Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Studies on glass transition and starch re-crystallization in wheat bread during staling using electrical impedance spectroscopy

Bread staling is a very complex phenomenon that is not yet completely understood. The present work explains how the electrical impedance spectroscopy technique can be utilized to investigate the effect of staling on the physicochemical properties of wheat bread during storage. An instrument based on electrical impedance spectroscopy technique is developed to study the electrical properties of wheat bread both at its crumb and crust with the help of designed multi-channel ring electrodes. Electrical impedance behavior, mainly capacitance and resistance, of wheat bread at crust and crumb during storage (up to 120 h) is investigated. The variation in capacitance showed the glass transition phenomenon at room temperature in bread crust after 96 h of storage with 18% of moisture in it. The resistance changes at bread crumb showed the starch recrystallization during staling.

Studies on the Tracking and Erosion Resistance of RTV Silicone Rubber Nanocomposite

One of the problems associated with outdoor polymeric insulators is tracking and erosion of the weathershed which can directly influence the reliability of the power system. Flame retardants are added to the base material to enhance its tracking and erosion resistance. Hydroxide fillers are regarded as the best flame retardants. This paper deals with studies related to nano - sized magnesium dihydroxide (MDH) and micron-sized Alumina Trihydrate (ATH) fillers as flame retardants in RTV silicone rubber. Tracking and erosion resistance studies were carried out on MDH and ATH silicone rubber composites using an inclined plane tracking and erosion (IPT) resistance tester. The MDH filled (5% by wt) composites performed much better than ATH composites in terms of eroded mass, depth of erosion, width and length of erosion. The eroded mass of MDH composite is 49.8 % that of ATH composite which can be attributed to high surface area and higher thermal stability of MDH nanofillers.

Electrical Discharge Resistant Characteristics of Epoxy Nanocomposites

This paper reports the electrical discharge resistant characteristics of epoxy nanocomposite systems with SiO2 and Al2O3 nano-fillers. A comparative study is performed between unfilled epoxy systems, nanoparticle filled epoxy systems and a bimodal system containing both micrometer and nanometer sized fillers of the same material. The samples are exposed to surface discharges and the levels of surface degradation are analyzed through SEM and surface roughness measurements. Significant variations were observed in the electrical discharge resistant characteristics between the different composite systems and it is seen that the introduction of nano-fillers to epoxy is advantageous in improving the electrical discharge resistance of epoxy.

Microprocessor-based temperature indicator using a thermistor as the sensor

A novel microprocessor-based temperature indicator has been developed and described. This indicator provides a linear performance over a wide dynamic temperature range of 0-100°C with an accuracy of ±0-l°C. The interfacing module reduces computing time required by the microprocessor for solving the thermistor equation. Test results are given to support the theory.

Resistance Noise in Graphene Based Field Effect Devices

We present a low-frequency electrical noise measurement in graphene based field effect transistors. For single layer graphene (SLG), the resistance fluctuations is governed by the screening of the charge impurities by the mobile charges. However, in case of Bilayer graphene (BLG), the electrical noise is strongly connected to its band structure, and unlike single layer graphene, displays a minimum when the gap between the conduction and valence band is zero. Using double gated BLG devices we have tuned the zero gap and charge neutrality points independently, which offers a versatile mechanism to investigate the low-energy band structure, charge localization and screening properties of bilayer graphene

Behavior Of High-Voltage Machine Insulation System In The Presence Of Thermal And Electrical Stresses

This paper presents the results on a resin-rich machine insulation system subjected to varying stresses such as electrical (2.6 to 13.3 MV/m) and thermal (40 to 155° C) acting together. Accelerated electro-thermal aging experiments subsequently have been performed to understand the insulation degradation The interpretations are based on several measured properties like capacitance, loss tangent, ac resistance, leakage current, and partial discharge quantities. The results indicate that the changes in properties are not significant below a certain temperature for any applied stress, Beyond this temperature large variations are observed even for low electrical stresses. Electrothermal aging studies reveal that the acceleration of the insulation degradation and the ultimate time to failure depends on the relative values of temperature and voltage stresses. At lower temperatures, below critical, material characteristics of the system predominate whereas beyond this temperature, other phenomena come into play causing insulation deterioration. During aging under combined stresses, it appears that the prevailing temperature of the system has a significant role in the insulation degradation and ultimate failure.

Efficient Energy Management Policies for Networks with Energy Harvesting Sensor Nodes

We study sensor networks with energy harvesting nodes. The generated energy at a node can be stored in a buffer. A sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time at the node. For such networks we develop efficient energy management policies. First, for a single node, we obtain policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable suboptimal policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay. Next using the results for a single node, we develop efficient MAC policies.

Zinc, cadmium and lead resistance mechanisms in bacteria and their contribution to biosensing

In bacteria resistance to heavy metals is mainly achieved through active efflux, but also sequestration with proteins or as insoluble compounds is used. Although numerous studies have dealt with zinc, cadmium and lead resistance mechanisms in bacteria, it has still remained unclear how different transporters are integrated into an effective homeostasis/resistance network and whether specific mechanisms for lead sequestration exist. Furthermore, since metals are toxic not only to bacteria but to higher organisms as well, it is important to be able to estimate possible biological effects of heavy metals in the environment. This could be done by determining the bioavailable amount of the metals in the environment with bacterial bioreporters. That is, one can employ bacteria that respond to metal contamination by a measurable signal to assess the property of metals to cross biological membranes and to cause harmful effects in a possibly polluted environment. In this thesis a new lead resistance mechanism is described, interplay between CBA transporters and P-type ATPases in zinc and cadmium resistance is presented and finally the acquired knowledge is used to construct bacterial bioreporters for heavy metals with increased sensitivity and specificity. The new lead resistance model employs a P-type ATPase that removes Pb2+ ions from the cytoplasm and a phosphatase that produces inorganic phosphate for lead sequestration in the periplasm. This was the first study where the molecular mechanism of lead sequestration has been described. Characterization of two P-type ATPases and two CBA transporters showed that resistance mechanisms for Zn2+ and Cd2+ are somewhat different than for Pb2+ as these metals cannot be sequestered as insoluble compounds as easily. Resistance to Zn2+ was conferred merely by the CBA transporter that could export both cytoplasmic and periplasmic ions; whereas, full resistance to Cd2+ required interplay of a P-type ATPase that exported cytoplasmic ions to periplasm and a CBA transporter that further exported periplasmic ions to the outside. The knowledge on functionality of the transporters and metal-inducible promoters was exploited in bioreporter technology. A transporter-deficient bioreporter strain that lacked exporters for Zn2+/Cd2+/Pb2+ could detect up to 45-fold lower metal concentrations than its wild type counterpart due to the accumulation of metals in the cell. The broad specificity issue of bioreporters was overcome by using Zn-specific promoter as a sensor element, thus achieving Zn-specific bioreporter.

Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

Negative resistance mode of forced oscillations of a string

A new mode of driven nonlinear vibrations of a stretched string is investigated with reference to conditions of existence, properties, and regions of stability. It is shown that this mode exhibits negative resistance properties at all frequencies and driving force amplitudes. Discovery of this mode helps to fill certain gaps in the theory of forced nonlinear vibrations of strings.

Quality of ALICE SSD modules revealed by electrical tests

ALICE (A Large Ion Collider Experiment) is an experiment at CERN (European Organization for Nuclear Research), where a heavy-ion detector is dedicated to exploit the unique physics potential of nucleus-nucleus interactions at LHC (Large Hadron Collider) energies. In a part of that project, 716 so-called type V4 modules were assembles in Detector Laboratory of Helsinki Institute of Physics during the years 2004 - 2006. Altogether over a million detector strips has made this project the most massive particle detector project in the science history of Finland. One ALICE SSD module consists of a double-sided silicon sensor, two hybrids containing 12 HAL25 front end readout chips and some passive components, such has resistors and capacitors. The components are connected together by TAB (Tape Automated Bonding) microcables. The components of the modules were tested in every assembly phase with comparable electrical tests to ensure the reliable functioning of the detectors and to plot the possible problems. The components were accepted or rejected by the limits confirmed by ALICE collaboration. This study is concentrating on the test results of framed chips, hybrids and modules. The total yield of the framed chips is 90.8%, hybrids 96.1% and modules 86.2%. The individual test results have been investigated in the light of the known error sources that appeared during the project. After solving the problems appearing during the learning-curve of the project, the material problems, such as defected chip cables and sensors, seemed to induce the most of the assembly rejections. The problems were typically seen in tests as too many individual channel failures. Instead, the bonding failures rarely caused the rejections of any component. One sensor type among three different sensor manufacturers has proven to have lower quality than the others. The sensors of this manufacturer are very noisy and their depletion voltage are usually outside of the specification given to the manufacturers. Reaching 95% assembling yield during the module production demonstrates that the assembly process has been highly successful.

LPG Gas-Sensing System With SnO2 Thin-Film Transducer and 0.7-mu m CMOS Signal Conditioning ASIC

The design and implementation of a complete gas sensor system for liquified petroleum gas (LPG) gas sensing are presented. The system consists of a SnO2 transducer, a lowcost heater, an application specific integrated circuit (ASIC) with front-end interface circuitry, and a microcontroller interface for data logging. The ASIC includes a relaxation-oscillator-based heater driver circuit that is capable of controlling the sensor operating temperature from 100degC to 425degC. The sensor readout circuit in the ASIC, which is based on the resistance to time conversion technique, has been designed to measure the gas sensor response over three orders of resistance change during its interaction with gases.