Browsing by Subject "Sensor networks"

Now showing 1 - 6 of 6
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    A Compressed Data Collection System For Use In Wireless Sensor Networks
    (2013-03-06) Erratt, Newlyn S.; Liang, Yao; Raje, Rajeev; Tuceryan, Mihran
    One of the most common goals of a wireless sensor network is to collect sensor data. The goal of this thesis is to provide an easy to use and energy-e fficient system for deploying data collection sensor networks. There are numerous challenges associated with deploying a wireless sensor network for collection of sensor data; among these challenges are reducing energy consumption and the fact that users interested in collecting data may not be familiar with software design. This thesis presents a complete system, comprised of the Compression Data-stream Protocol and a general gateway for data collection in wireless sensor networks, which attempts to provide an easy to use, energy efficient and complete system for data collection in sensor networks. The Compressed Data-stream Protocol is a transport layer compression protocol with a primary goal, in this work, to reduce energy consumption. Energy consumption of the radio in wireless sensor network nodes is expensive and the Com-pressed Data-stream Protocol has been shown in simulations to reduce energy used on transmission and reception by around 26%. The general gateway has been designed in such a way as to make customization simple without requiring vast knowledge of sensor networks and software development. This, along with the modular nature of the Compressed Data-stream Protocol, enables the creation of an easy to deploy and easy to configure sensor network for data collection. Findings show that individual components work well and that the system as a whole performs without errors. This system, the components of which will eventually be released as open source, provides a platform for researchers purely interested in the data gathered to deploy a sensor network without being restricted to specific vendors of hardware.
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    Designing and experimenting with e-DTS 3.0
    (2014-08-29) Phadke, Aboli Manas; Raje, Rajeev; Tuceryan, Mihran; Liang, Yao
    With the advances in embedded technology and the omnipresence of smartphones, tracking systems do not need to be confined to a specific tracking environment. By introducing mobile devices into a tracking system, we can leverage their mobility and the availability of multiple sensors such as camera, Wi-Fi, Bluetooth and Inertial sensors. This thesis proposes to improve the existing tracking systems, enhanced Distributed Tracking System (e-DTS 2.0) [19] and enhanced Distributed Object Tracking System (eDOTS)[26], in the form of e-DTS 3.0 and provides an empirical analysis of these improvements. The enhancements proposed are to introduce Android-based mobile devices into the tracking system, to use multiple sensors on the mobile devices such as the camera, the Wi-Fi and Bluetooth sensors and inertial sensors and to utilize possible resources that may be available in the environment to make the tracking opportunistic. This thesis empirically validates the proposed enhancements through the experiments carried out on a prototype of e-DTS 3.0.
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    Embedded System for Sensor Communication and Security
    (2010) An, Feng; Rizkalla, Maher; Li, Lingxi; Du, Yingzi; Salama, Paul; Knieser, Michael
    In this work, inter-integrated circuit mode (I2C) software was used to communicate between sensors and the embedded control system, utilizing PIC182585 MPLAB hardware. These sensors were built as part of a system on board that includes the sensors, microcontroller, and interface circuitry. The hardware includes the PIC18 processor, FPGA chip, and peripherals. A FPGA chip was used to interface the processor with the peripherals in order to operate at the same clock speed. This hardware design features high level of integration, reliability, high precision, and high speed communications. The software was first designed to operate each sensor separately, then the sensor system was integrated (to combine all sensors, microcontroller, and interfacing circuitries), and the software was updated to provide various actions if triggered by the sensors. Actions taken by the processor may include alarming signals that are based on threshold values received from the sensors, and inquiring temperature and CO2 readings. The system was designed for HVAC (heating, ventilating and air conditioning) applications and industrial settings. The overall system incorporating temperature and CO2 sensors was implemented and successfully tested. The response of the multi-sensor system was agreeable with the design parameters. The system may be expanded to include other sensors such as light senor, pressure sensor, etc. Monitoring the threshold values should add to the security features of the integrated communication system. This design features low power consumption (utilizing the sleeping mode of the processors), high speed communications, security, and flexibility to expansion.
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    Low-power ASIC design with integrated multiple sensor system
    (2013-08) Jafarian, Hossein; Varahramyan, Kody; Rizkalla, Maher E.; Agarwal, Mangilal; Shrestha, Sudhir; King, Brian
    A novel method of power management and sequential monitoring of several sensors is proposed in this work. Application specific integrated circuits (ASICs) consisting of analog and digital sub-systems forming a system on chip (SoC) has been designed using complementary metal-oxide-semiconductor (CMOS) technology. The analog sub-system comprises the sensor-drivers that convert the input voltage variations to output pulse-frequency. The digital sub-system includes the system management unit (SMU), counter, and shift register modules. This performs the power-usagemanagement, sensor-sequence-control, and output-data-frame-generation functions. The SMU is the key unit within the digital sub-system is that enables or disables a sensor. It captures the pulse waves from a sensor for 3 clocks out of a 16-clock cycle, and transmits the signal to the counter modules. As a result, the analog sub-system is at on-state for only 3/16th fraction (18 %) of the time, leading to reduced power consumption. Three cycles is an optimal number selected for the presented design as the system is unstable with less than 3 cycles and higher clock cycles results in increased power consumption. However, the system can achieve both higher sensitivity and better stability with increased on-state clock cycles. A current-starved-ring-oscillator generates pulse waves that depend on the sensor input parameter. By counting the number of pulses of a sensor-driver in one clock cycle, a sensor input parameter is converted to digital. The digital sub-system constructs a 16-bit frame consisting of 8-bit sensor data, start and stop bits, and a parity bit. Ring oscillators that drive capacitance and resistance-based sensors use an arrangement of delay elements with two levels of control voltages. A bias unit which provides these two levels of control voltages consists of CMOS cascade current mirror to maximize voltage swing for control voltage level swings which give the oscillator wider tuning range and lower temperature induced variations. The ring oscillator was simulated separately for 250 nm and 180 nm CMOS technologies. The simulation results show that when the input voltage of the oscillator is changed by 1 V, the output frequency changes linearly by 440 MHz for 180 nm technology and 206 MHz for 250 nm technology. In a separate design, a temperature sensitive ring oscillator with symmetrical load and temperature dependent input voltage was implemented. When the temperature in the simulation model was varied from -50C to 100C the oscillator output frequency reduced by 510 MHz for the 250 nm and by 810 MHz for 180 nm CMOS technologies, respectively. The presented system does not include memory unit, thus, the captured sensor data has to be instantaneously transmitted to a remote station, e.g. end user interface. This may result in a loss of sensor data in an event of loss of communication link with the remote station. In addition, the presented design does not include transmitter and receiver modules, and thus necessitates the use of separate modules for the transfer of the data.
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    Modeling, monitoring and optimization of discrete event systems using Petri nets
    (2014-01-29) Yan, Jiaxiang; Li, Lingxi; King, Brian; Chen, Yaobin
    Yan, Jiaxiang. M.S.E.C.E., Purdue University, May 2013. Modeling, Monitoring and Optimization of Discrete Event Systems Using Petri Nets. Major Professor: Lingxi Li. In last decades, the research of discrete event systems (DESs) has attracts more and more attention because of the fast development of intelligent control strategies. Such control measures combine the conventional control strategies with discrete decision-making processes which simulate human decision-making processes. Due to the scale and complexity of common DESs, the dedicated models, monitoring methods and optimal control strategies for them are necessary. Among various DES models, Petri nets are famous for the advantage in dealing with asynchronous processes. They have been widely applied in intelligent transportation systems (ITS) and communication technology in recent years. With encoding of the Petri net state, we can also enable fault detection and identification capability in DESs and mitigate potential human errors. This thesis studies various problems in the context of DESs that can be modeled by Petri nets. In particular, we focus on systematic modeling, asynchronous monitoring and optimal control strategies design of Petri nets. This thesis starts by looking at the systematic modeling of ITS. A microscopic model of signalized intersection and its two-layer timed Petri net representation is proposed in this thesis, where the first layer is the representation of the intersection and the second layer is the representation of the traffic light system. Deterministic and stochastic transitions are both involved in such Petri net representation. The detailed operation process of such Petri net representation is stated. The improvement of such Petri net representation is also provided with comparison to previous models. Then we study the asynchronous monitoring of sensor networks. An event sequence reconstruction algorithm for a given sensor network based on asynchronous observations of its state changes is proposed in this thesis. We assume that the sensor network is modeled as a Petri net and the asynchronous observations are in the form of state (token) changes at different places in the Petri net. More specifically, the observed sequences of state changes are provided by local sensors and are asynchronous, i.e., they only contain partial information about the ordering of the state changes that occur. We propose an approach that is able to partition the given net into several subnets and reconstruct the event sequence for each subnet. Then we develop an algorithm that is able to reconstruct the event sequences for the entire net that are consistent with: 1) the asynchronous observations of state changes; 2) the event sequences of each subnet; and 3) the structure of the given Petri net. We discuss the algorithmic complexity. The final problem studied in this thesis is the optimal design method of Petri net controllers with fault-tolerant ability. In particular, we consider multiple faults detection and identification in Petri nets that have state machine structures (i.e., every transition in the net has only one input place and one output place). We develop the approximation algorithms to design the fault-tolerant Petri net controller which achieves the minimal number of connections with the original controller. A design example for an automated guided vehicle (AGV) system is also provided to illustrate our approaches.
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    Secure data aggregation protocol for sensor networks
    (2015-02-20) Shah, Kavit; King, Brian; El-Sharkawy, Mohammed; Salama, Paul
    We propose a secure in-network data aggregation protocol with internal verification, to gain increase in the lifespan of the network by preserving bandwidth. For doing secure internal distributed operations, we show an algorithm for securely computing the sum of sensor readings in the network. Our algorithm can be generalized to any random tree topology and can be applied to any combination of mathematical functions. In addition, we represent an efficient way of doing statistical analysis for the protocol. Furthermore, we propose a novel, distributed and interactive algorithm to trace down the adversary and remove it from the network. Finally, we do bandwidth analysis of the protocol and give the proof for the efficiency of the protocol.