Unsupervised Learning-Based WSN Clustering for Efficient Environmental Pollution Monitoring

Wireless Sensor Networks (WSNs) have been adopted in various environmental pollution monitoring applications. As an important environmental field, water quality monitoring is a vital process to ensure the sustainable, important feeding of and as a life-maintaining source for many living creatures. To conduct this process efficiently, the integration of lightweight machine learning technologies can extend its efficacy and accuracy. WSNs often suffer from energy-limited devices and resource-affected operations, thus constraining WSNs’ lifetime and capability. Energy-efficient clustering protocols have been introduced to tackle this challenge. The low-energy adaptive clustering hierarchy (LEACH) protocol is widely used due to its simplicity and ability to manage large datasets and prolong network lifetime. In this paper, we investigate and present a modified LEACH-based clustering algorithm in conjunction with a K-means data clustering approach to enable efficient decision making based on water-quality-monitoring-related operations. This study is operated based on the experimental measurements of lanthanide oxide nanoparticles, selected as cerium oxide nanoparticles (ceria NPs), as an active sensing host for the optical detection of hydrogen peroxide pollutants via a fluorescence quenching mechanism. A mathematical model is proposed for the K-means LEACH-based clustering algorithm for WSNs to analyze the quality monitoring process in water, where various levels of pollutants exist. The simulation results show the efficacy of our modified K-means-based hierarchical data clustering and routing in prolonging network lifetime when operated in static and dynamic contexts

Structural damage detection using ambient vibrations

Master of ScienceDepartment of Civil EngineeringHani G. MelhemThe objective of this research is to use structure ambient random vibration response to detect damage level and location. The use of ambient vibration is advantageous because excitation is caused by service conditions such as normal vehicle traffic on a highway bridge, train passage on a railroad bridge, or wind loads on a tall building. This eliminates the need to apply a special impact or dynamic load, or interrupt traffic on a bridge in regular service. This research developed an approach in which free vibration of a structure is extracted from the response of this structure to a random excitation in the time domain (acceleration versus time) by averaging out the random component of the response. The result is the free vibration that includes all modes based on the sampling rate on time. Then this free vibration is transferred to the frequency domain using a Fast Fourier Transform (FFT). Variations in frequency response are a function of structural stiffness and member end-conditions. Such variations are used as a measure to identify the change in the structural dynamic properties, and ultimately detect damage. A physical model consisting of a 20 × 20 × 1670 -mm long steel square tube was used to validate this approach. The beam was tested under difference supports conditions varying from a single- to three-span continuous configuration. Random excitation was applied to the beam, and the dynamic response was measured by an accelerometer placed at various locations on the span. A numerical model was constructed in ABAQUS and the dynamic response was obtained from the finite element model subjected to similar excitation as in the physical model. Numerical results were correlated against results from the physical model, and comparison was made between the different span/support configurations. A subsequent step would be to induce damage that simulates loss of stiffness or cracking condition of the beam cross section, and that would be reflected as a change in the frequency and other dynamic properties of the structure. The approach achieved good results for a structure with a limited number of degrees of freedom. Further research is needed for structures with a larger number of degrees of freedom and structures with damage in symmetrical locations relative to the accelerometer position

Unsupervised Learning-Based WSN Clustering for Efficient Environmental Pollution Monitoring

Wireless Sensor Networks (WSNs) have been adopted in various environmental pollution monitoring applications. As an important environmental field, water quality monitoring is a vital process to ensure the sustainable, important feeding of and as a life-maintaining source for many living creatures. To conduct this process efficiently, the integration of lightweight machine learning technologies can extend its efficacy and accuracy. WSNs often suffer from energy-limited devices and resource-affected operations, thus constraining WSNs’ lifetime and capability. Energy-efficient clustering protocols have been introduced to tackle this challenge. The low-energy adaptive clustering hierarchy (LEACH) protocol is widely used due to its simplicity and ability to manage large datasets and prolong network lifetime. In this paper, we investigate and present a modified LEACH-based clustering algorithm in conjunction with a K-means data clustering approach to enable efficient decision making based on water-quality-monitoring-related operations. This study is operated based on the experimental measurements of lanthanide oxide nanoparticles, selected as cerium oxide nanoparticles (ceria NPs), as an active sensing host for the optical detection of hydrogen peroxide pollutants via a fluorescence quenching mechanism. A mathematical model is proposed for the K-means LEACH-based clustering algorithm for WSNs to analyze the quality monitoring process in water, where various levels of pollutants exist. The simulation results show the efficacy of our modified K-means-based hierarchical data clustering and routing in prolonging network lifetime when operated in static and dynamic contexts

IIT Sustainability Branding (Semester Unknown) IPRO 311: IITSustainableBrandingIPRO311MidTermPresentationSp09

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable

IIT Sustainability Branding (Semester Unknown) IPRO 311: IITSustainableBrandingIPRO311BrochureSp09

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable

IIT Sustainability Branding (Semester Unknown) IPRO 311: IITSustainableBrandingIPRO311ProjectPlanSp09_redacted

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable

IIT Sustainability Branding (Semester Unknown) IPRO 311: IITSustainableBrandingIPRO311FinalPresentationSp09

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable

IIT Sustainability Branding (Semester Unknown) IPRO 311: IITSustainableBrandingIPRO311FinalReportSp09

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable

IIT Sustainability Branding (Semester Unknown) IPRO 311: IITSustainableBrandingIPRO311AbstractSp09

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable

IIT Sustainability Branding (Semester Unknown) IPRO 311

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable