. A preliminary field test was used to evaluate the sensor system (including a protective housing and mounting system) and data acquisition system to identify problems before conducting the final field test. Stalk moisture content and harvest speed were used as treatment blocks in the final test. The influences of environmental and mechanical noise and the noise-like influence of corn leaves and weeds were also investigated. The final field test accurately simulated realistic harvesting conditions and real-time data was collected for stalk identification analysis. Post-acquisition processing, feature extraction, and principal component analysis of the extracted features were performed on the raw field data. Three sensor signal features were selected to identify stalks. A backpropagation artificial neural network technique was used to develop the pattern classification model. Numerous neural network structures were evaluated and two-layer structure with four neurons in the first layer and one neuron in the second layer was selected based on maximum prediction precision and accuracy and minimum structure complexity. This structure was then evaluated to determine the prediction accuracy at various resolution levels. Results showed that the model can predict stalk population at 99.5% accuracy when the spatial resolution is 0.025 ha. The sensor can predict stalk population with a 95% accuracy when the resolution is a 9-meter row segment (approximately 10 seconds)

New Electronic Interface Circuits for Humidity Measurement Based on the Current Processing Technique

The paper describes a new electronic conditioning circuit based on the current-processing technique for accurate and reliable humidity measurement, without post-processing requirements. Pseudobrookite nanocrystalline (Fe2TiO5) thick film was used as capacitive humidity transducer in the proposed design. The interface integrated circuit was realized in TSMC 0.18 mu m CMOS technology, but commercial devices were used for practical realization. The sensing principle of the sensor was obtained by converting the information on environment humidity into a frequency variable square-wave electric current signal. The proposed solution features high linearity, insensitivity to temperature, as well as low power consumption. The sensor has a linear function with relative humidity in the range of Relative Humidity (RH) 30-90 %, error below 1.5 %, and sensitivity 8.3 x 10(14) Hz/F evaluated over the full range of changes. A fast recovery without the need of any refreshing methods was observed with a change in RH. The total power dissipation of readout circuitry was 1 mW